Improvement of rearing goats in Bali Province, Indonesia687794/s005151_phd_correcte… · Banjar,...

Improvement of rearing goats in Bali Province, Indonesia

Lindawati Doloksaribu

B.Sc., M. App. Sc.

A thesis submitted for the degree of Doctor of Philosophy at

The University of Queensland in 2017

School of Agriculture and Food Sciences

Abstract

i

Abstract

Lack of baseline quantitative data on the reproductive and productive performance of goats in Bali

Province has limited our ability to identify factors that could lead to their improvement. This study

aimed to rectify this lack of data and to measure constraints to, challenges of, and opportunities for

improving goat production in Bali, through a hybrid method of Strengths, Weaknesses,

Opportunities and Threats and Analytic Hierarchy Process analyses.

Data was collected through direct observations, structured formal household interviews, key

informant interviews, focus group discussions, and case studies as well as from the surrounding

environment and market assessments from January to September 2014. This involved interviewing

175 households with 2,017 goats. Of these, 63 households with 1,169 goats were in Rendang

District, Karangasem Regency; 44 households with 590 goats were in Banjar, Busungbiu and

Grogak Districts in Buleleng Regency; and 68 households with 258 goats were in Mendoyo

District, Jembrana Regency. Data was analysed by using descriptive statistics, correlate bivariate

and general linear model multivariate using SPSS version 24.

Results revealed that households had an average of 2.3 labourers with a ratio of 5.2 ± 0.4 goats per

labourer who were aged 42 ± 1 year. This indicated that household labourers in Bali Province

worked 412 ± 9.9 hours/household/year to look after 11.5 ± 0.9 goats/flock in either battery or

colony housing with a cut and carry feeding system. Farmers cultivated on average 1.4 ± 0.05

ha/household with vegetables or commodity plantations integrated with goat rearing for 10.5 ± 0.7

years. Of the 175 farmers, 63%, 21% and 15% of farmers graduated from Grades 6, 9 and 12,

respectively, and only one farmer graduated from university.

A mixture of Gembrong, Benggala, Kacang, Etawah Grade, PE, Boer, Boerawa and their crossbreds

or backcrosses had an average kidding interval of about 8 months, bodyweight of 26.5 ± 0.2 kg and

no clinical anaemia (as indicated by an average FAMACHA©

score of 1.8). No pure Kacang goats

with small bodies and erect short ears were found. All goats observed had short or long floppy ears

of various lengths and widths. There were no significant differences between battery and colony

housing on gross margin (GM)/doe or on the bodyweights of goats (P>0.05); with goats on slatted

floors it was easier to collect their manure, more hygienic and profitable.

Average annual GM/doe per household across the 175 households was a loss of IDR 0.930 ± 0.148

million ranging from a loss of IDR 8.434 million to a profit of IDR 4.707 million per farm. The

economic loss on some farms may indicate an undervaluing of the labour input, or that goats were

Abstract

ii

raised for other than economic reasons, as a sideline enterprise. Of the 2,017 goats studied, 835

goats were sold in 2014 for the total price of IDR 1,357 million that contributed 82% to the annual

income of IDR 1,660 million. The largest GM/doe per household studied was IDR 4.707 million

when the household had a flock of 39 goats including 10 does, and they sold 37 goats or had a 96%

turn off rate in 2014. This household generated annual income of IDR 64.225 million and gross

margin of IDR 47.072 million. In contrast, the lowest GM/doe per household was a loss of IDR

8.434 million and annual income of IDR 0.639 million when the household had a flock of seven

goats including one doe and they sold no goats in 2014. Of the 175 households, 15 and 2

households in Rendang and Busungbiu Districts, respectively, were in the top 20 GM/doe, while

Banjar, Grogak and Mendoyo Districts contributed one household each. Goats were well integrated

in the farming systems of the small and marginal farmers of Bali who found in goats a vast potential

for their socio-economic upliftment.

This study generated new, important and detailed information on goat production by smallholder

farmers in Bali Province. Suggested ways to improve goat production included:

High performance (as indicated by GM/doe) was associated with a higher turn off rate

(underpinned by a higher reproductive rate);

Organic goat rearing management in Rendang District was a model for Bali;

The ideal labourer to goat flock size ratio was 1:20 goats;

At least 25% of the flock should be does, with a 75% annual turn off rate;

The kidding interval should be 8 months;

Does should only be kept up to their fourth or fifth kidding;

Farmers need to keep records of their goats;

A ―One gate marketing system‖ should be used to maintain profitable market prices; and

Farmers needed networks with the Indonesia Research Institute for Animal Production to ensure

quality breeds, feeds and efficient rearing goat management systems were used in Bali.

This information is important as suggestions for improving goat production in these three and the

other regencies in Bali Province.

Declaration by author

iii

Declaration by author

This thesis is composed of my original work, and contains no material previously published or

written by another person except where due reference has been made in the text. I have clearly

stated the contribution by others to jointly authored works that I have included in my thesis.

I have clearly stated the contribution of others to my thesis as a whole, including statistical

assistance, survey design, data analysis, significant technical procedures, professional editorial

advice, and any other original research work used or reported in my thesis. The content of my

thesis is the result of work I have carried out since the commencement of my research higher degree

candidature and does not include a substantial part of work that has been submitted to qualify for

the award of any other degree or diploma in any university or other tertiary institution. I have

clearly stated which parts of my thesis, if any, have been submitted to qualify for another award.

I acknowledge that an electronic copy of my thesis must be lodged with the University Library and,

subject to the policy and procedures of The University of Queensland, the thesis be made available

for research and study in accordance with the Copyright Act 1968 unless a period of embargo has

been approved by the Dean of the Graduate School.

I acknowledge that copyright of all material contained in my thesis resides with the copyright

holder(s) of that material. Where appropriate I have obtained copyright permission from the

copyright holder to reproduce material in this thesis.

Publications during candidature

iv

Publications during candidature

Conference Abstracts/Papers

Doloksaribu, L., Murray, P. J., Copland, R. S. and McLachlan, B. P. Constraints to, challenges of,

and opportunities for rearing goats in Bali Province. A case study: rearing goats in Banjar

Belulang, Sepang Village. The Second Asia-Australasia Dairy Goat Conference 2014, IPB

International Convention Centre, April 25th–27

th 2014. (Paper and Presentation).

Doloksaribu, L., McLachlan, B. P, Copland, R. S. and Murray, P. J. Constraints to, challenges of,

and opportunities for rearing goats in Bali Province. A case study: Rearing goats in Karangasem

Regency. International Conference on Agriculture Biology and Environmental Sciences IBIS Hotel

Kuta Bali December 9th–10

th 2014. (Paper and Presentation).

Doloksaribu, L., McLachlan, B. P, Copland, R. S. and Murray, P. J. Constraints to, challenges of,

and opportunities for rearing goats in Bali Province. A Case study: Rearing kids in Karangasem

Regency. The 3rd International Seminar on Animal Industry IPB International Convention Centre

Bogor September 17th

-18th

2015. (Paper and Presentation).

Publications included in this thesis

No publications

Contributions by others to the thesis

No contributions by others.

Statement of parts of the thesis submitted to qualify for the award of another degree

None

Acknowledgments

v

Acknowledgements

I am most grateful to The Almighty Lord Jesus, for His blessings and for providing me with sound

health, and I am thankful for the good will of all the people who helped me to complete this study

and have made my life in Australia beautiful.

I would like to acknowledge my sincere gratitude to Associate Professor Peter Murray, Associate

Professor Richard Copland and Dr Brenda McLachlan for their supervision, scientific suggestions,

constructive criticism of the work and manuscripts, continuous encouragement and great patience

throughout the study.

Special gratitude is given to former Postgraduate Coordinator, Dr Doug George, who understands

me and his kindness allowed me to continue this study when ―the storm‖ came by. I extend my

gratitude to Mr Allan Lisle for his advice on statistical analysis, and Professor IM Bakta, Rector of

the University of Udayana, Bali, Indonesia who supported me to pursue this study.

I am grateful for the financial support provided by the Ministry of Research Technology and Higher

Education (DIKTI) Scholarship, Republic of Indonesia and the School of Agriculture and Food

Sciences, The University of Queensland, Australia who supported the research reported in this

thesis. Without this support, the work could not have been undertaken. I am grateful to DIKTI who

teaches me to use my knees kneeling before Him and saying my help only comes from Him.

I would like to express my sincere gratitude to Ibu NM Liestyawati and Ibu DM Dwiwati in the

Department of Husbandry and Agriculture in Bali Province. Thank you for facilitating access to

primary and secondary data on small ruminant development in Bali Province and for the

introduction to goat farmer associations and livestock extension staff in each village, you both

provided me great help and confidence. I extend my gratitude to Ajik IB Mantra, Dr IM Udiana,

Ibu AA Oka, Bapak IG Suranjaya and Ibu M Dewantari for having fun and supporting me during

my data collection. To Mr Patrick Viane and Dr Silvia Tonyes thank you, as you always stood up

for me. You both make me believe that this PhD study is beautiful as HE enables me to enjoy my

struggle wisely.

I am grateful to God for allowing me to meet all the Bali smallholder farmers who took part in this

study. I had never met you before, but all of you accepted me as part of your families. Special

thanks for Bapak K Muliana, Bli Sar and Bli Brenyonk in Rendang, Bli Wardana, Nadya in

Acknowledgments

vi

Busungbiu, Bli Cerik in Banjar, and Bli Tunas in Mendoyo. All of you offered me your hands,

integrity to work in this research, generosity and love. I see GOD is in you all.

For many unexpected reasons, I always made time to visit you, Mrs Beryl Mortimer, your genuine

prayers, beautiful sense of humour as well as your heavenly wisdom poured out upon me. You

encouraged me to keep saying that God is good all the time when nothing else could be done. Mrs

Juanita Rittmeyer, Mrs Dina Williams, Mrs Janet Mills, Mrs Margaret and Dr Richard Copland,

Mum Elke and Pastor Barry Benz, Mum Barbra and Pastor Ralph Bennett, I praise God for

allowing me to meet you all. Your genuine loving care as well as your supported prayers makes me

feel loved. All the Thursday Fellowship and members of Church of Christ Gatton, I am grateful to

God for creating days of Thursday and Sunday as the days for having real fun with you. Escaping

for a couple of hours just for singing praise to Him made me feel heaven in my busy study.

I am grateful for all TRANS Link bus drivers for having loving chats on the way to and from

campus and go back home. Mr Dannie, Mr Rod, Mrs Debbie, and Mr Adrian, and Mr Ian, your

friendly greetings as well as your kindness to drop me right in front of my home at night when they

were too windy, rain or cool was much appreciated. All the UQ security staff, especially Mr John

and Mrs Rebecca, you always checked me and greeted me, thank you for making me feeling secure.

Bill Gaither Ministry always cheered up my cool peaceful nights when I had to stay overnight

working in the Postgraduate Room. Your song lyrics made me stay strong and I was never alone

there.

Finally, my grateful acknowledgement is expressed to all The Doloksaribus: my brothers, brothers

in-law, sisters, sisters in-law, nephews, and nieces who love me so much and believe that doing this

study is a blessing to Bali smallholder farmers. We are bound not only by blood, but we also are

bound by the power of love and prayers. I am grateful for our Pa and Ma had passed on these

bindings as their heritages. I know you are both looking down and smiling on me.

Dedication

vii

Keywords

Bali, farmers, goats, baseline data, questionnaire, direct observation, improvement, rearing goats,

gross margin per doe.

Australian and New Zealand Standard Research Classifications (ANZSRC)

ANZSRC code: 070106, Farm Management, Rural Management, and Agribusiness, 60%

ANZSRC code: 070107, Farming System Research, 20%

ANZSRC code: 070108, Sustainable Agricultural Development, 20%

Fields of Research (FoR) Classification

FoR code: 0701, Agriculture, Land and Farm Management, 50%

FoR code: 0702, Animal Production, 50%

Dedication

This piece of work is dedicated to all Bali smallholder goat farmers and all livestock extension staff

who are always immersed in vision about the success of goat industry in Bali Province.

"No eye has seen, no ear has heard,

no mind has imagined what God has prepared for those who love Him

But it was to us that God revealed these things by His Spirit.

For His Spirit searches out everything and shows us God's deep secrets”

1 Corinthians 2: 9 - 10

-New Living Translation

http://biblehub.com/nlt/1_corinthians/2.htm

Table of Contents

viii

Table of Contents

Abstract ................................................................................................................................................ i

Declaration by author .......................................................................................................................... iii

Publications during candidature .......................................................................................................... iv

Publications included in this thesis ..................................................................................................... iv

Contributions by others to the thesis ................................................................................................... iv

Statement of parts of the thesis submitted to qualify for the award of another degree ....................... iv

Acknowledgements .............................................................................................................................. v

Keywords ........................................................................................................................................... vii

Australian and New Zealand Standard Research Classifications (ANZSRC) ................................... vii

Fields of Research (FoR) Classification ............................................................................................ vii

Dedication .......................................................................................................................................... vii

Table of Contents .............................................................................................................................. viii

List of Figures ................................................................................................................................... xiv

List of Tables .................................................................................................................................... xvi

List of Plates...................................................................................................................................... xix

List of Abbreviations and Acronyms used in the thesis..................................................................... xx

Outline of thesis ............................................................................................................................... xxii

Chapter 1 Introduction. ........................................................................................................................ 1

1.1 Background of the problem ........................................................................................................ 1

1.2 Problem statement ...................................................................................................................... 2

1.3 Aims of this study....................................................................................................................... 3

1.4 Research questions ..................................................................................................................... 3

1.5 Overview of thesis document ..................................................................................................... 4

1.6 Expected findings ....................................................................................................................... 5

Chapter 2 Review of Literature. ........................................................................................................... 6

2.1 Goat genotypes in Bali Province ................................................................................................ 6

2.1.1 Meat goats .......................................................................................................................... 10

2.1.1.1 Kacang or Katjang goats ............................................................................................. 10

2.1.1.2 Gembrong goats .......................................................................................................... 11

2.1.1.3 Boer goats ................................................................................................................... 12

2.1.1.4 Boerka (Boer X Kacang) crossbreds ........................................................................... 12

2.1.1.5 Boerawa (Boer X Peranakan Etawah) crossbreds ....................................................... 13

Table of Contents

ix

2.1.2 Dairy goats ......................................................................................................................... 14

2.1.2.1 Etawah or Jamnapari goats ......................................................................................... 15

2.1.2.2 Saanen goats ................................................................................................................ 16

2.1.3 Dual-purpose goats ............................................................................................................ 17

2.1.3.1 Peranakan Etawah (PE) crossbreds ............................................................................. 17

2.1.3.2 Benggala goats ............................................................................................................ 18

2.2 Factors influencing reproductive performance in female goats ............................................... 19

2.2.1 Age of puberty ................................................................................................................... 20

2.2.2 Age at first kidding ............................................................................................................ 22

2.2.3 Postpartum interval ............................................................................................................ 23

2.2.4 Kidding interval (Parturition interval) ............................................................................... 24

2.2.5 Fertility or the number of does serviced per conception (S/C) .......................................... 26

2.2.6 Litter size ........................................................................................................................... 27

2.2.7 Annual reproductive rate ................................................................................................... 30

2.3 Strengths, Weaknesses, Opportunities and Threats (SWOT) and Analytic Hierarchy Process

(AHP) analyses .................................................................................................................... 31

Chapter 3 General Research Design and Methods. ............................................................................ 34

3.1 Location and description of study sites .................................................................................... 34

3.2 Sampling techniques................................................................................................................. 34

3.3 Period of data collection ........................................................................................................... 35

3.4 Data collection and Questionnaire preparation ........................................................................ 36

a. Household labourers and their profiles ................................................................................... 37

b. Basic information about the goats and their profiles .............................................................. 37

c. Reproductive performance and productivity of the goats ....................................................... 38

d. Rearing management .............................................................................................................. 39

e. Socio-economic parameters .................................................................................................... 40

f. Inputs into, outputs from goat rearing and their relationships ................................................ 40

g. Assessing current goat rearing towards improving productivity in Bali Province, Indonesia.41

3.5 Statistical analysis .................................................................................................................... 41

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x

3.6 Animal and Human Ethics Approvals ...................................................................................... 42

Chapter 4 Goat production systems in Bali Province, Indonesia: An Overview ............................... 43

4.1 Introduction .............................................................................................................................. 43

4.2 Study sites................................................................................................................................. 43

4.3 The distribution of goats in Bali Province................................................................................ 46

4.4 Agricultural systems in Bali Province ...................................................................................... 49

4.5 The use of agriculture and industry by-products in promoting the goat industry in Bali

Province ............................................................................................................................... 51

4.6 Goat rearing systems in Bali Province ..................................................................................... 52

4.7 The roles of Indonesian Government toward the improving goat production in Bali Province53

4.8 Conclusion ................................................................................................................................ 55

Chapter 5 Current and future goat production in Karangasem Regency, Bali Province, Indonesia: A

case study in Rendang District. .......................................................................................................... 57

5.1 Introduction .............................................................................................................................. 57

5.2 Research design and Methods .................................................................................................. 57

5.3 Results ...................................................................................................................................... 58

5.3.1 Household labourers and their profiles .............................................................................. 58

5.3.2 Goats and their profiles ...................................................................................................... 60

5.3.3 Socio-economic analysis ................................................................................................... 66

5.3.4 Effects of managerial and environmental factors on production parameters .................... 71

5.3.4.1 Objectives of goat keeping .......................................................................................... 71

5.3.4.2 Feed and feeding management .................................................................................... 71

5.3.4.3 Health and disease control management ..................................................................... 72

5.3.4.4 Housing system ........................................................................................................... 72

5.4 Discussion ................................................................................................................................ 76



5.4.3 Socio-economic analysis ................................................................................................... 85

5.4.4 Effects of managerial and environmental factors on production parameters .................... 88

5.4.4.1 Objectives of goat keeping .......................................................................................... 88

Table of Contents

xi

5.4.4.2 Feed and feeding management .................................................................................... 89

5.4.4.3 Health and disease control management ..................................................................... 91

5.4.4.4 Housing system ........................................................................................................... 91

5.5 Constraints to improving goat production in Rendang District, Karangasem Regency .......... 92

5.6 Challenges of improving goat production in Rendang District, Karangasem Regency ........... 92

5.7 Opportunities for improving goat production in Rendang District, Karangasem Regency ..... 93

5.8 Conclusion ................................................................................................................................ 93

5.9 Suggestions ............................................................................................................................... 93

Chapter 6 Current and future goat production in Buleleng Regency, Bali Province, Indonesia: Case

studies in Banjar, Busungbiu and Grogak Districts. .......................................................................... 96

6.1 Introduction .............................................................................................................................. 96

6.2 Research design and Methods .................................................................................................. 96

6.3 Results ...................................................................................................................................... 97



6.3.3 Socio-economic analysis ................................................................................................. 102

6.3.4 Effects of managerial and environmental factors on production parameters .................. 107

6.3.4.1 Objectives of goat keeping ........................................................................................ 107

6.3.4.2 Feed and feeding management .................................................................................. 108

6.3.4.3 Health and disease control management ................................................................... 109

6.3.4.4 Housing system ......................................................................................................... 109

6.4 Discussion .............................................................................................................................. 114

6.4.1 Household labourers and their profiles ............................................................................ 114

6.4.2 Goats and their profiles .................................................................................................... 116






6.4.4.4 Housing system ......................................................................................................... 130

Table of Contents

xii

6.5 Constraints to improving goat production in Banjar, Busungbiu and Grogak Districts,

Buleleng Regency .............................................................................................................. 131

6.6 Challenges of improving goat production in Banjar, Busungbiu and Grogak Districts,


6.7 Opportunities for improving goat production in Banjar, Busungbiu and Grogak Districts,


6.8 Conclusion .............................................................................................................................. 132

6.9 Suggestions ............................................................................................................................. 133

Chapter 7 Current and future goat production in Jembrana Regency, Bali Province, Indonesia: A

case study in Mendoyo District. ....................................................................................................... 134

7.1 Introduction ............................................................................................................................ 134

7.2 Research design and Methods ................................................................................................ 135

7.3 Results .................................................................................................................................... 135








7.3.4.4 Housing system ......................................................................................................... 144

7.4 Discussion .............................................................................................................................. 145








7.4.4.4 Housing system ......................................................................................................... 153

7.5 Constraints to improving goat production in Mendoyo District in Jembrana Regency ......... 154

Table of Contents

xiii

7.6 Challenges of improving goat production in Mendoyo District in Jembrana Regency ......... 154

7.7 Opportunities for improving goat production in Mendoyo District in Jembrana Regency .... 154

7.8 Conclusion .............................................................................................................................. 154

7.9 Suggestions ............................................................................................................................. 155

Chapter 8 Assessing current goat rearing towards improving productivity in Bali Province,

Indonesia through a hybrid method of Strengths, Weaknesses, Opportunities and Threats (SWOT)

and Analytic Hierarchy Process (AHP) analyses. ............................................................................ 156

8.1 Introduction ............................................................................................................................ 156

8.2 SWOT and AHP analyses ...................................................................................................... 158

Size of land cultivated per household (ha) ............................................................................... 159

Number of household labourers (labourer) .............................................................................. 160

Education level of the smallholder goat farmers ...................................................................... 161

Gross margin per doe per household (IDR million) ................................................................. 161

8.3 Strategies for improvement of goat production in Bali Province ........................................... 164

The proportional number of does and bucks in a flock. ........................................................... 164

The proportion of labourers to flock size ................................................................................. 165

Education level/knowledge/skill/experience of goats rearing management of smallholder goat

farmers ........................................................................................................................ 166

8.4 Suggestions for improvement of goat production in Bali Province ....................................... 167

8.5 Concluding remarks ............................................................................................................... 168

8.5.1 An outcome of this study is a tape measure that has been validated for predicting the

bodyweights of goats in the districts studied. ............................................................. 168

8.5.2 Strengths and limitations of this study ............................................................................. 170

8.5.3 Recommendations for future research ............................................................................. 170

References ........................................................................................................................................ 172

Appendix 1 ....................................................................................................................................... 200

Appendix 2 ....................................................................................................................................... 215

List of Figures

xiv

List of Figures

Figure 1.1 The outline of the thesis................................................................................................. xxiii

Figure 3.1 Measurement of changes in goat flocks between the two snapshot observations six

months apart in Rendang District, Karangasem Regency, Bali Province. ......................................... 36

Figure 4.1 Monthly rainfall (mm) in Buleleng, Karangasem and Jembrana Regencies (Bali

Province) recorded in 2014. ............................................................................................................... 44

Figure 5.1 Flock sizes and average number of goats of different physiological states owned by

households in Rendang District, Karangasem Regency. ................................................................... 62

Figure 5.2 Numbers of kids‘ born, that died, survived, were sold or reared of the 568 kids born in

the first six months in 2014 in Rendang District, Karangasem Regency. ......................................... 62

Figure 5.3 Growth rates and 1,265 bodyweights of 568 kids from birth until post weaning age i.e.

290 days, when kids were weaned at day 135, in 2014 in Rendang District, Karangasem Regency.

............................................................................................................................................................ 63

Figure 5.4 Flowchart of timing of kids born, kidding intervals, days open and gestation periods of

goats reared in Rendang District, Karangasem Regency in 2014. ..................................................... 65

Figure 5.5 Percentage of kids born based on flock size and the time of kids born from January 2014

to September 2014 in Rendang District, Karangasem Regency. ....................................................... 65

Figure 5.6 Flock size, turn off rate, GM(A-B) (IDR million) and GM/doe (IDR million) based on

four flock sizes of goats reared in Rendang District, Karangasem Regency. .................................... 69

Figure 5.7 Number of goats, of different physiological states, sold per household and estimated

price (IDR million) of goats reared in Rendang District, Karangasem Regency. ............................. 70

Figure 6.1 Flock sizes and average number of goats in different physiological state owned by

households in Banjar, Busungbiu and Grogak Districts, Buleleng Regency. .................................. 101


the first six months in 2014 in Banjar, Busungbiu and Grogak Districts, Buleleng Regency. ........ 101

Figure 6.3 Flock size, annual turn off rate (%), GM(A-B) (IDR million) and GM/doe (IDR million)

based on four flock sizes of goats reared in Banjar, Busungbiu and Grogak Districts, Buleleng

Regency. ........................................................................................................................................... 105

List of Figures

xv

Figure 6.4 Average number of goats in each physiological state sold per household, and estimated

prices (IDR million) of goats reared in Banjar, Busungbiu and Grogak Districts, Buleleng Regency.

.......................................................................................................................................................... 106


households in Mendoyo District, Jembrana Regency. ..................................................................... 139

Figure 7.2 Numbers of kids‘ born, that died, survived, were sold or reared of the 67 kids born in the

first six months in 2014 in Mendoyo District in Jembrana Regency. .............................................. 140


prices (IDR million) of goats reared in Mendoyo District. .............................................................. 142


four different flock sizes. ................................................................................................................. 143

Figure 8.1 Proposed SWOT analysis and Analytic Hierarchy Process research framework. ......... 157

Figure 8.2 Hierarchic structure of the SWOT analysis for AHP ..................................................... 158

List of Tables

xvi

List of Tables

Table 2.1 Mean bodyweights of Benggala, Jawarandu, Kacang, Marica, Muara and Samosir goats.

............................................................................................................................................................ 10

Table 2.2 Average birth weights, weaning weights and average daily weight gains for preweaned

Kacang, Boerka F1 and Boerka Back Cross F1 kids. ......................................................................... 13

Table 2.3 Average weaning weight (kg), kidding interval (months), litter size, estimated

repeatability of weaning weight, average Dam Productivity Index (DPI) and Most Probable

Producing Ability (MPPA) of Boerawa F1, Back Cross F1 and Back Cross F2 Boerawa crossbreds.

............................................................................................................................................................ 13

Table 2.4 Milk production, fat and protein percentages of PE crossbreds reared in Bali. ................. 18

Table 2.5 A summary of published data on ages (days) and bodyweights (kg) of first puberty in

female goats. ...................................................................................................................................... 21

Table 2.6 A summary of published data on age of first kidding (days) in female goats. .................. 22

Table 2.7 A summary of published data on postpartum interval (days) in female goats. .................. 24

Table 2.8 Litter size at weaning, kidding interval and doe productivity of Kejobong goats in

Kejobong District, Indonesia. ............................................................................................................ 25

Table 2.9 A summary of published data on kidding interval (days) in female goats. ....................... 26

Table 2.10 A summary of published data on number of services per conception in female goats. ... 26

Table 2.11 A summary of published data on litter size (goats) of different genotypes of goats with

information about the type of birth, sex of kid, and parity of does. ................................................... 28

Table 2.12 A summary of published data on birth weights (kg) of different genotypes of goats with

information about the type of birth, sex of kid, and body condition score of does. .......................... 29

Table 2.13 A summary of published data on doe productivity (kg meat/doe/year). .......................... 31

Table 3.1 Timing of and data collected during the direct animal observations in Bali Province. ..... 35

Table 4.1 Regency/city, area, geographic location, average annual temperature, relative humidity,

rainfall and wind velocity of Bali Province in 2014 (www.bmkg.go.id). .......................................... 44

Table 4.2 Regency/city, number of districts, villages, human population, number of goats, area and

density of the human population and goats in Bali 2014. .................................................................. 46

Table 4.3 Population of livestock by regency/city and type of livestock in Bali in 2014 and

designation areas. ............................................................................................................................... 47

Table 4.4 Population of goats, goats slaughtered and goat meat produced (tonne) by regency/city,

and genotype and sex of goats in Bali in 2014. ................................................................................. 47

List of Tables

xvii

Table 4.5 Farm commodities, total area (ha), and their production yield (tonne) by regencies in Bali,

in 2014................................................................................................................................................ 50

Table 4.6 Production (tonne) of commodities by regency/city in Bali in 2014. ................................ 50

Table 5.1 Average bodyweights of different classes of goats recorded once to four times during four

observations in Rendang District, Karangasem Regency. ................................................................. 61

Table 5.2 Kidding interval (days), BW preweaned (kg), ADG preweaned (g/d), BW post weaned

(kg) and ADG post weaned (g/d) of 1,169 goats reared by 63 households in Rendang District,

Karangasem Regency. ........................................................................................................................ 66

Table 5.3 Comparison between the top 20 and bottom 20 for annual Total income (IDR million),

Total variable costs (IDR million), GM(A-B) (IDR million) and GM/doe (IDR million) of 63 goat

farms under smallholder production systems in Rendang District, Karangasem Regency. .............. 67

Table 5.4 Simulation on how flock size and the number of does owned affects the GM(A-B) (IDR

million) and GM/doe (IDR million) of goats reared in Rendang District, Karangasem Regency. ... 69

Table 5.5 Average number of goats of different classes sold per households in Rendang District,


Table 5.6 Effects of housing (battery and colony) systems on kidding intervals of different kidding

birth types of does reared in Rendang District, Karangasem Regency. ............................................. 74

Table 5.7 Effects of housing (battery and colony) systems on kidding intervals of different parities

of does reared in Rendang District, Karangasem Regency in 2014. .................................................. 74

Table 5.8 Effects of housing (battery and colony) systems and flock size on annual turn off rate (%),

GM(A-B) and GM/doe of goats reared in Rendang District, Karangasem Regency. ....................... 75

Table 5.9 Effects of housing (battery and colony) systems and flock size on labourer ratio, number

of does owned per household (does) and number of goats sold per household in Rendang District,


Table 5.10 Effects of housing (battery and colony) systems and flock size on 3,133 bodyweight

recordings of 1,169 goats reared in Rendang District, Karangasem Regency. .................................. 76

Table 6.1 Flock sizes and average number of goats of different classes, owned per household in

Banjar, Busungbiu and Grogak Districts, Buleleng Regency. ......................................................... 100



farms under smallholder production systems in Banjar, Busungbiu and Grogak Districts, Buleleng

Regency. ........................................................................................................................................... 104

Table 6.3 Effects of housing (battery and colony) systems on annual production parameters of goats

reared in Banjar, Busungbiu and Grogak Districts, Buleleng Regency. .......................................... 110

List of Tables

xviii

Table 6.4 Effects of housing (battery and colony) systems on average numbers of goats in different

classes owned per household in Banjar, Busungbiu and Grogak Districts, Buleleng Regency. ..... 111

Table 6.5 Effects of housing (battery and colony) systems and flock sizes on labour ratio, number of

does owned per household (does), number of goats sold per household (goats), prices of goats sold

per household (IDR million) and prices of milk sold per household (IDR million) in Banjar,

Busungbiu and Grogak Districts, Buleleng Regency. ...................................................................... 112


GM(A-B) (IDR million) and GM/doe (IDR million) of goats reared in Banjar, Busungbiu and

Grogak Districts, Buleleng Regency. ............................................................................................... 113

Table 6.7 Effects of housing (battery and colony) systems and flock size on average bodyweights

and FAMACHA©

scores of 590 goats reared in Banjar, Busungbiu and Grogak Districts, Buleleng

Regency. ........................................................................................................................................... 114

Table 7.1 Average number of goats of different classes, owned by households in Mendoyo District,

Jembrana Regency. .......................................................................................................................... 139


Total variable costs (IDR million), GM(A-B) (IDR million) and GM/doe (IDR million) of goats

reared by smallholder goat farmers in Mendoyo District, Jembrana Regency. ............................... 141

Table 7.3 Average number of different classes of goats sold per household in Mendoyo District,

Jembrana Regency. .......................................................................................................................... 142

Table 8.1 Rank in order of importance of pairwise Pearson correlations, between the size of land

cultivated (ha) and other parameters of goat production, in Banjar, Busungbiu, Grogak, Mendoyo

and Rendang Districts, Bali Province. ............................................................................................. 159

Table 8.2 Rank in order of importance of pairwise Pearson correlations, between the number of

household labourers and other parameters of goat production, in Banjar, Busungbiu, Grogak,

Mendoyo and Rendang Districts, Bali Province. ............................................................................. 160

Table 8.3 Rank in order of importance of pairwise Pearson correlations, between the education level

of farmers to other parameters of goat production, in Banjar, Busungbiu, Grogak, Mendoyo and

Rendang Districts, Bali Province. .................................................................................................... 161

Table 8.4 Rank in order of importance of pairwise Pearson correlations, between the GM/doe and

other parameters of goat production, in Banjar, Busungbiu, Grogak, Mendoyo and Rendang

Districts, Bali Province. ................................................................................................................... 162

Table 8.5 SWOT factors considered for improving goat production in Bali Province, Indonesia .. 163

List of Plates

xix

List of Plates

Plate 2.1 Goat breeds commonly found across islands in Indonesia and potentially are also found in

Bali Province ........................................................................................................................................ 9

Plate 3.1 Map of Bali showing Karangasem, Buleleng and Jembrana Regencies that were selected

areas. .................................................................................................................................................. 34

Plate 8.1 Two hundred tape measures were produced for predicting bodyweights of goats reared in

Bali Province, based on the 2,017 goats measured during the data collection in 2014. .................. 170

List of Abbreviations and Acronyms used in the thesis

xx


a.s.l. Above sea level

ADG (g) Average daily gain

AHP Analytic Hierarchy Process

AIBP Agricultural and industry by-products

Battery housing system Elevated individual pens with slatted floors or on the ground

BL (cm) Body length

BPS - Bali Badan Pusat Statistik Provinsi - Bali or Statistics Bali Province. Bali

in figures

BPS - Indonesia Badan Pusat Statistik Republik - Indonesia or Statistics Indonesia. A

government body responsible for providing statistics of Indonesia

BPTP-Bali Balai Pengkajian Teknologi Pertanian-Bali or

Indonesian Agency for Agricultural Research and Development

Boerka crossbreds The crossbred between Boer X Kacang goats

Boerka BC F1 (75 Boer : 25 Kacang) crossbreds

Boerka F1 (50 Boer : 50 Kacang) crossbreds

Boerawa crossbreds The crossbred between Boer X Etawah Grade crossbreds

Boerawa BC F1 (75 Boer : 25 Etawah Grade) crossbreds

Boerawa F1 (50 Boer : 50 Etawah Grade) crossbreds

BW (kg) Bodyweight

CC (cm) Circumference of chest

CD (cm) Chest depth

Colony housing system Elevated group pens with slatted floors or on the ground

DGLS Directorate General of Livestock Service

Does Female mature goats including pregnant, lactating and dry female

goats

DPI Dam Productivity Index

Eid Qurban Also known as Sacrifice Feast that was celebrated by Muslim on the 5th

October 2014, the date of which alters by 354 to 355 days each year

F1 Filial1 or the 1st generation of offspring

FAMACHA©

score The FAMACHA©

system is used to estimate the level of anaemia in

sheep and goats associated Haemonchus contortus infection and is

used to make deworming decisions

GLM General Linear Model

GM Gross Margin


xxi

GM/doe Gross Margin/doe

GRDP Regency Gross Regional Domestic Product

HDI Human Development Index

HW (cm) Height at withers

I0 Incisors at first year (kid)

I1 Incisors at second year (goatling/yearling)

I2 Incisors at third year (two year old)

I3 Incisors at fourth year (three year old)

I4 Incisors at fifth year (four year old)

IDR Indonesian Dollar Rupiah.

IDR 1 million was equivalent to AUD$100.00

IRIAP Indonesia Research Institute for Animal Production - Balitnak-Ciawi

Labourer Labourer was a household member regardless of their sex who was 15

years old or older and was involved in goat farming based on the Act

of the Republic of Indonesia number 13 year 2003 concerning

manpower

Mecaru goats Mecaru goats that were one year old and had black coat colour were

used as sacred offerings in Mecaru rituals in Balinese Hindus for

temple celebrations or for individual ceremonies

MPPA Most Probable Producing Ability

NSW New South Wales

P Probability

PE The crossbreds between Etawah X Kacang goats

PE-AN The crossbreds between PE X Anglo-Nubian goats

PE-SA The crossbreds between PE X Saanen goats

Primatani Assessment Institute for Agriculture Technology is one of the Bali

Government support programmes to support smallholder goat farmers

RH (cm) Rump height

RIGP Research Institute for Goat Production (Sungei Putih)

S/C Service per conception

Simantri Sistem Pertanian Terintegrasi or A programme of Integrated Farming

System (IFS) with zero waste and produces 4 F (Food, Feed, Fertilizer

and Fuel) that was launched by the Bali Provincial Government in

2009

SWOT analysis Strengths, Weaknesses, Opportunities and Threats analysis

Outline of thesis

xxii

Outline of thesis

This thesis has eight chapters with an overall aim of establishing a database of reproductive and

productive performances of goats reared in Bali Province as well as their socio-economic analysis,

and identifying constraints to, challenges of and opportunities for improving rearing more goats in

Bali Province. The first two chapters present a critical review of existing literature on improvement

of the goat industry in Bali Province through identifying the constraints to, challenges of, and

opportunities for improving rearing goats in Bali Province. These chapters provide the existing

goat genotypes found in Bali Province as well as factors influencing reproductive performance of

goats, and Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis and Analytic

Hierarchy Process (AHP). Chapter 3 describes the research design and methods used in this

research. The research proposed in Chapter 3 was conducted through case studies, structured

formal household interviews, meetings, key informant interviews, focus group discussions and

direct animal observations across targeted districts in Bali Province.

The preliminary research was conducted in Sepang Kaja Village in Buleleng Regency. Chapter 4

presents an overview of goat production systems in Bali Province. Chapters 5, 6 and 7 present a

series of interrelated studies examining the roles of smallholder farmers in improving goat

productivity under their production systems in Bali Province where financial analysis of goat

production was also assessed. Chapter 5 presents factors influencing the efficiency of goat

production by smallholder farmers in Rendang District in Karangasem Regency, Bali Province.

Using Chapter 5 as a template, Chapters 6 and 7 present research results obtained in Busungbiu,

Banjar and Grogak Districts, Buleleng Regency and in Mendoyo District, Jembrana Regency Bali

Province, Indonesia, respectively. Analysis of the household labourers and their profiles, the goats

and their profiles, and the environment resources, managerial and market assessments as well as the

socio-economic analysis through case studies, formal household interviews, meetings, key

informant interviews and focus group discussions are presented in Chapters 6, 7 and 8. Finally,

Chapter 8 describes assessing current goat rearing towards improving productivity in Bali Province

through a hybrid method of SWOT and AHP analyses. This chapter presents general conclusions

and suggestions for future research. The outline of the thesis is illustrated in Figure 1.1.

Outline of thesis

xxiii

Figure 1.1 The outline of the thesis.

* preliminary questionnaire

was modified before conducting

data collection

Chapter 4

Goat production systems in Bali

Province, Indonesia: An Overview.

Chapter 1

Introduction.

1.1 Background of the problem

1.2 Problem statement

1.3 Aims of this study

1.4 Research questions

1.5 Overview of thesis document

1.6 Expected findings

Preliminary research in Sepang Kaja

Village in Buleleng Regency

Chapter 2

Review of Literature.

Goat research: Factors influencing

the efficiency of goat production by

smallholder farmers in Bali

Province were conducted in

Karangasem, Buleleng and

Jembrana Regencies, Indonesia.

Chapter 3

General Research Design and Methods. Chapter 5

Current and future goat production

in Karangasem Regency, Bali

Province, Indonesia: A case study

in Rendang District.

Chapter 6


in Buleleng Regency, Bali

Province, Indonesia: Case studies in

Banjar, Busungbiu and Grogak

Districts.

CHAPTER 8

Assessing current goat rearing towards improving productivity in Bali Province through a hybrid

method of Strengths, Weaknesses, Opportunities and Threats (SWOT) and Analytic Hierarchy

Process (AHP) analyses.

Chapter 7


in Jembrana Regency, Bali

Province, Indonesia: A case study

in Mendoyo District.

Chapter 1 Introduction

1

Lindawati Doloksaribu The University of Queensland 2017

Chapter 1

Introduction.

1.1 Background of the problem

Goat rearing played a very important role in the socio-economic and social life of many Indonesian

smallholder goat farmers according to Knipscheer et al. (1983). Smallholder farmers found that

goats were easy to care for (Soedjana 2007), prolific (Devendra 1985b), required low inputs for a

moderate level of production, and reached maturity early (Devendra & Burns 1983). Goats were

profitable to keep (Devendra & Burns 1983) and had a ready market (Soedjana 2005). Goats were

farmed as the main source of income or to provide a secondary income source in addition to

producing fertilizer for vegetable or crop growers (Cempaka et al. 2016). Their initial and

maintenance costs were low as they utilised marginal land, had low labour costs, utilised crop

residues and agricultural by-products, and required simple housing structures (Knipscheer et al.

1984; Soedjana 2005). Other roles of goats for Indonesian smallholder farmers included their

inclusion in social/religious ceremonies, particularly Eid Qurban (Budisatria 2006; Budisatria et al.

2008). Goats, especially those that were one year old and had black coat colour were used as

Balinese Hindu sacred offerings in Mecaru rituals for temple celebrations or for individual

ceremonies (Mantra, I. B. 2014, pers. comm. 21 February).

About 400,000 farmers in rural areas in Indonesia left their profession annually during the period

2003 to 2013 (BPS-Indonesia 2013a). In contrast, in the same period, the total Indonesian

population increased by about 3.4 million people and about 50 thousand people in Bali Province

(BPS-Indonesia 2014). About 99,900 people in urban areas and 85,300 people in rural areas in Bali

Province lived in extreme poverty with incomes below IDR 310,321 per capita per month in urban

areas or below IDR 271,646 per capita per month in rural areas of Bali Province in March 2013

(BPS-Bali 2013; BPS-Indonesia 2013b). Many villagers, particularly children and women could

not afford the average dietary protein consumption of 56 g/person/day as recommended by the

Indonesian Government in 2013 (FAOSTAT 2015; Anonymous 2016a). One of the ways to solve

this poverty was to introduce goats to smallholder farmers who did not have livestock and to

improve goat productivity of smallholder goat farmers in Bali Province. Improvement of goat

production in Bali Province, therefore, was expected to be one of the answers to Indonesia‘s

problems, particularly in providing protein sources, as well as in improving the income of goat

farmers. However, the goat population decreased between 2009 and 2014 (BPS Bali 2015). The

reasons for this decline were not clear; whether it was due to high demand of goats that were

slaughtered, or the low productivity of goat rearing in Bali Province.


2


BPS-Bali 2015 as the annual official report provided by the Indonesian Government regarding the

goat population in Bali Province was incomplete as crucial information was missing. For instance,

available literature generated showing little information about the goat rearing systems used in each

regency as well as unclear policies on which regencies were suitable for improving the goat

industry based on their human and environmental resources. In addition, published reviews also

had little information about the goat genotypes present, their reproductive and productive

performance, and the types of goat rearing systems utilised in Bali. As a result, the assessment of

the richness of the natural and human resources to support the goat industry in Bali Province could

not be identified hence current goat production in Bali Province was unclear. Therefore, this study

will provide the key information on the issues mentioned above.

This project presented a study on goat production in Bali Province Indonesia, but the findings might

have wider implications in rural Indonesia, and indeed other tropical developing countries. The

efficiency of reproduction and production of goats in Bali was measured via production parameters

including turn off rate and gross margin analysis (GM/doe). The definitions for the turn off rate and

gross margin analyses i.e. GM(A-B) and GM/doe were presented in Chapter 3. This efficiency of

production was compared to the efficiency of goat production in comparable environments. The

effects of environmental and genetic factors as well as management on the production parameters

were then examined statistically. This enabled the identification of possible restraints to efficient

goat production. The efficiency of goat production is defined as the total production produced per

goat, or the total production produced by goats per hectare including meat, manure, milk and sale of

animals (Devendra & Burns 1983). Further clues to the constraints to efficient goat production

were obtained by comparing the management of top performing flocks (as measured by GM/doe)

with the lowest performing flocks. The identification of constraints to efficient goat production

enabled the development of suggested practices to improve the efficiency of goat rearing in Bali

(Mantra 1991).

1.2 Problem statement

The lack of baseline quantitative data on the reproductive and productive performance of goats

reared in Bali Province, limited the ability to identify the factors that may involve in low

reproductive and productive performance of goats in Bali Province. Thus, this study intends to

identify and measure the constraints to, challenges of, and opportunities for rearing more goats in

Bali Province.


3


The environment where goats were raised, might affect their productivity. Bali covers 5,636.66

km2 and its geographic location is 8º3'40" - 8º50'48" south and 114º25'53" - 115º42'40" east. This

mountainous island was covered by 24 mountains ranging in height from 310 to 3,142 m above sea

level (a.s.l.). This island had average temperatures between 19 to 27.5 0C, relative humidity of 68

to 93%, annual average rainfall of 1,182 to 4,857 mm and average wind velocity of 3 to 9 knots

(Bali Meteorology Bureau 2015). In addition, Bali had an abundant supply of different crops and

agricultural industry by-products (AIBP) (BPS-Bali 2015). Research in other countries (Devendra

& Thomas 2002; Devendra 2010) indicated that Bali Province provided a suitable environment for

rearing goats and there were opportunities to explore, as well as to improve, the AIBP as feed for

goats.

However, there was a dearth of information on current reproductive and productive performances,

as well as the agricultural systems, goat rearing systems, and the quality of feeds fed or available to

be given to goats in Bali. This included information on the reproductive and productive profiles of

current goat farming in Bali as well as factors affecting efficiencies of goat farming in Bali. Further

information was also needed on constraints and challenges in improving the efficiency in goat

farming in this region and the strategies to improve the efficiency.

1.3 Aims of this study

Overall Aim: The overall aim of this study was to establish a database of reproductive and

productive performances of goats reared in the province of Bali as well as their socio-economic

analysis, and to identify constraints to, challenges of and opportunities for improving goat

production in Bali Province.

Objectives: The study had four main objectives:

1. Identify factors affecting efficiencies of goat farming in Bali Province.

2. Identify constraints and challenges in improving the current efficiency in goat farming in Bali

Province.

3. Develop relevant strategies from the above information for improving the efficiency of goats

reared in Bali Province.

4. Establish a database of current reproductive and productive performances of goats reared in

Bali Province from a base-line survey.

1.4 Research questions

The following research questions were proposed from the four main objectives:


4


Objective 1 (Identify factors affecting efficiencies of goat farming)

Questions:

What are factors affecting efficiencies of goat farming in Bali Province?

Objective 2 (Identify constraints and challenges in improving the efficiency in goat farming)

Questions:

What are the constraints and challenges in improving the efficiency in goat farming in this region?

Objective 3 (Develop strategies to improve the efficiency)

Questions:

What are the strategies to improve the efficiency?

Objective 4 (Establish a database of reproductive and productive performances of goats)

Questions:

What are the reproductive and productive profiles of current goat farming in Bali?

1.5 Overview of thesis document

This thesis is divided into chapters based around the main objectives:

Chapter 2 presents a review of the literature on topics relevant to this study i.e. goat genotypes

found in Bali Province; factors influencing reproductive performance in female goats and SWOT

and AHP analyses.

Chapter 3 presents the Research Design and Methods applied in the study. This is dealt with

location, sampling techniques, survey and observation for collecting data, and methods of

analysis.

Chapter 4 presents Goat production systems in Bali Province, Indonesia: An Overview.

Chapter 5 describes Current and future goat production in Karangasem Regency, Bali Province,

Indonesia: A case study in Rendang District.

Chapter 6 describes Current and future goat production in Buleleng Regency, Bali Province,

Indonesia: Case studies in Banjar, Busungbiu and Grogak Districts.

Chapter 7 describes Current and future goat production in Jembrana Regency, Bali Province,

Indonesia: A case study in Mendoyo District.

Chapter 8 describes Assessing the current goat rearing towards improving productivity in Bali

Province through a hybrid method of SWOT and AHP analyses. This chapter presents a

summary of the research findings against the aims of the research, implications, significance of


5


the findings and identifies directions for future research as well as Indonesian Government

policy intervention to improve goat rearing in Bali Province.

1.6 Expected findings

This research on the factors influencing the efficiency of goat production by smallholder farmers in

Bali Province generates important information by establishing a database of current goat rearing by

smallholder farmers in Bali Province. This efficiency of goat production was measured by

estimating the following production parameters: turn off rate, kidding rate, weaning rate, inter

kidding interval, growth rates of different classes of goats, and gross margin analysis (Knipscheer et

al. 1984; Peacock 1987; James & Carles 1996; Bosman et al. 1997a; Bosman et al. 1997b)

(Anonymous 2004a). The overall aim was to identify the factors (constraints) that reduce the

overall efficiency of goat production under smallholder production systems in Bali Province. This

may lead to strategies to ameliorate the effect of these constraints and thus increase the efficiency of

goat production. The management and environmental practices of goat farmers with the top 20%

performing flocks were then compared to the goat farmers with the poorest 20% performing flocks.

Performance was measured using GM/doe per year. This comparison helped to identify constraints

to efficiency of goat production in Karangasem, Buleleng and Jembrana Regencies (Baptist 1988;

Upton 1989, 1993). Finally, this study provided suggestions for further research and government

policy intervention to improve efficiency of goat rearing in Bali Province.

Chapter 2 Review of Literature

6


Chapter 2

Review of Literature.

The objective of this chapter was to review the context and farming systems under, which goats are

raised in Bali Province, Indonesia. The goat genotypes found in Bali Province will be discussed;

and the factors influencing the reproductive performance of female goats; and a hybrid method of

SWOT and AHP analyses of goat rearing towards improving productivity in Bali Province will be

reviewed. Different tools to measure efficiency of goat production in Bali were used in this study.

These tools will be reviewed. Also reviewed are the strategies used by other researchers to improve

smallholder farmer‘s goat production in Bali Province, Indonesia.

2.1 Goat genotypes in Bali Province

Goat (Capra aegagrus hircus) breeds were defined by breed standards as differences in colour, ear

size and type, horn size and type, face type, hair coat length, presence of beard, and or wattles,

bodyweight, and height in adult males and females (Devendra & Haenlein 2011). Identifying goat

genotypes reared by smallholder farmers in Bali Province helped in improving their productivity.

This was related in identifying the diversity of medium to high yield of single-purpose dairy types

or dual-purpose types or body sizes of goats, and their response mechanisms adapting to

environmental challenges i.e. climate, feed availability, rearing management and sustainable

agriculture (Devendra & Burns 1983; Devendra & Haenlein 2011; Daramola et al. 2012).

Devendra and Burns (1983) have classified tropical goats based on body size as Large (>65 cm),

Small (51-65 cm) and Dwarf (<50 cm) at the withers. Size was commonly represented by

bodyweight, though other linear measurements could be used. Classifying goats based on their

height at withers could be considered as a better predictor for bodyweight than of heart girth (Aziz

& Sharaby 1993), while other findings found that using heart girth based was a better predictor for

bodyweight, too (Villaquiran et al. 2005; Natsir et al. 2010; Chitra et al. 2012; McGregor 2017) as

well as using several body measurements (Kor et al. 2006; Pesmen & Yardimci 2008). This was in

agreement with Devendra (1985b) who stated that classifying goats based on body size was a useful

criterion indicating clues to their potential performance. This was also in line with the productivity

of goats that is normally related to their size and age and larger size usually produced more milk

and meat than smaller ones (Abebe et al. 2010; Devendra & Haenlein 2011).

Indonesia had native goat breeds that were commonly reared by smallholder farmers in many types

of integrated farming systems across Indonesia (Merkens & Soemirat 1926; Merkens 1930, 1931;


7


Merkens & Sjariff 1932). Seven indigenous goat breeds in Indonesia, which have been classified

based on their conformation traits and geographical distributions i.e. Benggala, Marica, Jawarandu,

Kacang or Katjang, Muara, Samosir (Pamungkas et al. 2009; Batubara et al. 2011; Zein et al. 2012)

and Gembrong goats (Pamungkas et al. 2009; Sulabda et al. 2012). This finding was confirmed by

Sulabda et al. (2012) who reported that the variety of habitats across Indonesia caused the

phenotypic differences among different native goat breeds. Phylogenetic relationship was

consistent with the history of its development based on Kacang goat (Zein et al. 2012). Kacang,

Kejobong, Kosta and Jawarandu goats, are known for their strong fitness and foraging capability

under a wide range of habitats in Java Island (Merkens & Soemirat 1926; Merkens 1930, 1931;

Merkens & Sjariff 1932). Kejobong goats were originally kept in Purbalingga District, Central Java

(Astuti et al. 2007; Budisatria et al. 2010; Socheh et al. 2012), Marica goats were reared in Maros

and Jeneponto Regencies in South Sulawesi Province (Batubara et al. 2011), and Kosta goats were

commonly found in Serang and Pandeglang Regencies of the Banten Province (Sodiq & Tawfik

2003; Pamungkas 2008). Samosir and Muara goats were commonly reared in North Sumatera

Province, particularly in Northern Tapanuli (Doloksaribu et al. 2006; Batubara et al. 2011).

The Indonesian Animal Production Research Institute began to characterize Indonesian goat breeds

in the 1980‘s (Setiadi et al. 1985; Setiadi 1988; Subandriyo et al. 1995; Setiadi et al. 1998). It was

estimated that there were local Indonesia goat breeds that were still not characterized and some

which were rare or nearing extinction (Sulabda et al. 2012). Therefore, exploring the characteristics

and identifying the genetic diversity of local goat resources will help in planning for conservation

strategies as well as genetic improvement of goats (Batubara et al. 2011; Sulabda et al. 2012; Zein

et al. 2012).

To improve the genetics of Indonesian native goat breeds particularly for high milk production,

Etawah goats were imported from Jamnapari in the Uttar Pradesh and Madhya Pradesh states in

India, between 1911 and 1931 (Merkens & Soemirat 1926; Merkens 1930, 1931; Merkens & Sjariff

1932). The imported large, long-legged Etawah or Jamnapari goats had an average bodyweight of

50 kg for males and 40 kg for females that had average 210 kg milk production in 260 days

(Devendra & Haenlein 2011), and were crossed with the small local goats especially Kacang goats

(Plank 1949). As a result, Peranakan Etawah aka PE or Etawah Grade or Etawah crossbred existed

from the crossing between the imported Etawah bucks and Kacang does. The PE crossbred was

known as a dual-purpose goat used to produce milk and meat (Merkens & Soemirat 1926; Merkens

1930, 1931; Merkens & Sjariff 1932). Of all goat breeds in Indonesia, PE crossbreds were the most


8


preferred goat genotype and were spread widely in Indonesia including Bali Province (BPS-Bali

2015) (Table 4.4).

For further improvement of Indonesian native goat breeds, Saanen, Angora and Cashmere goats

were also imported and introduced into the government experimental stations in Bogor and

Bandung in West Java Province, Padang Mangatas in West Sumatera Province and Sumba in East

Nusa Tenggara Province of Indonesia between 1911 and 1931 (Merkens & Soemirat 1926; Merkens

1930, 1931; Merkens & Sjariff 1932). Earlier published reviews of goat breeds in Indonesia

undertaken by Sodiq and Tawfik (2003) or Tjokrohoesodo and Grossman (1975) or Merkens (1931)

did not report about the former imported breeds such as Angora, Cashmere and Saanen. The

questions of interest are: when were they actually imported?; how many of them were imported?;

where were they distributed?; how did they adjust to Indonesian environments?; and what was the

productive and reproductive performances of these breeds and their crossbreds? Saanen goats,

however, were continued to be imported and were crossed with PE crossbreds resulted in a new PE-

SA crossbred that improved the quality of milk production (Taufik et al. 2011; Zurriyati et al. 2011;

Praharani et al. 2015). Saanen goats were now monitored in IRIAP Balitnak-Ciawi for the

productivity of their offspring when they were crossed with PE crossbreds (Praharani et al. 2013;

Praharani et al. 2015) and their productivity under smallholder production systems in West Java

Province (Taufik et al. 2011; Zurriyati et al. 2011).

In addition to the improvement of Indonesian native goat breeds, Boer goats were imported recently

to RIGP Sungei Putih (Mahmilia & Doloksaribu 2010; Mahmilia et al. 2010), and Anglo-Nubian

goats to RIGP Sungei Putih and IRIAP Balitnak-Ciawi (Praharani, L. 2013, pers. comm. 30

November). Subsequently, new crossbreds such as Boerka (Mahmilia & Elieser 2008; Mahmilia &

Doloksaribu 2010) and Boerawa (Sulastri 2010), and PE-AN (Praharani 2014; Praharani et al.

2015) have been produced from crossing Boer X Kacang, Boer X PE and PE X Anglo-Nubian,

respectively. The Indonesian Research Institute for Animal Production (Balitnak-Ciawi) has

conducted various research projects in creating a composite of meat and dairy goat breeds that will

adapt to Indonesia‘s humid tropical environment. A nine billion IDR funded research project was

launched to develop a new dairy goat breed for Indonesia (Praharani, L. 2013, pers. comm. 30

September) with Anglo-Nubian goats imported from Europe to upgrade Kacang goats as well as he

local goats, particularly PE crossbreds (Praharani 2014; Praharani et al. 2015).

Although Indonesian Government has been monitoring the improvement of goat productivity by

upgrading with the imported goat breeds, the Ministry of Agriculture and Livestock Bali Province


9


(2015) reported only Gembrong, Kacang and PE goat breeds officially in Bali Province (Plate 2.1).

Therefore, this study will determine what genotypes of goats are found in Bali Province, how

smallholder farmers rear their goats, the availability of human and environmental resources as well

as measurement of productivity of their goats. Goat breeds available in Bali Province may be

classified as meat, milk or dual-purpose goats.

Kacang that was not found in

Bali

Etawah PEa

Benggalab Gembrong

c PE goats with floppy short

earsd

Boer

e Boerawa

f = Boer X PE Mecaru goat farm

g

Photos of PEa; Benggalab; Gembrongc; Mecarud; Boere, Boerawaf and Peg that were reared by smallholder farmers in Bali Province

were taken by Doloksaribu, L., during the data collection in 2014 The remaining photos of goats reared in Java Island that were

downloaded from www.google.com 16 August 2016

Plate 2.1 Goat breeds commonly found across islands in Indonesia and potentially are also found in

Bali Province

http://www.google.com/


10


2.1.1 Meat goats

The number of young weaned and the total weaning weight per doe per year were the production

traits of importance of meat goats (Sodiq & Haryanto 2007). Available literature and information

generated showing that smallholder farmers commonly reared the Indonesian native goats for their

meat production. Kacang and Gembrong were recommended as meat goats (Tillman 1981). Meat

goats that are commonly reared in Indonesia, including Bali, are described in the following sections.

2.1.1.1 Kacang or Katjang goats

The Kacang or Katjang goat had long been recognised as an Indonesian native meat goat (Merkens

& Soemirat 1926; Devendra & Nozawa 1976) and a prolific breeder (Devendra 1985b). Devendra

and Burns (1983) characterized this goat by small body size, flat nose, and small erect ears, short

horns in females and males, short hair and widely varied colours. It also had a relatively thin coat

with coarse hair, and the male had a pronounced, long, coarse mane. Mean bodyweight of Kacang

goats was comparable to some native goats measured by Batubara et al. (2011) (Table 2.1).

Table 2.1 Mean bodyweights of Benggala, Jawarandu, Kacang, Marica, Muara and Samosir goats.

Goat breed

Doe Buck Overall

n Mean ± s.d. (kg) n Mean ± s.d. (kg) n Mean ± s.d. (kg) CV (%)

Marica 48 20.9 ± 6.6c 12 19.2 ± 5.3bc 60 20.5 ± 6.4c 31.0

Kacang 193 21.6 ± 5.9c 24 24.7 ± 6.1b 217 21.9 ± 5.9bc 27.1

Jawarandu 72 23.1 ± 7.9c 22 16.4 ± 4.8c 94 21.1 ± 7.8c 36.2

Benggala 89 24.7 ± 8.7b 7 16.0 ± 3.9c 96 24.1 ± 8.7b 36.2

Samosir 36 25.0 ± 5.4b 6 22.0 ± 8.1bc 42 24.6 ± 5.9b 23.8

Muara 28 37.5 ± 11.0a 2 49.0 ± 26.9a 30 38.2 ± 12.1a 31.6

Source: Batubara et al. (2011). n=number of samples; sd=standard deviation; CV=coefficient of variance

Means in the same column with different superscripts differ significantly (P<0.05).

The Kacang goat was known to adapt well to the humid, tropical environment of Indonesia and had

shown good productivity on limited feed resources. This breed also possessed good natural

characteristics of heat and tick tolerance and high fecundity under harsh circumstances (Sitepu

1985). Although the growth rate potential was relatively poor (Devendra & Burns 1983), Kacang

goats could achieve liveweights of 20 and 25 kg for adult does and bucks (Devendra & McLeroy

1982; Batubara et al. 2011) (Table 2.1).

Average birth weights of female and male Kacang kids in Purwodadi Regency were 1.9 ± 0.0 kg

and 2.1 ± 0.0 kg, respectively (Sodiq et al. 2010). Kacang does in Malaysia had longer postpartum

interval i.e. 106 ± 9 days when they had twins kids than had single kids i.e. 89 ± 8 days

(Thangavelu & Mukherjee 1983). Average kidding interval of Kacang does in RIGP Sungei Putih

Indonesia were between 247 ± 6 days (Elieser et al. 2012) and 268 ± 34 days (Doloksaribu et al.

2005) with an average of 37.12 kg meat/doe/year doe productivity (Elieser et al. 2012).


11


Available literature and information generated shows that Kacang goats have existed in Bali

Province for some time. Kacang goats were firstly introduced to Bali Province as Present Aid in the

era of the former Indonesian President Soeharto. About 1000 female and 100 male Kacang goats

were introduced to Bali Province during 1981 to 1987 (Anonymous 1990; Mantra 1991, 1994).

Kacang goats were commonly found in dry humid Kubu Village in Karangasem Regency (Oka et

al. 2011). BPS-Bali (2015) reported that Karangasem Regency had the largest number (14,469

goats) of Kacang goats among other regencies in Bali Province in 2014 (Table 4.4). Of note, there

is a lack of published data available on the productivity of Kacang goats reared under smallholder

production systems in Bali Province.

2.1.1.2 Gembrong goats

The Gembrong breed of goats originated from Karangasem, Eastern Bali (Matram et al. 1993;

Setiadi et al. 1998). In the Balinese language, Gembrong means hairy, with this breed having long

hair that covers its whole body including its neck and face, particularly in males (Plate 2.1). In

general, the colour of Gembrong goat body was white, or partly brown or solid brown (Hasinah et

al. 2015).

Gembrong goats were intermediate in size compared to Kacang goats and Etawah goats (Setiadi et

al. 1998; Zein et al. 2012). The average body weight of 15 Gembrong goats that were conserved in

Karangasem Regency was of 23.2 kg for females and 30.7 kg for males (Hasinah et al. 2015).

These were higher than 21.6 ± 5.9 kg for Kacang females and 24.7 ± 6.1 kg for Kacang males

(Batubara et al. 2011) (Table 2.1). Although Gembrong, Kacang and PE goats had a very close

genetic relationship (Oka et al. 2011), Gembrong were different from Kacang and PE goats

(Matram et al. 1993; Setiadi et al. 1998; Oka et al. 2011; Sulabda et al. 2012).

The Gembrong goat was in a critically low population and was being conserved extensively in the

BPTP farm in Tumbu Village in Karangasem Regency (Hasinah et al. 2015), also being conserved

in RIGP Sungei Putih North Sumatera (Sianipar et al. 2005) and in Pacet District in East Java

(Maharani et al. 2014). On 5th

July 2014, only 25 Gembrong goats were conserved in the BPTP

farm in the Tumbu Village (pers. obs.). The goal of their selection programme was for their

conservation (Sulandari et al. 2014; Hasinah et al. 2015) and for the potential production of

cashmere or fine silky hair (Setiadi et al. 1998; Oka et al. 2011).


12


2.1.1.3 Boer goats

The Boer goats from Australia were assessed for their production and reproductive traits in the

Research Institute for Goat Production (RIGP) Sungei Putih North Sumatera (Mahmilia & Tarigan

2004; Mahmilia 2007; Mahmilia & Elieser 2008; Mahmilia 2010; Mahmilia & Doloksaribu 2010;

Mahmilia et al. 2010; Sulastri 2010; Syawal 2010; Elieser et al. 2012). Fifteen Boer dams and five

Boer bucks were imported to RIGP Sungei Putih in 2004. During the first five years in RIGP

Sungei Putih, they produced 90 kids that were reared with dams until they were weaned at 3 months

of age (Mahmilia et al. 2010). Using crossbreeding the Australian Boer goats improved the quality

of Kacang and PE crossbreds as meat goat breeds to produce Boerka, Boerawa and their crossbreds

or backcrosses that were suitable to the tropical climate of Indonesia (Mahmilia & Tarigan 2004;

Elieser et al. 2006; Mahmilia 2007; Mahmilia & Elieser 2008; Mahmilia 2010; Mahmilia &

Doloksaribu 2010; Mahmilia et al. 2010; Elieser et al. 2012).

A pure Boer buck was brought from Jember District in East Java Province into Pucaksari Village in

Buleleng Regency in 2000. As a result, there were also Boerawa and their backcrosses reared by

smallholder farmers in Pucaksari, Buleleng Regency (Widiasa, K. 2014, pers. comm. 18 January)

(Plate 2.1). The Boer and crossbreds have adjusted well to the humid environment of Buleleng

Regency. Other than in Buleleng Regency, Boer, Boerawa or their crossbreds were unknown to be

in other regencies in Bali Province.

2.1.1.4 Boerka (Boer X Kacang) crossbreds

The Boerka crossbreds resulted from the cross between Boer bucks and Kacang does have been

greatly reviewed for their productivity in improving goat production in Indonesia (Mahmilia &

Tarigan 2004; Elieser et al. 2006; Mahmilia 2007; Mahmilia & Elieser 2008; Mahmilia 2010;

Simanihuruk & Sirait 2010; Elieser et al. 2012). Mahmilia (2007) reported that liveweight gain

from mating up to 3 months of pregnancy of Boer X Boer was not different from Kacang X Boer,

but it was significantly different (P<0.05) from Kacang X Kacang goats. The figures were 4.5 ± 1.5

kg; 4.1 ± 2 kg, and 2.3 ± 0.5 kg, respectively.

However, the kidding weight of Boer X Boer kids was significantly different (P<0.05) from Kacang

X Boer or Kacang X Kacang goats. Gestation, litter size and mortality rate were not significantly

different (P>0.05) between the three mating types of does. The relative superiority of Boerka kids

studied by Mahmilia and Doloksaribu (2010) was indicated by their birth and weaning weights.

The Boerka F1 (50 Boer : 50 Kacang) and Boerka Back Cross F1 (75 Boer : 25 Kacang) were

heavier than Kacang (100 Kacang) kids.


13


Field and laboratory research have shown that Boerka crossbreds adjusted well to humid tropical

environments; since their productive and reproductive performances were better than their parents

(Mahmilia & Doloksaribu 2010) (Table 2.2). In future, Bali Province should have more Boerka

crossbreds from the Research Institute for Goat Production in Sungei Putih or from the Indonesia

Research Institute for Animal Production (Balitnak-Ciawi) to improve goat productivity. The

Boerka crossbreds and other breeds that were commonly reared in Indonesia are shown in Plate 2.1.

Table 2.2 Average birth weights, weaning weights and average daily weight gains for preweaned

Kacang, Boerka F1 and Boerka Back Cross F1 kids. Variable Birth weight (kg) Weaning weight (kg) Daily weight gain preweaned (g)

n Mean ± s.d. n Mean ± s.d. n Mean ± s.d.

Average 564 2.0 ± 0.6 423 7.7 ± 2.6 423 61.5 ± 40.3

Genotypic *** *** ***

Kacang 142 1.7a ± 0.4 109 5.9a ± 1.8 109 45.7a ± 20.8

Boerka F1 326 2.1b ± 0.5 242 7.8b ± 1.8 242 62.6b ± 19.8

Boerka BC1 96 2.4c ± 0.5 72 9.1c ± 2.0 72 70.0 ± 31.8

Sex *** *** ****

Male 297 2.2a ± 0.5 214 8.4a ± 2.1 214 69.6a ± 31.8

Female 255 1.9b ± 0.6 209 7.0b ± 2.3 209 56.5b ± 27.6

Birth type ns *** ***

1 290 2.1a ± 0.6 231 8.3a ± 2.5 231 68.4 ± 27.3

>2 274 2.0a ± 0.5 192 7.0b ± 2.2 192 51.1b ± 22.5

Parity *** *** ****

1 219 1.9a ± 0.6 154 6.9a ± 2.1 154 52.3a ± 18.5

2 74 2.1b ± 0.6 143 8.1b ± 2.2 143 65.8b ± 20.1

>3 171 2.1b ± 0.5 126 8.3b ± 2.0 126 67.0b ± 16.7

r 0.20 0.22 0.14

Source: Mahmilia and Doloksaribu (2010). Means in a column with different superscripts differed significantly at the .05 level.

2.1.1.5 Boerawa (Boer X Peranakan Etawah) crossbreds

The Boerawa crossbreds resulted from the cross between Boer bucks and Etawah Grade or PE does

have been greatly reviewed for their productivity in improving goat production in Indonesia. Field

and laboratory research have shown that Boerawa crossbreds were well adjusted to humid tropical

environments (Sulastri 2010; Adhianto et al. 2013); since their productive and reproductive

performances were better than their parents (Sulastri 2010) (Table 2.3).

Table 2.3 Average weaning weight (kg), kidding interval (months), litter size, estimated

repeatability of weaning weight, average Dam Productivity Index (DPI) and Most Probable

Producing Ability (MPPA) of Boerawa F1, Back Cross F1 and Back Cross F2 Boerawa crossbreds. Breed Average

weaning

weight (kg)

Kidding interval

(month)

Average

litter size

Repeatability

estimate for

weaning weight

Average

DPI (kg)

Average MPPA

(kg)

Etawah Grade 17.7 ± 0.5 10.4 ± 2.0 1,7 ± 0.3 0.2 ± 0.7 35.1 ± 2.5 18.1 ± 0.4

Boerawa F1 21.0 ± 1.3 9.6 ± 1.8 1.9 ± 0.3 0.3 ± 0.3 50.9 ± 1.9 21.5 ± 0.1

Boerawa BC1 22.1 ± 1.9 9.2 ± 2.0 1.9 ± 0.2 0.4 ± 0.0 55.3 ± 1.3 22.6 ± 0.6

Boerawa BC2 23.3 ± 2.0 9.1 ± 1.8 1.9 ± 0.2 0.8 ± 0.2 59.7 ± 1.2 23.9 ± 1.2

Source: Sulastri (2010)


14


In future, Bali Province could have more Boerawa crossbreds from the Research Institute for Goat

Production in Sungei Putih or from the Indonesia Research Institute for Animal Production

(Balitnak-Ciawi) to improve goat productivity. Boerawa crossbreds and other breeds that were

commonly reared in Indonesia are shown in Plate 2.1.

2.1.2 Dairy goats

A search of Indonesian agricultural and animal science literature indicated that Indonesia had no

native dairy goat breeds. An annual report of the Directorate General of Livestock Service (DGLS)

in 1972 – 1973, cited in Tjokrohoesodo and Grossman (1975) mentioned that there were 751.5

thousand goats and buffaloes but the report did not mention the exact number or breed of goats.

The annual report of the DGLS continues up to the present (BPS-Bali 2015) did not mention goat

breeds nor their quantity or quality of goat milk production in Indonesia nor in Bali Province.

Devendra and Liang (2012) reported that although 60% of the world goat population were found in

Asia that was equivalent to 146 indigenous breeds, only 13 dairy breeds have been classified.

Goat milk and its products have an important role in human nutrition for feeding undernourished

people in the developing countries (Haenlein 2004; Devendra & Haenlein 2011). Haenlein (1996)

and Haenlein (2001) conducted technical studies and published in refereed journals and technical

books about nutritional studies with goat milk. They compared goat and cow milk for content of

enzymes, minerals, vitamins, miscellaneous constituents and physical properties that have medical

benefits to humans particularly treating people afflicted with cow allergies and gastro-intestinal

disorders. Haenlein (2004) studied the comparative protein and fat compositions and other unique

components of goats milk that have positive effects on human health. Goat milk reduces cancer

risks and prevents diabetes in men and coronary heart disease in woman due to its contents being

rich in omega 3 (Thorsdottir et al. 2004; Pihlanto 2006; Huffman et al. 2011). Goats milk is also

high in n-3 PUFA (Tschakert 2007), and high CLA (Pihlanto 2006). Goats are widely distributed

globally, and the developing world is the home of about 97% of the total world population of about

782 million goats (Devendra & Haenlein 2011).

Although goats could provide precious nutritious milk, meat (Haenlein 2004; Devendra & Haenlein

2011) and as a deposit for emergency needs for smallholder goat farmers in developing countries

including in Bali Province, farming families do not consume the products directly (Devendra 1986,

1988), so the result malnutrition still occurs. Women and children, the most vulnerable victims of

extreme poverty, are closely involved with rearing goats (Devendra 1986, 1988). For decades the


15


BPS Indonesia or BPS Bali have annually reported the number of PE and Kacang goats in Bali

Province, but with no reports of their milk production. No published references have mentioned

that Indonesian Government or other institutions have officially imported the exotic (Saanen, Boer,

Anglo-Nubian and Etawah) goat breeds for improving goat rearing in Bali Province. Strategic

plans of the Indonesian Minister of Agriculture for 2015-2019 did not have a specific strategic plans

for development of exotic goat breeds imported to particular district for improving quality of goats

under smallholder production system in Bali Province (Anonymous 2015c). Devendra (1992)

reported that wider official support, intensive use of improved breeds, use of appropriate organized

collection, transportation and marketing, extension and practical technologies and efficient delivery

systems to real farm situations need to be implemented. Furthermore, Devendra (1992) and

Devendra (2007) urged that its impact-oriented benefits could directly sustain pro-poor initiatives to

reduce poverty and hunger that are consistent with income growth, socioeconomic benefits,

improved livelihoods and self-reliance.

2.1.2.1 Etawah or Jamnapari goats

The Etawah or Jamnapari goat is known for high milk production that is average 210 kg in 260

lactating days. The large, long legged Indian breed for females weigh 40 kg and are 75 cm high at

withers while males weigh about 50 kg and are 78 cm high at withers. The ears are very long and

pendulous, with dominant white coat colour. The Jamnapari is one of the tallest goat breeds and

has been bred and selected for tall legs, to give the udder clearance. (Devendra & Haenlein 2011).

Gall (1980) reported that good legs and feet are very important for a productive dairy goat. The

legs should be squarely set, wide apart and straight when seen from the front or rear.

However, Etawah goats reared today by smallholder farmers across Indonesia were no longer

guaranteed to be pure as the Etawah imported from Jamnapari have been crossed with Kacang or

other local goat breeds (Merkens & Soemirat 1926; Merkens 1930, 1931; Merkens & Sjariff 1932).

This was in agreement with Sitorus et al. (1982) who argued that pure Kacang and pure Etawah (the

Jamnapari breed, first introduced from India) breeds were difficult to find, as the 'Etawah cross' is

now the most common type in most areas of Java. PE or Etawah Grade crossbreds have gradually

been increasing in number and in popularity (Knipscheer et al. 1984). This was due to this breed

being well adjusted to Indonesia‘s humid tropical environment; in addition to their ability to survive

on low quality feed (Suranindyah 2004), and produce quality, and larger quantities of milk

(Suranindyah et al. 2009a; Zurriyati et al. 2011). Zurriyati et al. (2011) reported that Etawah grade

milk had highest (P < 0.05) density value (1.033 ± 0.002) and solid non-fat (9.577 ± 0.704%) than

those of Saanen and PE-SA fresh milk goat. However, they had 21-64 litre/lactation/goat for 130-


16


153 lactating days (Suranindyah et al. 2009a). Therefore, goat research in Indonesia, particularly

milk producing goat breeds always refers to the improvement of milk production by upgrading them

with Etawah goats.

2.1.2.2 Saanen goats

Even though the Saanen breed was well known for their high milk producing ability i.e. annual milk

production ranges from 300 to 2,000 kg in 150-300 days of lactation, depending on the country

(Devendra & Haenlein 2011), it was not very popular with smallholder farmers in Bali Province.

No publications were found in relation to the time and place of the original Saanen goats imported,

as well as their rearing systems for their milk production in Bali Province. In addition, Saanen

goats were still being assessed in the IRIAP (Balitnak-Ciawi) for crossing with Etawah Grade goats

that produce PE-SA crossbreds (Praharani et al. 2013; Praharani et al. 2015). Research on

upgrading programmes on the imported Saanen goats and their crossbreds showed that milk quality

of Etawah Grade crossbreds milk had the highest density value (1.033 ± 0.002) and solid non-fat

(9.6 ± 0.7%) than those of Saanen and PE-SA fresh milk (Zurriyati et al. 2011). This finding

indicated that PE crossbreds were the best milk-producing goat found in Indonesia.

Birth weight of Saanen kids reared in Brazil i.e. 2.8 ± 0.2 kg (Freitas et al. 2004a) was lower than

the birth weight of 3.9 ± 0.1 kg, 3.4 ± 0.6 kg and 3.2 ± 0.7 for PE kids from PE does. These PE

does produced low, medium and high milk production when reared in Balitnak-Ciawi (Sutama et al.

1999) (Table 2.12). Saanen females that were reared in Brazil reached their first puberty at 135 ± 2

days (Ferraz et al. 2009) or 148 ± 21 days (Freitas et al. 2004a) earlier compared to 362 ± 18 days

of PE females with high milk production that were reared in Balitnak-Ciawi (Sutama et al. 1999).

However, PE females reached bodyweight of 18.8 ± 1.6 kg (Sutama et al. 1999) lower than Saanen

females were 19.7 ± 0.3 kg (Ferraz et al. 2009) and 22.5 ± 1.7 kg (Freitas et al. 2004a) when they all

reached their first puberty (Table 2.5). The highest average milk production of Saanen goats reared

in Croatia was 588 litre milk with 21.6 kg fat was in the third lactation (Antunac et al. 1999)

although Saanen goats could reach 2,000 kg milk production in 150-300 days of lactation

(Devendra & Haenlein 2011). The highest average milk production of PE crossbreds was 203.2 ±

66.6 kg/goat/lactating period which was 245.5 ± 102.3 days with average fat content of 4,4 ± 0,6%

(Budiarsana 2011). The average body weight of adult males is 90 kg with 90 cm of height at

withers and that of females 65 kg with 80 cm of height at withers (Devendra & Haenlein 2011). In

future, Saanen goats are expected to upgrade indigenous breeds through crossbreeding to improve

goat productivity particularly milk production in Busungbiu District, Buleleng Regency that is well-

known with their goat milk production.


17


2.1.3 Dual-purpose goats

The majority of goat breeds in developing countries were dual-purpose breeds used mainly for meat

production plus low to medium milk production (Tillman 1981; Peacock 1996).

2.1.3.1 Peranakan Etawah (PE) crossbreds

Peranakan Etawah aka PE or Etawah Grade crossbreds were milk and meat producing goats

(Merkens & Soemirat 1926; Merkens 1930, 1931; Merkens & Sjariff 1932). Dual-purpose PE

crossbreds had large body frames, long hanging ears, a convex face and large horns and a wither

height of 72 to 90 cm. The average slaughter weight for males was 37 kg and 32 kg for females.

PE crossbreds had the highest milk yield among Indonesian native goats (Setiadi et al. 1997; Sodiq

et al. 2004). The peak milk yield for PE crossbreds in Indonesia was about 1 to 1.25 litre/goat/day

(Riyanto & Anam 2012), with a 4 month lactation (Astuti et al. 2000).

The length and size of the floppy ears as well as the body size of PE goats usually determined the

degree of purity of Etawah goats. The longer the floppy ears, the purer the degree of the Etawah

goats, particularly with the white body coat colour (SNI 2008). To ensure high quantity and quality

of production of PE goats, Indonesian National Standardization (SNI 2008) requires 23 ± 3 cm of

ears length and 29 ± 5 kg bodyweight required for male PE breeding stock aged 0.5-1 year or 24 ± 3

cm of ears length and 22 ± 5 kg bodyweight for female breeding stock aged 0.5-1year. In addition,

Goat Breeding Centre in Kaligesing, Indonesia classified Etawah into three grades based on their

body measurement at particular ages as Etawah Grade A is a superior grade, B is moderate, and C is

the lowest grade (Rasminati 2013).

PE crossbreds were important component of farming activities for Indonesian smallholder farmers

(Budiarsana 2011; Elieser et al. 2012). For instance, most of the farmers (84%) in Lumajang and

Ponorogo Regencies in East Java preferred to keep PE crossbreds than Kacang goats as they

considered PE crossbreds could be sold at a higher price (Djoharjani 1996). PE crossbreds showed

high levels of milk production, persistency and efficiency of milk production and this crossbred was

easy to be managed by small farmers in the rural areas, and economically feasible to be developed

commercially (Sutama et al. 1999; Budiarsana 2011). Besides, the price of one litre of goat milk

was IDR 50,000 or 10 times higher than for one litre of cow‘s milk in Indonesia in July 2013

(www.kompas.com downloaded on Wednesday, July 31, 2013) as many believe there were healthy

beneficial contents in goat milk (Bernacka 2011).


18


PE goats were first introduced to Bali Province as Present Aid in the era of the former Indonesian

President Soeharto. About 1,000 female and 100 male PE goats were introduced to Bali Province

during 1981 to 1987 (Anonymous 1990; Mantra 1991) including to Mengwi District in Badung

Regency (Mantra 1994). Except in Karangasem Regency, smallholder farmers in Bali Province

preferred rearing PE crossbreds rather than other goat breeds (BPS-Bali 2015). They primarily

raised PE crossbreds for meat but in Buleleng Regency that had the largest number of 26,021 PE

crossbreds in 2014, PE crossbreds were raised for both meat and milk (BPS-Bali 2015). Since the

Simantri programme was introduced to Bali Province in 2009, goat smallholder farmers were

encouraged to milk their PE crossbreds. At present, smallholder farmers in Busungbiu District in

Buleleng Regency as well as in Pupuan District in Tabanan Regency milked their PE crossbreds

(pers. obs.).

The University of Udayana Bali that conducted research on milk production and milk quality of PE

crossbreds reported that the potential to produce milk from PE does at about 1.6 litres per day

(Supriyono 1994) with 5.7% fat (Junaedi 2007) and 5.0% protein (Musyafak 1995) (Table 2.4).

Table 2.4 Milk production, fat and protein percentages of PE crossbreds reared in Bali. Milk production (ml/h/d) Fat (%) Protein (%) Study

980 – 1,627 3. 4 – 4.9 2.9 – 3.7 Supriyono (1994)

408 – 551 4. 6 – 5.5 4.2 – 5.0 Musyafak (1995)

886 – 1,475 3. 8 – 4.8 3.4 – 3.7 Nurprihadi (1995)

520 – 885 4. 3 – 5.3 3.9 – 4.7 Santoso (1995)

674 – 1,128 3. 8 – 4.8 3.5 – 4.2 Ridwan (1998)

861 – 679 5. 1 – 5.7 4.0 – 4.2 Junaedi (2007)

Sukarini (2006) reported that PE does achieved a daily milk yield of about 1.6 litres/goat/day when

they were supplemented with concentrates compared to 0.98 litres/goat/day with no concentrate

supplementation. This indicated the opportunity to produce more and higher quality milk from PE

crossbreds in Bali in the future.

2.1.3.2 Benggala goats

Available literature and information generated shows that Benggala goats have existed in Bali

Province for some time. Benggala goats were firstly introduced to Bali Province as Present Aid in

the era of the former Indonesian President Soeharto. About 1000 female and 100 male Benggala

goats were introduced to Bali Province during 1981 to 1987 (Anonymous 1990; Mantra 1991)

including to Busungbiu District in Buleleng Regency (Widiasa, K. 2014, pers. comm. 18 January).

The mean bodyweight of Benggala goats as well as their morphometric and phylogenic analysis


19


compared to Marica, Kacang, Samosir, Jawarandu and Muara goats are shown in Table 2.3

(Batubara et al. 2011).

Although Benggala goats have adjusted to the humid environment of Bali Province, it seemed

smallholder farmers in Bali Province, particularly in Busungbiu District in Buleleng Regency

preferred rearing PE crossbred to produce meat and milk. However, no published reviews of Bali

Government reports mentioned the milk production of goats reared in Bali province (BPS-Bali

2015).

Therefore, there were at least 15 goat breeds and 5 crossbreds of meat, dairy and dual-purpose goats

that were commonly reared by smallholder farmers in many types of integrated farming systems

across Indonesia. Kacang, Gembrong, Marica, Muara, Samosir, Kejobong, Kosta, Angora,

Cashmere, Anglo-Nubian, Boer goat breeds and Boerka and Boerawa crossbreds were meat goats

while Etawah/Jamnapari, Saanen were known as dairy goat breeds and Jawarandu and Benggala

goat breeds and PE, PE-SA, PE-AN crossbreds, were dual purpose goat breeds. However, available

literature and information generated showing that smallholder farmers in Bali Province reared

Etawah Grade, PE and Kacang (Mantra 1991, 1994; BPS-Bali 2015), Benggala (Anonymous 1990;

Mantra 1991), Gembrong (Matram et al. 1993; Oka et al. 2011; Sulabda et al. 2012; Hasinah et al.

2015), Boer, Boerawa and their crosses (Widiasa, K. 2014, pers. comm. 18 January) (Plate 2.1).

The Boer and crossbreds have just adjusted well to the humid environment of Buleleng Regency.

2.2 Factors influencing reproductive performance in female goats

Reproductive performance was the most important factor affecting flock productivity (Menendez-

Buxadera et al. 2004; Garcia-Peniche et al. 2012; Lopes et al. 2012; Adhianto et al. 2013; Yagoub

et al. 2013; Kunbhar et al. 2016) thus dictated the rate of expansion of the flock, the number of

excess stock for sale and thus milk available for home consumption and sale (Peacock 1996). This

also dictated the larger number of offspring available for breeding stock for selection programmes

(Peacock 1996; Abebe 2009) consequently improved the ratio of units of output per units of input to

achieve efficient goat production (Knipscheer et al. 1984; James & Carles 1996).

Various indicators were used to measure reproductive performance in female goats such as number

of weaned animals, weaned weight relative to the number of reproductive females (Menendez-

Buxadera et al. 2004) and length of kidding interval (Greyling & Vanniekerk 1991). Additional

measurements included the breeding season, litter size at birth, litter birth weight, ages at first

service, conception, and first kidding (Kataktalware et al. 2004), litter size (Menendez-Buxadera et


20


al. 2004), the growth and viability of the offspring (Shelton 1978; Greyling 2000) and number of

services per conception, and the postpartum anoestrus period or days open (Abebe 2009).

Because of little documented data on reproductive performance indicators of goats reared by

smallholder farmers in Bali Province was available, it was the intention of this study to measure a

set of indicators for reproductive performance of goats in Bali Province. This review of literature is

limited to the measurements of age of puberty (Freitas et al. 2004a; Delgadillo et al. 2007), age at

first kidding (Abebe 2009; Lopes et al. 2012), postpartum interval (Al-Hozab et al. 1999; Freitas et

al. 2004a; Freitas et al. 2004b; Abebe 2009), kidding interval (Mani et al. 1996; Martin et al. 2004),

fertility (Abebe 2009), litter size (Alexandre et al. 1999; Mellado et al. 2006) and annual

reproductive rate (Sodiq et al. 2003; Sodiq & Tawfik 2003; Sodiq et al. 2004; Sodiq & Haryanto

2007; Elieser et al. 2012; Adhianto et al. 2013). A combination of two or more traits could be used

as a measure of reproductive performance. Identifying factors influencing the efficiency of goat

production reared by smallholder farmers is believed could identify the constraints to, challenges of

and opportunities of improving goat rearing in Bali Province. Each of these will be discussed in

detail in the following.

2.2.1 Age of puberty

Age at puberty was defined as the date of first oestrus followed by luteal function (Freitas et al.

2004a; Delgadillo et al. 2007). It was followed by characteristic cyclic ovarian activity in the non-

pregnant animal (Greyling 2000) but animals were not yet fully sexually mature at this stage

(Abebe 2009). A female animal had reached puberty when she was able to release gametes and to

manifest complete sexual behavioural sequences (Freitas et al. 2004a).

Understanding the correct weights and age of pubertal female goats and the factors that affected

them were crucial in improving the efficiency of goat production (Salles et al. 2001). Early mating

and subsequent pregnancy could bring negative consequences to the growth and reproductive

performance of young female goats. It was important that pubertal females were mated when they

had reached sexual maturity at about 70% of their adult weight (Salles et al. 2001). Waldron et al.

(1999) noted that Boer X Spanish and Spanish X Spanish reached their first oestrus at 45% and

50% of their 18-month bodyweight, respectively. Anglo-Nubian yearlings that were reared in

Khartoum North, Sudan attained puberty at the age of 265 ± 16.5 days with a mean bodyweight of

16.8 ± 0.6 kg (Yagoub et al. 2013). Since puberty was more dependent on bodyweight than age of

the animal, it was common to delay mating. However, delaying mating for an extended period

would shorten the productive life of female goats (Hassan et al. 2007).


21


Published data on age of first puberty was reported from 135 to 374 days (4.4 to 12.3 months) with

16 to 32 kg bodyweights in different breeds of goats under different ecological and management

conditions and is summarized in Table 2.5.

Table 2.5 A summary of published data on ages (days) and bodyweights (kg) of first puberty in

female goats. First puberty Breed Location Reference

Weight (kg) Age (days)

Mean ± SEM Mean ± SEM

32.0 ± 1.7 341 ± 21 Anglo-Nubian Brazil Ferraz et al. (2009)

26.4 ± 5.6 256 ± 70 Anglo-Nubian Brazil Freitas et al. (2004a)

16.8 ± 0.6 265 ± 16 Anglo-Nubian Sudan Yagoub et al. (2013)

29.8 ± 0.9 264 ± 19 Anglo-Nubian X Saanen Brazil Ferraz et al. (2009)

10.01 ± 0.2 234 ± 6 Black Bengal Bangladesh Halim et al. (2011)

18.8 ± 0.5 234 ± 4 Boer X Spanish USA Waldron et al. (1999)

16.8 ± 3.9 355 ± 17 Jamnapari Bangladesh Hassan et al. (2010)

19.9 ± 1.5 321 ± 63 Low

Medium

High

Level of milk

production of

PE does

Balitnak- Ciawi Sutama et al. (1999)

18.2 ± 0.8 341 ± 72

18.8 ± 1.6 362 ± 18

22.5 ± 1.7 148 ± 21 Saanen Brazil Freitas et al. (2004a)

19.7 ± 0.3 135 ± 2 Saanen Brazil Ferraz et al. (2009)

19.2 ± 0.5 229 ± 4 Spanish X Spanish USA Waldron et al. (1999)

Unlike the goats reared in temperate regions that their seasonal breeding period was affected by

latitude, climate, breeding systems and specifically photoperiod (Walton et al. 2011; Willard 2011;

Valasi et al. 2012), in tropical regions, goats were considered continuous breeders. Restricted food

availability often affected birth liveweight, thus bodyweight for female goats ready to be mated that

had reached breeding maturity (Aritonang 2009; Fatet et al. 2011). This indicated that attaining

correct liveweight was more critical than age in determining time of sexual maturity (Delgadillo et

al. 2007). Of note, none of the published literature made any mention of the effects of age and

weight of first puberty on sexual maturity of goats reared in Bali Province.

The age of puberty was not only affected by the role of hormones (Shahnaz et al. 2000; Shahnaz et

al. 2001; Yagoub & Elsheikh 2003; Yagoub et al. 2013) but was also affected by breed differences

(Ferraz et al. 2009). For example, PE crossbreds reared in Indonesia reached puberty at various

bodyweights between 12 to 23.8 kg at ages from 10 to 12 months (Tomaszewska et al. 1991). PE

females observed in Balitnak-Ciawi, reached their puberty at average bodyweights of 18.8 ± 0.4 kg

at 13 weeks of age (Sutama et al. 1995). Kosta females reared in Bandung Indonesia reached

sexual maturity at average bodyweights of 7.6 ± 0.7 kg at 19.5 ± 1.3 weeks of age (Siwi et al.

2011). Observations of ages and bodyweight at first puberty were also different between the

Saanen and Anglo-Nubian kids that were raised in a semi-arid region of north-eastern Brazil

(Freitas et al. 2004a). Saanen female kids achieved puberty at 147.8 ± 21.1 days with bodyweights


22


of 22.5 ± 1.7 kg while the Anglo-Nubian kids were 256.3 ± 69.6 days and with bodyweights of 26.4

± 5.6 kg.

The age of puberty was also affected by the quality of roughage or feedstuffs fed to female goats.

The quality of nutrition fed influenced the growth and sexual development of female kids hence

promoted puberty that improved their reproductive performance (Robinson 1990, 1996; Robinson et

al. 2006). Improved feeding quality reduced significantly the age of puberty by 19 days in

Moroccan indigenous goats i.e. 278 ± 8 days vs 297 ± 2 days (Chentouf et al. 2011). Sutama et al.

(1999) reported that PE female kids fed different quality of nutrition reached different average

puberty bodyweights i.e. 19.9 ± 1.5 kg, 18.2 ± 0.8 kg and 18.8 ± 1.6 kg at average ages of 321 ± 63

days, 341 ± 72 days and 362 ± 18 days, respectively.

2.2.2 Age at first kidding

Age at first kidding was defined as the age at which a doe had her first litter of kids (Abebe 2009).

An earlier age at first kidding promoted simultaneous improvement in her productive and

reproductive performance (Lopes et al. 2012). A variation in age at first kidding in does was

affected by breed (Perez-Razo et al. 2004) and maternal behavioural effects (Weppert & Hayes

2004). Although Bagnicka et al. (2001) found that there was a linear increase of milk, fat and

protein yield with increasing age at first kidding, delaying breeding for a long time decreased the

margin of profit by decreasing lifetime production (Hassan et al. 2007). Published data on age of

first kidding that was reported from 360 to 686 days (11.8 to 22.5 months) in different breeds of

does under different ecological and management conditions and is summarized in Table 2.6.

Table 2.6 A summary of published data on age of first kidding (days) in female goats. Age of 1st kidding (days) Breed Location Reference

Mean ± SE

517 ±155 Alpine USA Garcia-Peniche et al. (2012)

534 ± 153 Anglo-Nubian

674 ± 23 Anglo-Nubian F1 Trinidad Lallo et al. (2012)

686 ± 35 Anglo-Nubian F1

362 ± 11 Black Bengal Bangladesh Halim et al. (2011)

360 ± 10 Black Bengal Bangladesh Hassan et al. (2007)

411 ± 15 Black Bengal crossbred

643 ± 7 Dairy crossbred India Kataktalware et al. (2004)

549 ± 68 Jamnapari Bangladesh Hassan et al. (2010)

444 ± 8 Pure dairy Tanzania Jackson et al. (2012)

398 ± 12 Tanzania

498 ± 132 Saanen Mexico Torres-Vazquez et al. (2009)

402 ± 19 Saanen Brazil Ribeiro et al. (2000)

472 ± 140 Saanen USA Garcia-Peniche et al. (2012)

638 ± 52 Saanen F1 Trinidad Lallo et al. (2012)

657 ± 50 Saanen F1

428 ± 11 Surti Gujarat Sabapara et al. (2010)

494 ± 154 Toggenburg USA Garcia-Peniche et al. (2012)


23


The season of a kids birth affected the onset of its puberty (Delgadillo et al. 2007) hence an earlier

age of first kidding was achievable (Kataktalware et al. 2004). The season of a kids birth was

correlated with the availability of feed for pregnant does (Walkden-Brown & Bocquier 2000).

Higher birth weight was an important factor in obtaining a higher puberty liveweight at an earlier

age (Delgadillo et al. 2007). This led to improved efficiency in goat production. An average of 3.1

± 0.1 kg of female kids born in May in Mexico that had average daily gain of 122 ± 3 g achieved

average bodyweight at puberty of 28 ± 0.8 kg and attained age at puberty at 201 ± 3 days. These

productive parameters were higher than in those female kids born in October that had 2.7 ± 0.5 kg,

83 ± 4 g, 32 ± 1.3 kg and 344 ± 5 days, for the four reproductive parameters, respectively

(Delgadillo et al. 2007). However, there was a lack of published data available regarding the age of

first kidding of does reared in Bali Province. Thus, it is necessary to measure the age at first

kidding of any goat breeds reared under smallholder farming systems in Bali Province.

2.2.3 Postpartum interval

Postpartum interval was defined as the time between parturition and the resumption of cyclic

ovarian activity in breeding females (Al-Hozab et al. 1999). Postpartum interval was a major factor

in controlling the kidding interval thus, it contributed significantly to productive efficiency (Freitas

et al. 2004a; Freitas et al. 2004b; Abebe 2009). Does reared in Indonesia under smallholder

production systems were expected to kid three times in two years with twin kids (Sodiq & Haryanto

2007; Budisatria et al. 2012). Setiadi et al. (1997) reported that PE females observed in Balitnak-

Ciawi had an average first oestrus at 56 days (range of 26 to 99 days) after parturition. Shorter

gestation length, postpartum period and kidding interval for does as well as multiple births was

possible for efficient goat production (Khanum et al. 2007).

Breed affected the length of postpartum interval (Hassan et al. 2007). The average postpartum

period for Black Bengal does of 38.7 ± 10.5 days, which was shorter than that of crossbreds with

121.7 ± 15 days. These lengths resulted in shorter kidding intervals in Black Bengal does of 179 ±

20 days rather than 270 ± 22 days in crossbreds reared in Bangladesh (Hassan et al. 2007).

Published data on postpartum interval was reported to be from 27 to 160 days (0.9 to 5.2 months) in

different breeds of goats under different ecological and management conditions and is summarized

in Table 2.7.

To be able to have a kidding interval of about 8 months, dams need to receive sufficient quantity

and quality of nutrition to obtain an early oestrus postpartum as well as improved fertility

(Robinson 1990, 1996; Robinson et al. 2006). Low levels of nutrition fed to female kids caused


24


reduced growth rates during their rearing phase (Bagnicka et al. 2002; Ugur et al. 2004). Poor

nutrition significantly reduced the expression of oestrus, conception, fecundity and twinning rates in

does (Kusina et al. 2001). This was due to a decrease in the number of goats exhibiting a pre-

ovulatory surge of gonadotrophins, reduced magnitude of the surge, and reduced incidence of

ovulation (Mani et al. 1996). This potentially resulted in both longer postpartum and kidding

intervals thus reducing the productivity of female goats (De Santiago-Miramontes et al. 2011).

Table 2.7 A summary of published data on postpartum interval (days) in female goats. Postpartum interval (days) Breed Location Reference

Mean ± SE

79 ± 8 Anglo-Nubian Brazil Freitas et al. (2004b)

51 ± 4 Black Bengal Sudan Yagoub et al. (2013)



62± 20 Boer S. Africa Greyling (2000)

122 ± 15 Crossbred Bangladesh Hassan et al. (2007)

27 ± 6 Dwarf Pakistan Shahnaz et al. (2001)

97 ± 6 Kacang Malaysia

Thangavelu and Mukherjee (1983)

89 ± 8 Kacang with single kids

106 ± 9 Kacang with twins kids

34 ± 0 Kacang with aborted kids

112 ± 41 Local goat, S type Burundi Mbayahaga et al. (1998)

160 ± 58 Local goat, T type

144 ± 56 Local goat, Combined

95 ± 12 Saanen Brazil Freitas et al. (2004b)


2.2.4 Kidding interval (Parturition interval)

Parturition interval, also known as kidding interval, was defined as the number of days between

successive parturitions. The length of kidding interval was an important trait in goat production due

to its effects on the goat population‘s turnover rate and total lifetime productivity (Mani et al. 1996;

Martin et al. 2004). Attempts to shorten the length of postpartum and gestation intervals potentially

resulted in shorter lengths of kidding intervals thus increasing the efficiency of goat production

(Sodiq & Haryanto 2007; Budisatria et al. 2012).

Sodiq and Haryanto (2007) reported that kidding intervals of Kejobong goats reared in Central Java,

Indonesia shortened progressively with the advance in the parity and the type of birth i.e. single,

twin and triple kids thus increased doe productivity (kg meat/doe/year) (Table 2.8).


25


Table 2.8 Litter size at weaning, kidding interval and doe productivity of Kejobong goats in

Kejobong District, Indonesia. Traits n Litter size at weaning (goats) Kidding interval (days) Doe productivity (kg meat/doe/year)

Mean ± SEM Mean ± SEM Mean ± SEM

Overall 212 160 ± 0.0 268 ± 2.4 26.6 ± 0.8

Parity ** ** **

1st Parity 78 1.5 ± 0.1a 278 ± 4.7a 23.6 ± 1.3a

2nd Parity 53 1.6 ± 0.1a 269 ± 5.0a 26.9 ± 1.6a

3rd Parity 44 1.7 ± 0.1bc 261 ± 4.4b 29.7 ± 1.7b

4th Parity 13 1.9 ± 0.1b 256 ± 7.3b 32.7 ± 2.8b

5th Parity 11 1.8 ± 0.1bc 256 ± 8.4b 31.3 ± 2.6b

6th Parity 4 1.5 ± 0.3ac 255 ± 9.4b 25.3 ± 4.4a

7th Parity 9 1.3 ± 0.2ac 253 ± 5.3b 22.9 ± 3.0a

Type of birth ** ** **

Single 66 1.0 ± 0.0a 296 ± 4.5a 14.6 ± 0.3a

Twin 128 1.9 ± 0.0bc 259 ± 2.4b 31.3 ± 0.6b

Triplet 18 2.1 ± 0.0c 237 ± 4.8c 37.9 ± 4.4c

Source: Sodiq and Haryanto (2007). Means in a column with different superscripts differed significantly at the .05 level.

Doe productivity indicates kg meat produced per doe per year.

A scenario to shorten kidding interval in PE crossbreds from 278 days to 240 days in middle zone

and from 273 days to 220 days in upland Yogyakarta Province, Indonesia produced 2.2 and 1.7

times more kids than in the real situation in the middle zone and uplands, respectively. Reducing

kidding intervals also resulted in an increase in the number of kids sold by 1.2 and 1.3 respectively

for kidding intervals of 240 and 220 days in the middle zone; while in the uplands this was 1.1 and

1.3 times respectively. The breeding scenario calculations indicated when the kidding interval was

shortened i.e. 8 months, smallholder farmers achieved greater economic benefits (Budisatria et al.

2012).

Factors such as breed, litter size, parity and month of mating (Amoah et al. 1996) including season

of parturition (Delgadillo et al. 1998) influenced both the length of postpartum and gestation

periods thus the length of kidding interval. An average bodyweight of 34 ± 7 kg for PE does

observed in Balitnak-Ciawi had a positive significant correlation with gestation period 150 ± 3 days

(r=0.379) (Kostaman & Sutama 2006). Average doe bodyweights i.e. 35 ± 6.7 kg, 38 ± 5.1 kg and

39 ± 5.1 kg for PE does observed in Balitnak-Ciawi had different lengths of gestation periods, i.e.

149 ± 2 days, 146 ± 8 kg and 150 ± 3 kg, respectively (Novita et al. 2006). Understanding the

reproductive potential of goats therefore could optimise their reproductive efficiency (Greyling

2000).

Published data on kidding interval was reported to be from 179 to 532 days (5.9 to 17.4 months) in

different breeds of does under different ecological and management conditions and is summarized

in Table 2.9.


26


Table 2.9 A summary of published data on kidding interval (days) in female goats. Kidding interval (days) Breed Location Reference

Mean ± SEM

381 ± 82 Alpine USA Montaldo et al. (2010)

384 ± 84 Garcia-Peniche et al. (2012)

379 ± 84 Anglo-Nubian

479 ± 34 Anglo-Nubian F1 Trinidad Lallo et al. (2012)

319 ± 35 Anglo-Nubian F1

240 ± 8 Anglo-Nubian Sudan Yagoub et al. (2013)

373 ± 75 Anglo-Nubian USA Montaldo et al. (2010)



301 ± 10 Boer RIGP Sungei Putih,

Indonesia

Elieser et al. (2012)

288 ± 53 Boerawa F1 Lampung, Indonesia Sulastri (2010)

276 ± 59 Boerawa BC1

272 ± 53 Boerawa BC2

270 ± 22 Black Bengal crossbreds Bangladesh Hassan et al. (2007)

312 ± 60 Etawah Grade Lampung, Indonesia Sulastri (2010)

210 ± 29 Jamnapari Bangladesh Hassan et al. (2010)

247 ± 6 Kacang RIGP Sungei Putih,

Indonesia

Elieser et al. (2012)

268 ± 34 Doloksaribu et al. (2005)

296 ± 4 Single

Twin

Triplet

Average

Kejobong Kejobong, Indonesia Sodiq and Haryanto (2007)

259 ± 2

237 ± 5

268 ± 2

328 ± 37 Saanen Brazil Ribeiro et al. (2000)

384 ± 93 Saanen USA Montaldo et al. (2010)

388 ± 91 Saanen USA Garcia-Peniche et al. (2012)

521 ± 94 Saanen F1 Trinidad Lallo et al. (2012)

474 ± 66 Saanen F1


382 ± 78 Toggenburg USA Montaldo et al. (2010)

382 ± 85 Toggenburg USA Garcia-Peniche et al. (2012)

532 ± 5 Kamohri Pakistan Kunbhar et al. (2016)

2.2.5 Fertility or the number of does serviced per conception (S/C)

Various definitions of fertility in relation to goats existed in the scientific literature - such as

conception rate, fecundity, prolificacy, and birth rate (Mellado et al. 2006; Abebe 2009; Faruque et

al. 2010). A general definition of fertility was the number of does kidding divided by the number of

does mated or the number of does serviced per conception (S/C) and for the male by the percentage

of services which resulted in conception (Abebe 2009). Published data on number of services per

conception (S/C) that was reported from 1 to 1.8 in different breeds of does under different

ecological and management conditions is summarized in Table 2.10.

Table 2.10 A summary of published data on number of services per conception in female goats. S/C

Mean ± SEM

Breed Location Reference

1.2 ± 0.2 Black Bengal Under semi-scavenging farming systems Halim et al. (2011)

1.2 ± 0.0 Bangladesh Livestock Research Institute Faruque et al. (2010)

1.0 ± 0.0 In intensive rearing systems

1.2 ± 0.2 In semi intensive rearing systems

1.4 ± 0.1 Breeding season March to June

1.0 ± 0.4 Breeding season July to October

1.8 ± 0.3 Breeding season November to February

1.2 – 1.7 Black Bengal Bangladesh Livestock Research Institute Chowdhury et al. (2002)

1.3 ± 0.0 Dairy crossbred NDRI Haryana, India Kataktalware et al. (2004)

1.3 ± 0.6 Jamnapari Bangladesh Hassan et al. (2010)


27


Photoperiodism was defined as the ability of plants and animals to measure environmental day

length to ascertain time of year. Central to the evolution of photoperiodism in animals is the

adaptive distribution of energetically challenging activities across the year to optimize reproductive

fitness while balancing the energetic tradeoffs necessary for seasonally-appropriate survival

strategies (Walton et al. 2011). Photoperiod, where changes in day length that was known to

influence the onset of puberty (Valasi et al. 2012; Flores et al. 2013) were also known to control

signals for seasonal breeding rhythms for goats in temperate regions or in sub-tropical areas

(Carrillo et al. 2010; Flores et al. 2013). Therefore, setting a breeding plan that suited the time of

breeding of goats in a temperate climate, optimised the service per conception to around 1 to 2

(Mellado et al. 2000b). Mating Anglo-Nubian, Granadina, Saanen, Toggenburg and French Alpine

goats in their sexually active period in autumn (Oct. to Dec.) resulted in lower S/C and does were

nine times more likely to become pregnant than in summer (May to Sept.) (Mellado et al. 2006).

This was due May was the hottest month of the year in a hot arid environment of northeast Mexico

(Mellado et al. 1991; Mellado et al. 2006). Similarly, mating does in July to October decreased the

S/C to 1 ± 0.4 compared to does that were mated in November to February i.e. 1.8 ± 0.31 (Faruque

et al. 2010).

However, plane of nutrition, availability of forage, the presence of buck, and temperature had more

influence than photoperiod on the season of breeding of goats reared under subtropical conditions

(Urrutia-Morales et al. 2009) as well as in most tropical areas (Delgadillo et al. 1997). Indonesian

goats like other goats in tropical regions, did not have the same response to changes in the length of

the day due to it was little variation in the length of day. As a result, tropical goats were capable of

breeding all year (Djajanegara & Setiadi 1991; Restall 1991; Carrillo et al. 2010). Setiadi et al.

(1988) reported that the average ovulation rate of Etawah goats in Indonesia was 1.5 (range=1 to 3).

Ultimately, it was crucial to know whether goats reared in Bali Province were capable of breeding

all year.

2.2.6 Litter size

Litter size was defined as the total number of kids born per kidding and per goat (Alexandre et al.

1999) including still-born kids (Mellado et al. 2006). Litter size was one aspect of maternal abilities

affecting birth weight and was used as an indicator to measure the reproductive performance of

goats. Published data on litter size that was reported from 0.99 to 2.34 in different genotypes of

does with information about the type of birth, sex of kid, and parity of does under different



28


Table 2.11 A summary of published data on litter size (goats) of different genotypes of goats with

information about the type of birth, sex of kid, and parity of does. Litter size

(goats)

Breed Type of birth Location Reference

Mean ± SEM

1.9 ± 0.1 Alpine American Mixed Georgia Amoah et al. (1996)

2.0 ± 0.1 Anglo-Nubian Mixed

1.6 ± 0.5 Primiparous Mexico Mellado et al. (2011)

1.6 ± 0.6 Multiparous

1.9 ± 0.1 Anglo-Nubian F1 Mixed Trinidad Lallo et al. (2012)

1.6 ± 0.1 Anglo-Nubian F1 Mixed

1.7 ± 0.01 Black Bengal Mixed Bangladesh Halim et al. (2011)

2.0 ± 0.7 Black Bengal Mixed Bangladesh Hassan et al. (2007)

1.7 ± 0.1 Boer Mixed RIGP, Sungei Putih, Indonesia Elieser et al. (2012)

1.9 ± 0.3 Boerawa F1 Mixed Lampung, Indonesia Sulastri (2010)

1.9 ± 0.2 Boerawa BC1 Mixed

1.9 ± 0.2 Boerawa BC2 Mixed

1.4 ± 0.5 Boerka F1 Mixed RIGP, Sungei Putih, Indonesia Mahmilia and Elieser (2008)

1.2 ± 0.2 Black Bengal Mixed Bangladesh Hassan et al. (2007)

1.7 ± 0.3 Etawah Grade Mixed Lampung, Indonesia Sulastri (2010)

1.4 ± 0.5 French Alpine Primiparous Mexico Mellado et al. (2011)


1.7 ± 0.1 Mixed Georgia Amoah et al. (1996)

1.5 ± 0.5 Granadina Primiparous Mexico Mellado et al. (2011)


1.7 ± 0.6 Jamnapari Mixed Bangladesh Hassan et al. (2010)

2.0 ± 0.0 Kejobong Single Kejobong, Indonesia Sodiq and Haryanto (2007)

1.9 ± 0.0 Twin

2.1 ± 0.0 Triplet

1.6 ± 0.0 Average

1.3 ± 0.5 Saanen Primiparous Mexico Mellado et al. (2011)



1.5 ± 0.1 Saanen F1 Mixed Trinidad Lallo et al. (2012)

1.2 ± 0.1 Saanen F1 Mixed

1.4 ± 0.5 Toggenburg Primiparous Mexico Mellado et al. (2011)



In prolific species, the high level of competition between foetuses had a meaningful effect on

developmental capacity, survival rate of the foetus and individual growth rate of the animals born in

the litter and during the preweaning period (Nowak 1996; Perez-Razo et al. 1998; Mellado et al.

2000a; Nowak et al. 2000; Simsek & Bayraktar 2006; Simsek et al. 2007; Mahmilia & Elieser

2008). In other words, higher litter size was correlated with lower birth weight and higher losses of

young in goats during the first few days of life (Ruvuna et al. 1991; Menendez-Buxadera et al.

2003; Menendez-Buxadera et al. 2004). Stabilizing the variability of the size of the litter or even

decreasing litter size increased the birth weight and thus potentially decreased the loss of kids.

Eventually this improved the productivity of the dams (Menendez-Buxadera et al. 2003). Published

data on birth weights was reported from 1.7 to 5.0 kg in different genotypes of goats with

information about the type of birth, sex of kid, and body condition score of does under different



29


Table 2.12 A summary of published data on birth weights (kg) of different genotypes of goats with

information about the type of birth, sex of kid, and body condition score of does. Birth-weight (kg) Breed Type of birth Location Reference

LSM ± SE

3.4 ± 0.1 Alpine American Mixed Georgia, USA Amoah et al. (1996)

3.4 ± 0.1 Alpine French



4.7 ± 1.5 Anglo-Nubian Primiparous


3.1 ± 0.1 BCS=2.7 Guaiuba Farm Silva et al. (2011)

2.9 ± 0.1 BCS=2.0

2.6 ± 0.3 Female Brazil Freitas et al. (2004a)

3.3 ± 0.1 Mixed Georgia, USA Amoah et al. (1996)

2.9 Boerawa Female Tanggamus Regency Adhianto et al. (2013)

3.1 Male

3.2 Single

3.0 Twin

2.1 ± 0.5 Boerka F1 Mixed RIGP Sungei Putih Mahmilia and Elieser (2008)

1.7 ± 0.4 Creole Mixed Caribbean Menendez-Buxadera et al. (2003)

3.3 ± 0.1 Dairy crossbred Mixed Georgia, USA Amoah et al. (1996)

3.3 ± 0.0 India Kataktalware et al. (2004)

3.9 ± 1.2 Granadina Primiparous Mexico Mellado et al. (2011)


2.1 ± 0.0 Kacang Male Purwodadi Regency Sodiq et al. (2010)

1.9 ± 0.0 Female

3.9 ± 0.1 PE Low,

Medium

High

Level of milk

production of

PE does

Balitnak-Ciawi, Sutama et al. (1999)

3.4 ± 0.6

3.2 ± 0.7

2.8 ± 0.2 Saanen Female Brazil Freitas et al. (2004a)

3.1 ± 0.6 Female Brazil Ciffoni (1999)

3.3 ± 0.8 Male

2.8 ± 0.0 Mixed Thailand Bungsrisawat and Tumwasorn

(2011)

3.6 ± 0.1 Mixed Georgia, USA Amoah et al. (1996)



4.4 ± 1.5 Toggenburg Primiparous


3.9 ±0.2 Mixed Georgia, USA Amoah et al. (1996)

Positive relationships between litter size and age or parity of dams had been noted. Devendra and

Burns (1983) and Amoah et al. (1996) recommended to keep does up to their fourth and fifth

kidding only when does were about 5 to 7 years of age to maintain maximum litter size. Larger

litter size (higher than twins) did not necessarily mean higher individual productivity or more

economic benefits for the flock. Principal factors that influenced offspring production efficiency

appeared to be the balance between prolificacy of the dam and mortality in her young (Menendez-

Buxadera et al. 2004). Birth weight and potential growth rate of kids, therefore, were important

criterion for high survival rate (Nemeth et al. 2005; Nemeth et al. 2009; Gaddour et al. 2012).

Of some goat breeds reared in Indonesia, Kejobong does with the triplet type born kids had the

highest litter size i.e. 2.1 ± 0.0 goats (Sodiq & Haryanto 2007) while Boerka F1 does with mixed

type born kids had the lowest litter size i.e. 1.4 ± 0.5 kids (Mahmilia & Elieser 2008) (Table 2.11).

PE does that had low level of milk production gave the highest birth weight of 3.9 ± 0.1 kg (Sutama

et al. 1999) while Kacang female kids had the lowest birth weight i.e. 1.9 ± 0.0 kg (Sodiq et al.


30


2010) (Table 2.12). Of importance, there was little information available on the little size as well as

the survival rates of kids born in Bali Province.

2.2.7 Annual reproductive rate

Annual reproductive rate was defined as the number of kids weaned per doe of reproductive age per

year. Annual reproductive rate was more commonly measured by litter size at birth than litter size

at weaning (Sodiq et al. 2003; Sodiq & Tawfik 2003; Sodiq et al. 2004; Sodiq & Haryanto 2007;

Elieser et al. 2012; Adhianto et al. 2013). However, the latter was preferred as it took the mothering

ability of the dam into consideration.

Best practice mating management increased the productivity of goats as more does got pregnant and

produced kids. Setiadi et al. (1997) reported that mating does at the second oestrus after parturition

resulted in better (70%) conception rates than at the first oestrus (50%). This type of mating also

caused a better weaning weight of kids (16.4 kg) than those born from the first mating (11.8 kg) or

the third mating (12.9 kg), but birth weight (3.4 to 3.5 kg) was not affected by the timing of the

different matings. Furthermore, Setiadi et al. (1997) reported that when breeding management

included reducing the kidding interval from 11 to 12 months to 7 to 8 months, this significantly

increased the productive efficiency of goats and thus provided more economic benefits for

smallholder farmers.

Published data on doe productivity that was reported from 1.1 to 37.9 kg meat/doe/year in different

genotypes of goats with information about the type of birth, sex of kid, and parity of does under

different ecological and management conditions is summarized in Table 2.13.


31


Table 2.13 A summary of published data on doe productivity (kg meat/doe/year). Doe reproduction

(kg meat/doe/year)

Breed Type of birth Location Reference

18.12 Boer Mixed RIGP, Sungei Putih Elieser et al. (2012)

41.52 Boerawa Mixed Tanggamus Regency Adhianto et al. (2013)

1.41 Kacang Single Java Island, Indonesia Sodiq and Tawfik (2003)

2.98 Twin

4.58 Triplet

2.95 Mixed Grobongan, Indonesia Sodiq et al. (2003)

3.07 Purworeja, Indonesia Sodiq et al. (2004)

37.12 Kacang Mixed RIGP, Sungei Putih Elieser et al. (2012)

14.6a ± 0.3 Kejobong Single Kejobong, Indonesia Sodiq and Haryanto (2007)

31.3b ± 0.6 Twin

37.9c ± 4.4 Triplet

26.6 ± 0.8 Average

1.1 PE Single Java Island, Indonesia Sodiq and Tawfik (2003)

2.2 Twin

3.5 Triplet

1.8 Mixed Grobongan, Indones Sodiq et al. (2003)

1.6 Mixed Purworeja, Indonesia Sodiq et al. (2004)

1.9 Kacang 1st Parity Java Island, Indonesia Sodiq and Tawfik (2003)

2.3 2nd Parity

3.0 3rd Parity

3.8 4th Parity

3.3 5th Parity

2.7 6th Parity

23.6 ± 1.3 Kejobong 1st Parity Kejobong, Indonesia Sodiq and Haryanto (2007)

26.9 ± 1.6 2nd Parity

29.7 ± 1.7 3rd Parity

32.7 ± 2.8 4th Parity

31.3 ± 2.6 5th Parity

25.3 ± 4.4 6th Parity

22.9 ± 3.0 7th Parity

26.6 ± 0.8 Average

1.3 PE 1st Parity Java Island, Indonesia Sodiq and Tawfik (2003)

1.6 2nd Parity

1.9 3rd Parity

2.5 4th Parity

2.1 5th Parity

-- 6th Parity

2.3 Strengths, Weaknesses, Opportunities and Threats (SWOT) and Analytic Hierarchy Process

(AHP) analyses

SWOT analysis is a tool commonly used for strategic planning (Phadermrod et al. IN PRESS). The

tool is important for evaluating the current situation of goat rearing towards improving productivity

in Bali Province, Indonesia. The purpose of using this analysis is to provide comprehensive

documentation in determining their internal strengths and weaknesses as well as the external

factors, in order to develop the most suitable strategic planning. In the process, the SWOT analysis

lists all the strengths, weaknesses, opportunities, and threats to the farming operation and then

serves as a basis for the goat farm‘s business plans and thus provides directions for the goat farming

business. Smallholder farmers, stakeholders working in the goat industry and the local government

should use the benefits of strategic planning to sustain the development of their goat rearing sector

(Dubeuf et al. 2014; Ghorbani et al. 2015; Santopuoli et al. 2016).


32


The SWOT analysis is no doubt a valuable tool for creating future strategies. However, it has some

weaknesses in practice when it stands alone (Kurttila et al. 2000; Wang 2007; Ho 2008; Erdil &

Erbıyık 2015; Santopuoli et al. 2016). In order to overcome these weaknesses, the SWOT analysis

should be integrated with other decision-making tools, such as case studies, direct observations,

environment resources assessments, market assessments, managerial practices, structured formal

household interviews, meetings, key informant interviews and focus group discussions (Dubeuf et

al. 2014). The SWOT analysis should also be integrated with AHP (Saaty 1980; Ho 2008;

Santopuoli et al. 2016) or quantitative strategic planning matrix (QSPM) analysis techniques

(Ghorbani et al. 2015). All of the methods proposed will help in weighing all parameters involved,

as well as in analysing the situation more precisely. It also will help the decision makers in the

development strategies that strengthen the weak areas or take advantage of the strengths and

opportunities.

The AHP of Saaty (1980) is one of the most widespread and powerful methods for decision-

making, particularly when it was integrated with SWOT analysis (Wang 2007; Ho 2008; Wang et

al. 2014; Santopuoli et al. 2016). The AHP is generally used to derive priorities based on sets of

pairwise comparisons (Kurttila et al. 2000). The AHP approach is a multi-criteria decision-making

method that uses hierarchic or network structures to represent a decision problem and then develops

priorities for the alternatives based on the decision makers‘ judgments throughout the system. It

addresses the issues on how to structure a complex decision problem, identify its criteria, both

tangible or intangible, measure the interaction among them and finally synthesize all the

information to arrive at priorities, which depict preferences (Saaty 1980; Ho 2008; Wang et al.

2014; Santopuoli et al. 2016). A significant number of researchers provide evidence that applying

the integrated AHPs was better and more effective in aiding researchers and decision makers than

the stand-alone AHP (Ho 2008).

By applying the combined methodology, decision makers are able to list and to identify all the

farming operation‘s internal strengths and weaknesses as well as to examine the external

opportunities and threats in operating the farm goat business. The combined method gives an

overall look at the current position of the goat production operation, as well as offering possibilities

to assess the current gaps in improving goat production (Saaty 1980; Dubeuf et al. 2014; Ghorbani

et al. 2015; Bayram & Üçüncü 2016; Santopuoli et al. 2016).

In summary, this chapter provides basic information required to improve rearing goats under

smallholder production in Bali Province, Indonesia. The information describes a representative


33


example of the typical reproductive performance of goats under smallholder production systems in

the region. The reproductive performance indicators measured in this study present the current

situation of goat rearing as well as identify the factors influencing the efficiency of goat production

by smallholder farmers. Finally, the SWOT analysis, integrated with the AHP applied on the

current situation of goat production will be used to identify the most suitable management strategies

for sustainable improvement of goat production in Bali Province, Indonesia.

Chapter 3 General Research Design and Methods

34


Chapter 3

General Research Design and Methods.

3.1 Location and description of study sites

Bali Province consists of a capital city and eight regencies, namely: Denpasar, Buleleng,

Karangasem, Jembrana, Tabanan, Bangli, Klungkung, Gianyar and Badung (www.bmkg.go.id)

(BPS-Bali 2014) (Plate 3.1 and Table 4.1). Goat farmers exist in all regencies and all were

smallholder goat farmers. Preliminary studies showed that Buleleng, Karangasem and Jembrana

Regencies contributed about 86% of the total goat population of 68,457 goats in Bali Province

(BPS-Bali 2014). These three regencies were selected for more detailed study.

Plate 3.1 Map of Bali showing Karangasem, Buleleng and Jembrana Regencies that were selected

areas.

3.2 Sampling techniques

The livestock statistics for 2014 (BPS-Bali 2014) were referred to identify regency, district and

village as well as goat owning families with the largest goat populations. Buleleng, Karangasem

and Jembrana Regencies were selected as the study area because they contained 86% of the goat

population (BPS-Bali 2014). Jembrana Regency was officially promulgated a designation regency

for improvement of goat farming by the Indonesian Minister of Agriculture (Anonymous 2015d).

A purposive sampling procedure as described by Bryman (2016) was adopted to ensure that the

selected householders comprised of the goat farmers. A survey method based on a structured

questionnaire (Appendix 2) and direct observations were conducted to collect information needed in

this study. A total of 175 smallholder goat farmers with 2,017 goats were randomly selected and

involved in the study, of which, 63 farmers with 1,169 goats were in Karangasem Regency, 44

farmers with 590 goats were in Buleleng Regency and 68 farmers with 258 goats were in Jembrana

Regency. A random sample of regencies, districts, and villages, number of farmers or farms and

number of goats reared in Rendang, Banjar, Busungbiu, Grogak and Mendoyo Districts are shown

in Tables 3.1.


35


In addition, goat farmers that previously reared goats but no longer reared goats, particularly in

Mendoyo District, Jembrana Regency, were also randomly sampled to collect information about

their reasons for ceasing rearing goats. Their information was crucial for understanding the

constraints to, challenges of, and opportunities for improving goat production in Bali Province.

3.3 Period of data collection

The study was conducted over 12 months focussing on specific districts and a subsample of

smallholder farmers. Preliminary research was conducted in Buleleng Regency in September 2013

where 13 goat-owning families with 117 goats were recorded and measured in Sepang Kaja Village,

Busungbiu District. The fourth observation in Rendang District was the last observation that was

completed for Karangasem Regency on 30 September 2014. A Mecaru goat farm in Karangasem

Regency where all goats had all black coat colours was observed in December 2014. Timing of and

data collected during the study is shown in Table 3.1.

Table 3.1 Timing of and data collected during the direct animal observations in Bali Province. Description Time Regency District No. of farmers or farms No. of goats

Preliminary research 15th -30th Sep. 2013 Buleleng Busungbiu 13 117

1st Observation 1st -30th March 2014 Buleleng Banjar 7 103

Busungbiu 25 358

Grogak 12 129

1st Observation 3rd -30th June 2014 Jembrana Mendoyo 68 258

1st Observation 3rd -30th April 2014 Karangasem Rendang 42 735

2nd Observation 3rd -30th June 2014 Karangasem Rendang 63 1,169

3rd Observation 3rd -30th Aug. 2014 Karangasem Rendang 61 1,072

4th Observation 3rd -30th Sep. 2014 Karangasem Rendang 52 997

1st Observation 5th July 2014 Karangasem Rendang A Gembrong Conservation 25

1st Observation 6th December 2014 Karangasem Rendang A Mecaru goat Farm 53

Field measurements were based on two snapshots where the same animals were observed twice,

approximately 6 months apart (Figure 3.1). It did not work well on the second visit due to the

climate. Heavy rain destroyed the roads in the coffee plantations in Buleleng Regency.

Furthermore, by the second visit to Jembrana, some goats had been sold.


36


1st Snapshot

April – June

2nd Snapshot

Aug – Sep

Lactation

Status

Lactation

Status

Kid weaned or died (-)

New kid born (+)

Pregnancy

status

Pregnancy

status

Doe conceived (+)

Kid born (-)

Flock

number

Flock

number

New kids born or purchases (+)

Goats died or sold (-) Body

weight &

condition

Body

weight &

condition

Figure 3.1 Measurement of changes in goat flocks between the two snapshot observations six

months apart in Rendang District, Karangasem Regency, Bali Province.

3.4 Data collection and Questionnaire preparation

The primary and secondary data on goat rearing under smallholder production systems in Bali

Province was summarized from data collected from the Department of Husbandry and Agriculture

in Bali Province, Statistics Indonesia (www.bps.go.id) and the Department of Meteorology and

Geophysics (www.bmkg.go.id). The data was also collected through case studies, direct

observations, environment resources assessments, market assessments, managerial practices,

structured formal household interviews, meetings, key informant interviews and focus group

discussions collected as well as through structured questionnaire surveys.

The design of the questionnaire was based on questionnaires conducted on livestock systems and

from advice obtained from Bali Government officers and university experts in agricultural

extension. A preliminary questionnaire was tested in one local area in Sepang Kaja Village,

Buleleng Regency where 13 goat farmers with 117 goats were interviewed. This preliminary

questionnaire was undertaken to ‗road test‘ the questions and to gain experience in conducting

questionnaires. Data collected during the preliminary questionnaire were analysed. Subsequently,

the preliminary questionnaire was modified and the actual questionnaire used in this study is

presented in Appendix 2.

Daily data collection from questionnaires or from direct measurement of goats, were directly

computed, and checked for their accuracy at night, particularly for extreme and blank data. The

extreme and blank data, particularly on biological measurements and reproductive parameters of

goats were re-measured and completed on the following day. Checking the accuracy of the data

from household labourers and their profiles, goats and their profiles, the roles of goats in Hindu

ceremony, and the roles of farmer groups, the economic factors in goat rearing activities, the

surrounding resources assessment and market assessment were re-done at the end of data collection

in the particular area. All this was re-checked through formal household interviews, meetings, and

http://www.bps.go.id/

http://www.bmkg.go.id/


37


key informant interviews as well as focus group discussions. This included checking the number

and prices of goats sold; and the number, items and prices of input and output parameters in goat

rearing activities.

Data noted in the questionnaire were obtained largely based on the goat owner‘s recall and the

interviewer‘s observation and assessment of what was said. Where possible, other family members

who were also responsible for the goats were interviewed to confirm the owner‘s information.

The questionnaire was designed to gain information on the aspects listed below:

(1) General information about the farmer‘s profiles;

(2) General information about the goats;

(3) Goat breeding and reproduction;

(4) Goat management and nutrition;

(5) Goat health and disease;

(6) The role of farmer groups;

(7) Marketing of goats and goat products;

(8) The role of the goat in Hindu ceremonies; and

(9) The constraints, challenges and opportunities faced in rearing goats under smallholder

production systems.

In addition, morphometric measurements were taken directly from the farmer‘s goats. Each goat in

this study had its own identification card and measured for their live weight and body

measurements.

Parameters measured included:

a. Household labourers and their profiles

The information on each smallholder farmer‘s profile i.e. their age, education level, family

labourers per household, skill or training courses taken, rearing management applied from their

knowledge, attitude, practices, skills and creativeness, as well as their use of natural resources in

rearing goats was checked by related family members. In addition, members of goat farmer

association through case studies, formal household interviews, meetings, key informant interviews

and focus group discussions also checked the information on each smallholder farmer‘s profile.

b. Basic information about the goats and their profiles

Breed-types were defined by breed standards as differences in colour, ear size and type, horn

size and type, face type, hair coat length, presence of beard, and or wattles, bodyweight, and

height in adult males and females (Devendra & Haenlein 2011).


38


Sex, age, and dentition status (I0, I1, I2, I3, I4, toothless) (Kunz et al. 1996). Approximate ages

of kids were estimated from their dentition status (based on eruption of their incisors of goats

reared in Indonesia) (Sulastri & Sumadi 2005) while their birth dates were estimated by using

the farmer‘s data and recordings during the observations in 2014. Body condition and the size

of dam‘s mammae (udder) or date of post-partum mating confirmed birth dates. The state of

the umbilicus also aided in the estimation of age of very young kids (Kunz et al. 1996).

FAMACHA©

score (Ejlertsen et al. 2006).

Parity of does (Sodiq & Haryanto 2007; Mahmilia & Doloksaribu 2010)

Bodyweight (BW, kg) were measured in the morning before feeding goats by using a Shelter©

scale which had an accuracy to 0.1 kg.

Body length (BL, cm) referred to the distance from the base of the ear to the base of the tail

(where it joins the body). Extreme care was taken to ensure that the backbone was straight in

both vertical and horizontal planes. All the measurements of body length were taken to the

nearest 0.5 cm.

Chest circumference (CC, cm) or hearth girth is a circumferential measurement taken around

the chest just behind the front legs and withers.

Chest depth (CD, cm) was measured from the backbone at the shoulder (standardized on one

of the vertical processes of the thoracic vertebrate) to the brisket between the front legs.

Height at withers (HW, cm). This measures records the distance from the surface of a

platform on which the animal stands to the withers. The measurement was made with a special

measuring stick made with two arms one which was held vertical and the other at right angles

to it sliding firmly up and down to record height.

Rump height (RH, cm) is the distance from the surface of a platform on which the animal is

standing to the rump using a measuring stick as described for height at withers.

Ear‘s size such as Short, Medium and Long as well as floppy or erect ear‘s type and the

colours of the goat‘s ears were recorded.

c. Reproductive performance and productivity of the goats

As farmers had no recorded data, the animal‘s birth date, or dates that animals were mated, or dates

and type of kidding, were from the farmer‘s recall. Farmers recall was assessed as being accurate

due to the small flock size and close association between goats and their owners. The remaining

data was recorded as the result of direct animal observations or calculations such as determining the

precise stage of pregnancy, or lactation status, or mortality rate or the body conditions of goats.


39


Lactation status. Visual observations and massage of the udder of does was used to determine

if goats were lactating. The presence of suckling kids with the does also indicated lactation

status (Devendra & McLeroy 1982; Peacock 1987, 1996).

Pregnancy status. Pregnancy status was estimated from the farmer‘s recall of when the last

date does were mated. The absence or presence of kids with the does also indicated the doe‘s

pregnancy status (Devendra & McLeroy 1982; Peacock 1987, 1996).

Month of kidding. Month of kidding was recorded by direct animal observation if it occurred

during the study and from household interviews when it occurred outside the study period. The

presence and size of kids with the does also indicated the month of kidding (Devendra &

McLeroy 1982; Peacock 1987, 1996).

Age at first kidding (months). Age at first kidding was calculated using the month of birth for

the goat and date of first kidding based on the farmer‘s recall (Devendra & McLeroy 1982;

Peacock 1987, 1996).

Kidding rate. Kidding rate or percentage is defined as the number of kids born per 100 does of

reproductive ages that were mated per year (Devendra & McLeroy 1982; Peacock 1987, 1996).

Weaning rate. Weaning rate or percentage is defined as the number of kids weaned per 100

does of reproductive ages that were mated per year (Devendra & McLeroy 1982; Peacock

1987, 1996).

Kidding interval. Kidding interval (months) was calculated as the time between the two most

recent parturitions (Devendra & McLeroy 1982; Peacock 1987, 1996).

Kid mortality. Kid mortality was determined from information provided by farmers and by

examination of the status of the udder of goats. Kids were defined as animals that had reached

the weaning period. Kid mortality was defined as the percentage of kids that died between

birth and weaning (Devendra & McLeroy 1982; Peacock 1987, 1996).

Month of kid mortality. The month of kid mortality was determined from information

provided by farmers and examination of the udder of goats that were producing milk without

the presence of a kid (Devendra & McLeroy 1982; Peacock 1987, 1996).

Turn off rate. Turn off rate, where the numerator is the total number of animals turned off in a

year (this includes animals consumed by the farmer). The denominator is the total number of

animals in the flock or population. This is usually expressed as a percentage.

d. Rearing management

The rearing management of goats in small farm systems are closely associated with the type of

production system that influences their productivity (Devendra 1986, 1988). Information noted in

this section includes:

Type of rearing systems,


40


Type of housing systems,

Types of feed and feeding systems, and

The breeding and management systems they applied (Appendix 2).

e. Socio-economic parameters

Socio-economic parameters are measured by the ratio of value of output from to value of input into

goat rearing and their relationship (Knipscheer et al. 1984). Information noted in this section

includes:

Sale of animals is in Indonesian Rupiah (IDR) per 100 animals or per flock, or per village per

year.

Gross income is IDR per 100 animals or per flock, or per village per year.

Gross margin (Total income - Total variable costs) analysis is carried out using the system

described by NSW Department of Primary Industries Farm Enterprise Budget Series – July

2006 (Anonymous 2004a). Gross margin analysis is a method of integrating all of these

parameters that were calculated as:

Gross Margin (A-B) or GM(A-B) (IDR million) = Total Income (IDR million) - Total Variable

Costs (IDR million). This was calculated for each flock/household.

Gross Margin per doe or GM/doe is the GM(A-B) per flock divided by the number of does in

the flock.

Total income from sale of all animals (including personal consumption), milk and manure

Variable costs from purchase of replacement animals, medicines, fodder, labourer and

marketing costs.

f. Inputs into, outputs from goat rearing and their relationships

The economic factors associated with goat rearing were recorded through case studies, formal

household interviews, meetings, key informant interviews and focus group discussions. The

number, items and prices of input and output parameters in these goat-rearing activities were

collected. The inputs included feeds, veterinary services, drugs, and labour cost i.e. labourers (from

the family). The outputs obtained included sales of live animals, milk and milk products, manure or

goat products consumed at home which were then converted into cash (IDR million). IDR 1

million was equivalent to AUD$100.00.

The information on goat rearing contributing to annual household income was calculated and

computed for the gross margin analysis. The gross margin analysis was calculated for each

household. Information about the surrounding environments to establish baseline information about

the goat‘s productivities was also collected.


41


g. Assessing current goat rearing towards improving productivity in Bali Province, Indonesia.

The goat productivity is assessed through a hybrid method of SWOT and AHP analyses (Kurttila et

al. 2000; Ho 2008; Bayram & Üçüncü 2016; Santopuoli et al. 2016).

3.5 Statistical analysis

The effect of sex of the goats, their birth type, parity, birth season, flock size, age, dentition status,

FAMACHA©

score, the research site, and housing system on the goats bodyweight were analysed

by Least-squares methods using the General Linear Model Multivariate Model procedure (GLM) of

SPSS version 24 (SPSS-Institute 2014). The relationships between goats‘ bodyweight and other

factors were established using linear regression analysis while correlations between bodyweight and

other factors were computed by using SPSS version 24 (SPSS-Institute 2014). The live weights of

goats from birth to weaning was analysed by fitting a separate linear regression model of live

weight on the age of each kid, then analysing the regression coefficients by analysis of variance.

The sources of variation considered were group; sex; group dentition i.e. I0, I1, I2, I3, I4 and

toothless; multiple birth rate; parity; and research sites (regencies) i.e. Buleleng, Karangasem and

Jembrana with the continuous measurements of body dimensions as well as the indicators of

reproductive performance and productivity of goats reared in Bali Province.

The financial analysis determined the economics of rearing goats by different farmers. Estimations

of economic efficiency i.e. kids weaned per year per doe of breeding age (or per 100 does); kg meat

(or litre milk) produced per goat per year (or per 100 goats); total value ($USD) of all products

produced by the flock per year per total value of the flock ($USD); and turn off rate. Farmers were

ranked based on these estimates of efficiency and data from the top 20% were compared to the

bottom 20% of the farmers. Data was analysed to identify the factors that contributed to this

ranking.

Data generated were analysed using descriptive statistics (frequency distribution and mean) and

budgetary analysis were carried out using the system described by the NSW Department of Primary

Industries Farm Enterprises Budget Series – July 2006 (Anonymous 2004a). Descriptive statistics

were used to describe the socio-economic characteristics of the respondents (goat farmers). The

budgetary analysis was used to estimate the costs and returns of producing goats. This involved the

determination of the total income per flock, which was the difference between the gross revenue

and total costs. Total costs included fixed costs, which did not alter the type or number of animals

(i.e. rates and land tax), plus variable costs (i.e. feeds and medicines) that vary with the number of


42


animals. Further substantiative analysis, i.e. the profitability of this enterprise, and gross margin per

doe per year were also analysed.

GM/doe was calculated for each flock. All the flocks in the regency or district under consideration

were then arranged in order or merit, the highest GM/doe first, and the lowest GM/doe last. The top

20% of flocks were then compared with the bottom 20% of flocks to determine what management,

genetic, or environmental factors were associated with this difference in GM/doe performance. The

GM/doe analysis were calculated for each flock in every regency i.e. Karangasem, Buleleng and

Jembrana Regency and finally, all the 175 GM/doe analysis was arranged in order or merit, the

highest GM/doe first, and the lowest GM/doe last for Bali Province.

Current goat rearing aimed at improving goat productivity in Bali Province was assessed with a

hybrid method that was composed of SWOT and AHP analyses to achieve optimal use of the

opportunities and control of threats (Kurttila et al. 2000; Ho 2008; Bayram & Üçüncü 2016;

Santopuoli et al. 2016). The primary and secondary data on goat rearing under smallholder

production systems in Bali Province was summarized from various data resources. The combined

data were analysed by using descriptive statistics, correlate bivariate and general linear model

multivariate analyses using SPSS version 24.

The strengths and weaknesses of the current reproductive and productive efficiency of goat farming

under smallholder production systems in Banjar, Busungbiu, Grogak, Mendoyo and Rendang

Districts in Bali Province, as well as their socio-economic analysis and their opportunities and

threats originating from each district, were determined using the SWOT matrix. The information

obtained from the SWOT matrix was integrated into the AHP hierarchy to identify the most

important factors in each district as well as the optimum strategies for improving goat production

(Kurttila et al. 2000; Ho 2008; Bayram & Üçüncü 2016; Santopuoli et al. 2016).

3.6 Animal and Human Ethics Approvals

The University of Queensland Animal and Human Experimentation Ethics Committee, in

agreement with the Australian National Health and Medical Research Council guidelines under

approval numbers SAFS/A52/13 and SAFS/H13/19, respectively, approved the research conducted

in this study.

Chapter 4 Goat production systems in Bali Province, Indonesia: An Overview

43


Chapter 4

Goat production systems in Bali Province, Indonesia: An Overview

4.1 Introduction

Identifying the background such as the environment, livestock, managerial as well as the roles of

Indonesian Government helped in improving the goat productivity under smallholder production

systems in Bali Province. Hindu Balinese families have a strong family bonding with sesuhunan or

their great ancestors as an ―intangible heritage‖ in the form of keeping family‘s rules, rituals and

ceremonies. This intangible heritage is bonded with the family‘s property, such as the family‘s

temple, house, rice field, farm or other family‘s belongings (Sudarsana 2001). Therefore, unlike

farmers in Java Island (Budisatria et al. 2007; Suranindyah et al. 2009a; Suranindyah et al. 2009b),

most of Hindu Balinese farmers will always have their own property to grow crops or rear livestock

(Nitis 1997; Nitis et al. 2004). Furthermore, traditional crop-livestock farming in Bali is

environment orientated based on the Tri Hita Karana concept, a traditional philosophy for life on

the island of Bali for ―three causes of well-being‖ or ―three reasons for prosperity‖. The concept

emphasis that the well-being of human is achieved when life has an harmony between people,

nature or environment, and God (Nitis et al. 2004). The objective of this chapter is to overview of

goat production systems in Bali Province and investigates the potential benefits and limitations to

village goat production could be used for the improving of their productivity.

4.2 Study sites

Bali Province is situated between 803‘40‖ to 8

050‘48‖ south and 114

025‘53‖ to 115

042‘40‖ east

with 24 mountains ranging in height from 310 to 3,142 m a.s.l. Bali Island experiences a range of

temperatures between 19 and 27.50C, relative humidity of 68 to 93%, annual average rainfall of

1,182 to 4,857 mm and average wind velocity of 3 to 9 knots (Bali Meteorology Biro 2015)

(www.bmkg.go.id). The area, geographic location, average annual temperature, relative humidity,

rainfall, and wind velocity of each regency and city in Bali Province is described in Table 4.1.



44


Table 4.1 Regency/city, area, geographic location, average annual temperature, relative humidity,

rainfall and wind velocity of Bali Province in 2014 (www.bmkg.go.id). Regency/city Geographic location Area

(km2)

Average annual

Temperature

(0C)

Humidity

(%)

Rainfall

(mm)

Wind velocity

(knot)

Denpasar 8036‘56‖ – 8042‘01‖ S 127.8 27.3 81 2,026 7

115010‘23‖ – 115016‘27‖ E

Klungkung 8027‘37‖–8049‘00‖ S 315 26.9 85 1,957 6

115021‘28‖–115037‘28‖ E

Gianyar 8018‘48‖–8038‘58‖ S 368 25.6 80 2,381 6

115013‘29‖–115022‘23‖ E

Badung 8014‘01‖–8050‘52‖ SL 418.5 26.9 81 1,849 6

115005‘03‖–115026‘51‖ EL

Bangli 8008‘30‖–8031‘07‖ S 520.8 23.8 68 1,947 7

115013‘43‖–115027‘24‖ E

Tabanan 8014‘30‖–8038‘7‖ S 839.3 19.7 93 4,857 5

114059‘00‖–115002‘57‖ E

Karangasem 8033‘07‖–8010‘00‖ S 839.5 26.7 77 1,428 9

115023‘22‖–115042‘37‖ E

Jembrana 809‘58‖–8028‘2‖ S 841.8 26.2 83 1,721 3

114026‘28‖–115051‘28‖ E

Buleleng 803‘40‖–8023‘00‖ S 1,365.9 27.5 75 1,182 7

115025‘55‖–115027‘28‖ E

Bali 803‘40‖–8050‘48‖ S 5,636.7

114025‘53‖–115042‘40‖ E

BPS-Bali (2014) S=south latitude and E=east longitude

Bali Province has a tropical climate comprised of two seasons, a dry season (May - September) and

a rainy season (October - April). Average monthly rainfall of Karangasem, Buleleng and Jembrana

Regencies contributed to the total rainfall of Bali Province (Figure 4.1).

(www.bmkg.go.id)

Figure 4.1 Monthly rainfall (mm) in Buleleng, Karangasem and Jembrana Regencies (Bali

Province) recorded in 2014.

Karangasem Regency is situated 08033‘07‖ to 08

010‘00‖ south and 115

023‘22‖ to 115

042‘37‖ east

with average temperatures between 19 to 27.5 0C, and annual average relative humidity of 77%,

total annual rainfall of 1,428 mm and average wind velocity of 9 knots (www.bmkg.go.id). The wet

season occurs during the months of November (106 mm), December (851 mm) and January (343

mm) while little or no rain falls during the months May (75 mm) to October (75 mm). In contrast,




45


monthly rainfall in Bali Province was more stable ranging from 40 to 90 mm per month during this

study (www.bmkg.go.id) (Figure 4.1).

Buleleng Regency stretches across almost all of the northern part of Bali. It borders on Karangasem

Regency in the east; Jembrana, Tabanan, Badung, and Bangli Regencies in the south; Jembrana

Regency in the west; and the Java/Bali Sea in the north (Plate 3.1). Buleleng Regency is situated

08003‘40‖ to 08

023‘00‖ south and 115

025‘55‖ to 115

027‘28‖ east with an average temperature of

28.7 0C, annual average relative humidity of 75%, total annual rainfall of 1,182 mm and an average

wind velocity of 7 knots (Table 4.1) (www.bmkg.go.id). Little rain falls in July (26 mm), August

(26 mm), September (30 mm), October (30 mm), and November 2014 (36 mm) in Buleleng

Regency. The wet season occurs during the months of December (400 mm), January (403 mm),

February (333 mm), March (191 mm) and May (151 mm). In contrast, monthly rainfall in Bali

Province was more stable ranging from 40 to 90 mm per month during this study

(www.bmkg.go.id) (Figure 4.1).

In Bali Province, the largest amount of rainfall occurred in December 2014 and gradually decreased

in January 2014 until March 2014; and in contrast, the smallest amount of rainfall was in September

2014. The monthly rainfall (mm) in Karangasem Regency fluctuated and became the largest

amount that contributed, with Buleleng and Jembrana Regencies, to the total rainfall of Bali

Province during this study. It was 343 mm in January 2014 and then it gradually decreased to 70

mm in May; and no rainfall occurred in June, September, and October and then it increased to 100

mm in November before it reached the peak of 851 mm in December. The rainfall in Buleleng and

Jembrana Regencies were intermediate and contributed to the total rainfall of Bali Province. No

rainfall occurred in June, August, September and October 2014 in Buleleng Regency while

Jembrana Regency had no rain except in September 2014 (Figure 4.1).

Although Buleleng, Karangasem and Jembrana Regencies had similar natural resources, the

management and environment where goats were reared were slightly different. Most goat farming

in Buleleng Regency, particularly in Busungbiu District was in the area around coffee (Coffea spp.)

and cacao (Theobroma cacao) plantations (Elisabeth 2012; BPS-Bali 2015). Banjar District was

located at the base of Abang Mountain where farmers grew vegetables or fruits integrated with goat

rearing (BPS-Bali 2015) (Tables 4.5 and 4.6). Grogak District was located in coastal areas in the

zone designated West Bali National Park (Surata et al. 2014). In Karangasem especially in

Rendang District where the study was conducted goat farming was mostly associated with

vegetable farms and the farmers had accesses to nearby conservation forest for fresh roughages for





46


their goats. Goat farming in Jembrana Regency especially in Mendoyo District where the study was

conducted represented an area of goat farming, which was integrated with coconut, coffee, clove

and cacao plantations. This district was a designation regency for improvement of goat farming that

was officially promulgated by the Indonesian Minister of Agriculture (Anonymous 2015d).

Therefore, results of the studies from Rendang, Busungbiu, Banjar, Grogak and Mendoyo Districts

in these three regencies were analysed and reported in different chapters.

Bali Province consists of a capital city and eight regencies, namely: Denpasar, Badung, Gianyar,

Klungkung, Bangli, Buleleng, Karangasem, Jembrana and Tabanan (Plate 3.1). Regencies are made

up of districts, districts are divided into villages, and villages consist of area units (Table 4.2).

Table 4.2 Regency/city, number of districts, villages, human population, number of goats, area and

density of the human population and goats in Bali 2014. Regency/city Number of : Area (km2) Density/km2

Districts Villages Population Goats Population Goat

Denpasar 4 43 880,600 491 127.78 6,892 4

Gianyar 7 70 495,100 685 368.00 1,345 2

Badung 6 62 616,400 807 418.52 1,473 2

Klungkung 4 59 175,700 946 315.00 558 3

Bangli 4 72 222,600 1,291 520.81 427 3

Tabanan 10 133 435,900 5,009 839.33 519 6

Jembrana 5 51 271,600 7,735 841.80 323 9

Karangasem 8 78 408,700 19,280 839.54 473 23

Buleleng 9 148 646,200 32,213 1,365.88 457 24

Total in 2014 57 716 4,152,800 68,457 5,636.66 737 12

Source: BPS-Bali (2015)

The goat density and the ratio of goats to humans in Bali island was 12 goats/km2 and 16

goats/1,000 people in 2014 (BPS-Bali 2015) (Table 4.2). Bali Province had 4.225 million people in

2014, covered area of 5,636 km2 and the goat density was 375 times smaller compared to sheep

density in New Zealand i.e. 6 sheep per person where it had 4.471 million people in 2014, covered

area of 268,021 km2 of New Zealand. New Zealand had 22 sheep per person in 1982

(www.stats.govt.nz).

4.3 The distribution of goats in Bali Province

The major livestock reared in Bali were pigs, Bali cattle, goats and buffalo (Table 4.3) and their

populations have fluctuated and gradually decreased over the last 10 years (BPS-Bali 2015). No

sheep were reported in Bali in 2014 and horses contributed to less than 1% of the total livestock

population in Bali in 2014 (BPS-Bali 2015).

The Indonesian Minister of Agriculture‘s Decree officially promulgated Jembrana and Tabanan

Regencies were designation areas for improving goats production (Anonymous 2015d). Therefore,


47


the Planning, Development and Financial Programmes have focused on improving goat production

in both regencies. Decades ago, however, the largest goat population in Bali Province was in

Jembrana Regency, although in 2014, this regency only had 11.3% of the total Bali goat population;

while Tabanan has less than 10% of the goat population (BPS-Bali 2015). Reasons for the

reduction of total goat population in Jembrana Regency were not clear. This made it challenging to

establish the current database as well as strategies for future development.

Table 4.3 Population of livestock by regency/city and type of livestock in Bali in 2014 and

designation areas. Regency/City Goats Bali cattle Pigs Buffaloes Designation areas in 2015*

Denpasar 491 7,241 16,251 3 Pig

Gianyar 685 46,861 128,597 0 Pig

Badung 807 37,862 82,479 0 ---

Klungkung 946 37,250 27,272 16 Bali cattle

Bangli 1,291 75,164 63,876 0 Pig

Tabanan 5,009 52,916 94,537 275 Goat

Jembrana 7,735 52,306 64,998 1,101 Goat

Karangasem 19,280 122,369 147,079 37 Bali cattle

Buleleng 32,213 121,613 196,497 134 Bali cattle

2014 68,457 553,582 821,586 1,566

2007 74,322 633,789 879,740 6,598

Source: BPS-Bali (2015). *Anonymous (2015d)

Although Tabanan has never been one of the top three largest goat population, this regency had the

potential to support the larger goat population as it has the topography as well as the area and the

production yield of farm commodities (Tables 4.4 and 4.5) to support more goats. The land in

Tabanan Regency had an abundance of vegetation and crops that provided AIBP as livestock feeds

for goats.

Table 4.4 Population of goats, goats slaughtered and goat meat produced (tonne) by regency/city,

and genotype and sex of goats in Bali in 2014. Breed of goats Total

goats

Goats

slaughtered

Goat meat

produced

(tonne) City/Regency Kacang PE

Female Male Total Female Male Total

Denpasar 10 7 17 295 179 474 491 25,775 386.63

Gianyar 164 109 273 226 186 412 685 10,719 160.79

Badung 33 13 46 570 191 761 807 4,880 73.20

Klungkung 165 66 231 519 196 715 946 4,166 62.49

Bangli 283 100 383 586 322 908 1,291 5,332 79.98

Tabanan 342 181 523 2,446 2,040 4,486 5,009 32,769 491.54

Jembrana 980 513 1,493 3,869 2,373 6,242 7,735 26,493 397.40

Karangasem 9,859 4,610 14,469 3,076 1,735 4,811 19,280 4,676 70.14

Buleleng 3,796 2,396 6,192 16,832 9,189 26,021 32,213 17,214 258.21

Total in 2014 15,632 7,995 23,627 28,419 16,411 44,830 68,457 132,024 1,980.38


Goat population in Bali has fluctuated within a range of above 65 thousand to 75 thousand goats for

the period 2009 to 2014. The average of growth rate of goat population in Bali Province was 9%


48


during the periods. Buleleng, Karangasem, Jembrana and Tabanan Regencies were the top four

regencies that contributed above 90% of the total goat population in Bali during the period 2009 to

2014 (BPS-Bali 2015).

The goat population peaked in 2009 and in 2011 with about 75 thousand goats and the lowest

number was in 2014 with 68.5 thousand goats, this decreased to 9%. Reasons for the reduction of

total goat population were little known whether it was due to high demand of goats that slaughtered

high number of goats or the low productivity of goat rearing in Bali Province. This made it

challenging to establish the current database as well as strategies for future development.

In 1981, 1,140 females and 160 males were the first of the PE, Kacang and Benggala goats

introduced to Bali. Then the second and the third introductions were in 1986 and 1987 when each

year 900 females and 100 males were imported into Bali (Mantra 1991, 1994). The average

increase in the number of goats, up to the year 1990 was 2.1% annually (Anonymous 1990).

However, the Ministry of Animal and Livestock of Bali Province had officially reported only the

Kacang and PE goats were in Bali (BPS-Bali 2015).

Indonesian Government statistics (BPS-Bali 2015; BPS-Indonesia 2015) reports had no data on goat

milk production or on goat meat/milk products in Bali. Although goats observed by The University

of Udayana Bali could produce up to 1.6 litres per goat per day when goats were supplemented with

concentrate (Table 2.4). Only the Ministry of Agriculture and Livestock of Bali Province presented

data on the number of Kacang and Peranakan Etawah (PE) goats in regencies in Bali (BPS Bali

2015) (Table 4.4). However, all 175 smallholder goat farmers studied in Rendang, Banjar,

Busungbiu, Grogak and Mendoyo Districts, Bali Province reared 2,017 goats that were a mixture of

Gembrong, Benggala, Kacang, Etawah Grade, PE, Boer, Boerawa and their crossbreds or

backcrosses (Chapters 5, 6 and 7 and Plate 2.1). No pure Kacang goats as described by Devendra

and Burns (1983) having erect short sized ears, were found in Bali Province during the data

collection. All goats observed had short or long floppy ears of various lengths and widths. This

finding could be a correction to the annual report of the Ministry of Agriculture and Livestock of

Bali Province (2015) and BPS-Bali (2015) (Table 4.4). In addition, the annual reports did not

mention that Bali Government had clear goals for the goat industry.

Prospects for development of goat production are promising in Bali Province due to the abundance

of feed resources and increasing market demand (Tables 4.4, 4.5 and 4.6). Large numbers of goats

were imported to Bali, particularly from NTB through Padang Bay Harbour and East Java through


49


Gilimanuk Harbour (Liestyawati, N. M. 2014, pers. comm. 11 April). This high demand of goats

was shown by 132,024 slaughtered goats while the total goats population was 68,457 in 2014 were

slaughtered in Bali during 2014 (BPS-Bali 2015) (Table 4.4).

4.4 Agricultural systems in Bali Province

The agricultural sector was the second largest after tourism sector contributed to the economics of

Bali Province. The total working aged 15 years and above in Bali Province in 2014 was 3,092,880

people where 1,546,498 were male and 1,546,382 were female while the economic growth of Bali

Province was 6.72% in 2014 (BPS-Bali 2015). Of the 3.093 million people, 1.243 million people or

40% were unskilled workers who had the lowest level of education i.e. Primary School or Grade 1-6

and 528,500 people or 52.5% of the unskilled workers worked in agriculture sector in Bali Province

in 2014 (BPS-Bali 2015). Meantime, there were 195,950 poor people in September 2014 that

increased from 185,200 poor people in March 2014 when the regional minimum wage of Bali

Province was IDR 1.321 million per person per month. Therefore, attempts to improve goat

productivity in Bali province will improve the economy of smallholder goat farmers thus the

economic growth of Bali Province. This was in agreement with many experts (Devendra 2001;

Devendra & Chantalakhana 2002; Santosa 2004; Peacock 2005; Devendra & Liang 2012) who

advocated sustainable improving the productivity of goats reared by smallholder goat farmers as a

means of improving the quality of life in developing countries.

The major agricultural commodity in Bali Province was coconuts (Cocos nucifera) with a total

production of about 74 thousand tonnes in 2014, and it was followed by coffee (Coffea spp.), cloves

(Syzygium aromaticum), cacao (Theobroma cacao) and cashew nuts with total productions of

approximately 18 thousand, 7 thousand, 6.6 thousand and 2 thousand tonnes, respectively. The area

of land used and the quantity of plants produced was almost linear except for cacao and cloves

(Table 4.5).

Paddy (rice) was one of the major crops produced with 858 thousand tonnes in 2014. Its production

yield was followed by cassava with 132 thousand tonnes, then sweet potato and maize of 54.4 and

40.6 thousand tonnes, respectively (Table 4.6). Tabanan Regency had the largest paddy production

(25%) in Bali Province as well as the largest farm commodity area (24%) and their production

yields (22%) were also found in this regency (Tables 4.5 and 4.6).


50


Table 4.5 Farm commodities, total area (ha), and their production yield (tonne) by regencies in Bali,

in 2014. Coffee Cacao Cashew nut Clove Coconut Tobacco

Regency/City Farm commodities Arabica Robusta

Denpasar Area (ha) 0 0 0 0 0 160 0

Production (tonne) 0 0 0 0 0 58.50 0

Badung Area (ha) 1,413 396 606 47 275 2,734 0

Production (tonne) 626.02 192.26 185.67 32.02 28.05 2,539.25 0

Gianyar Area (ha) 156 252 326 0 152 4,638 296

Production (tonne) 48.37 158.42 138.73 0 43.92 3,831.70 282.99

Klungkung Area (ha) 0 63 54 617 345 3,634 0

Production (tonne) 0 37.55 35.70 14.80 132.00 2,492.13 0

Bangli Area (ha) 6,558 296 257 0 202 2,944 26

Production (tonne) 2,338.39 156.81 140.33 0 38.19 2,957.71 16.19

Buleleng Area (ha) 2,767 10,745 1,279 2,162 7,752 8,971 334

Production (tonne) 554.24 8,468.49 759.54 369.45 5,270.75 9,061.24 629.31

Karangasem Area (ha) 1,067 608 1,066 9,485 890 24,234 10

Production (tonne) 226.79 267.35 183.87 1,554.74 272.49 14,348.86 3

Jembrana Area (ha) 0 1,217 6,257 0 3,447 17,333 4

Production (tonne) 0 275.73 3,000.32 0 785.36 19,847.47 8.32

Tabanan Area (ha) 914 9,602 4,625 0 2,651 15,810 0

Production (tonne) 9.23 4,557.17 2,131.09 0 503.49 18,919.20 0

Total Area (ha) 3,803.03 14,113.77 6,575.27 1,971.01 7,074.25 74,056.06 931.49

In 2014 Production (tonne) 12,876 23,179 14,468 12,312 15,714 80,458 670


Tabanan (24%), Buleleng (22%), Karangasem (20%) and Jembrana (18%) were the top four largest

areas for farm commodities as well as for their production yield, i.e. 22%, 19%, 22% and 22%, for

the four regencies, respectively (Tables 4.5 and 4.6). The other regencies and Denpasar City had

farm commodity areas, as well as their production yields, at about 5% or less. However, Tabanan

(7%) and Jembrana (11%) Regencies had much fewer goats compared to Buleleng (47%) and

Karangasem (28%) of the total goats in Bali Province (Table 4.4). The total population of goats in

Tabanan Regency has always been less than in Jembrana, Karangasem and Buleleng Regencies.

Table 4.6 Production (tonne) of commodities by regency/city in Bali in 2014. Regency/City Paddy Corn Cassava Sweet potato Peanuts Soybeans Mungbeans

Denpasar 24,952 31 0 0 0 449 0

Badung 109,148 126 4,828 12,963 903 1,219 1

Gianyar 186,526 724 2,910 2,661 168 1,467 23

Klungkung 32,064 5,038 9,243 2,558 882 976 31

Bangli 29,208 4,240 11,336 21,457 923 11 0

Buleleng 133,447 18,339 14,157 84 1,199 43 423

Karangasem 66,116 9,885 88,168 14,062 4,176 90 331

Jembrana 62,278 102 375 0 63 3,248 132

Tabanan 214,204 2,128 870 610 41 684 0

Total in 2014 857,944 40,613 131,887 54,395 8,355 8,187 941


The area of Tabanan Regency can be divided into two i.e. the first area is located on 0 to 500 m

a.s.l. that is used to grow paddy and this has a border to the south with Badung Regency (Table 4.1

and Plate 3.1). The second area is located to the north that has a border with Buleleng Regency that

is about 500 to 1,000 m a.s.l. and is commonly used to grow farm commodities. Buleleng,

Karangasem and Jembrana Regencies are located mostly on 500 to 1,000 m a.s.l. and were planted


51


with farm commodities and most goats were reared in these regencies. In future, Tabanan Regency,

as mentioned in The Minister of Agriculture‘s Decree on national designation areas for goats, has

the potential to increase the number as well as the quality of goats in this regency.

Although Bali Province had a large livestock population (Table 4.3), and abundant agriculture

industry by-products (AIBP) produced from the various plant production commodities (Tables 4.5

and 4.6), there were no livestock feed mills or livestock feed industries in Bali. As a result, much of

the AIBP was discarded in landfills due to it was not fed to ruminants (Marlina & Askar 2004).

Therefore, one of the strategies to develop the goat industry in Bali is the utilization of by-products

various agricultural commodity. Other feedstuffs such as grasses, legumes, kitchen waste, food

market waste, culinary waste, home industrial waste, and crop residues were also potential feeds for

goats in Bali Province (Indraningsih et al. 2006).

4.5 The use of agriculture and industry by-products in promoting the goat industry in Bali Province

The availability and capability of Indonesia to provide feed for 100 million goats or 10 times that of

the present total number was realistic (Horne et al. 1994; Marlina & Askar 2004; Indraningsih et al.

2006; BPS-Indonesia 2015). Indonesia produced 72 million tonnes of un-husked rice in 2012

(BPS-Indonesia 2012). Furthermore, over 10,000 ha were planted for cashew plants in Bali where

they produced 3,303 tonnes of cashew nuts annually (Anonymous 2006). The cashew crop

produced cashew nuts for export while 91 - 92% of cashew apple, commonly treated to be cashew

apple powder, was potential goat feed (Guntoro et al. 2006). Indonesia in 2013, had 1.746 million

ha of cacao plantations that produced 939 thousand tonnes of fresh cacao pod that was equivalent

with 872.3 thousand tonne of DM cacao pod per year.

Conventional feedstuffs were often more expensive (Mirzaei-Aghsaghali & Maheri-Sis 2008) than

feeding goats with improved AIBP (Marlina & Askar 2004; Guntoro et al. 2006; Mirzaei-

Aghsaghali & Maheri-Sis 2008; Guntoro 2012). For example, bodyweight gains were significantly

higher i.e. 60 g/h/d for goats fed cashew apple over traditional feeding of goats i.e. 34 g/h/d during a

12 week trial in Kubu Village, Karangasem Regency, Bali and provided profit of IDR 31,950/h/12

weeks (Guntoro et al. 2006). A 30% substitution of Gliricidia sepium and Caliandra calothrysus

with Aspergillus niger fermented coffee pulp achieved 100 g average daily gain in young PE males

reared in Sepang Village, Busungbiu District, Buleleng Regency Bali (Londra & Sutami 2013).

Fermenting with Phanerochaete chrysosporium increased the crude protein of cacao pods from

8.7% for untreated to 13.8% (Suparjo et al. 2011) and it contained NDF 55.30-73.90% and ADF

38.31- 58.98% (Wisri & Susana 2014). Utilisation of 30% fermented cacao resulted in average


52


daily gain of 84 to 102 g/goat/day and 100 to 125 g/goat/day as well as 1.00 to 1.25 litre/goat/day

(Riyanto & Anam 2012). Therefore, as long as goat industry in Bali Province could optimise

utilization of AIBP, they could contribute to expansion of the goat industry in Bali Province

(Yusdja 2004b, 2004a).

One of the critical issues to the development of the goat industry in Bali was that AIBP had some

constraints for its use including it could be unpalatable, had low protein content and low

digestibility. The nutritive value of abundant potential feeds for livestock could be improved by

implementing technology by further processing the feed (Guntoro et al. 2006; Guntoro 2012).

Simple technologies to improve the nutritive value of this feed were urgently needed by smallholder

farmers so these farmers could feed the available crop residues and AIBP to their goats. More

research in assessing the characteristics as well as the nutritive value of AIBP feedstuffs, when fed

to goats, were needed (Marlina & Askar 2004).

Rice straws were normally low in protein, but high in fibre and with an un-balanced mineral

composition (Choi et al. 2012; Traiyakun et al. 2012). In contrast, AIBP had high protein content

and could be used as protein resources (Moore et al. 2002). Combinations of grasses/straws and

AIBP (Devendra 1974) or shrubby vegetation and AIBP (Ben Salem et al. 2008) or treated grasses

and AIBP (de Oliveira et al. 2010) could be utilised. Therefore, in formulating complete feed

rations, based on the different requirements necessary at different physiological stage for goats, the

available various wastes and by-products in Bali Province could be optimized, too. In addition to

this, the valuable information of the updated analysis of various wastes and by-products in

Indonesia provided by Balitnak-Ciawi made possible for agriculture extension officers could inform

smallholder farmers to improve feed quality for their goat farmers in Bali Province (Kushartono &

Iriani 2004; Marlina & Askar 2004). In future, researchers, and stakeholders such as the livestock

feed industry and in particular, the goat industry could have a livestock feed factory in Bali to

produce livestock feed with low prices.

4.6 Goat rearing systems in Bali Province

Identifying the common types of goat rearing systems, the size of flocks owned per smallholder

family and the role of AIBP as feed to support goat production applied in Bali could help in

improving the growth and economic performance of goat production in Bali Province. This was in

agreement with Paez Lama et al. (2013) and Paez Lama et al. (2015) who reported that different

rearing systems, particularly the feeding systems affected the growth and the profitability of goats


53


production thus improved the number of goats sold. Nemeth et al. (2004) also supported that

different goat farm sizes affected the profitability of goat production.

Goats studied in Rendang, Banjar, Busungbiu, Grogak and Mendoyo Districts in Bali Province were

housed in battery and/or colony housings where a cut and carry, also known as hand feeding or zero

grazing along with a labour intensive production systems. In Gianyar Regency where intensive

farming systems were applied, smallholder farmers housed their goats using a cut and carry feeding

system (Mantra 1991). While Mantra and Bhinawa (1989) reported that in Badung Regency,

smallholder farmers used a cut and carry feeding system and extensive grazing. Goats reared in

Buleleng Regency were penned in coffee or cacao plantations and fed cut and carry with Caliandra

calothrysus, Gliricidia sepium, Pennisetum purpureum, Erythrina variegata and cacao wastes

(Doloksaribu & Subagiana 2009). This result was confirmed by Knipscheer et al. (1984) who

reported the effective use of crop residues, limiting damage to arable crops and young trees, plus the

collection of manure which farmers considered a valuable by-product for use on high value crops

when this feeding system was used. Applying this feeding system also resulted in potentially better

disease management for goats as they were effective browsers and very selective and often selected

feeds which had anti-parasitic properties e.g. trees and bushes containing tannins (Tangendjaja &

Wina 2000; Ørskov 2011; Pathak et al. 2017).

In developing agricultural areas in Bali Province, i.e. dry regions of Karangasem and Klungkung

Regencies or areas that used to suffer from volcanic eruptions, goats usually freely grazed and were

only housed at night or not housed at all (Mantra 1991). Goats in Kubu Village of Karangasem

Regency had extensive grazing in dry hilly regions (pers. obs.). Smallholder farmers in Serangan

Island that is located about 10 km south of Denpasar City also applied extensive grazing. Most of

them were anglers and landless and they penned their goats at night in front of their houses but

allowed them grazing in public fields, roadsides and communal areas in the daytime (pers. obs.).

However, there is little information on whether the tethering system or whether farmers rear goats

integrated with other tree plantations in other regencies in Bali Province.

4.7 The roles of Indonesian Government toward the improving goat production in Bali Province

Like other provinces of Indonesia, agricultural development of Bali Province specifically its goat

production was also planned in the Five Year Development Plan (Repelita) by central government,

the plan that given on the government‘s economic target for the next five years in the New Order

government of the President Suharto era (Booth 1989, 2005). One of the programmes, for example,

smallholder goat farmers in Bali Province received 3,300 Kacang, PE, and Benggala goats (360


54


males and 2,940 females) as President Aid in the era of the former Indonesian President Soeharto

between 1981 and 1987. As a result, Bali smallholder farmers started rearing quality goats as well

as improved goat population in Bali Province (Anonymous 1990; Mantra 1991, 1994).

As the role of central government changed to decentralisation government, beginning in the

calendar (and fiscal) year 2001, the central government replaced many of the existing grants from

the centre to the regions with a 'general allocation grant' (Booth 2003). Therefore, the continuous

programmes to accelerate the sustainable growth and development of agriculture, as well as to

alleviate poverty and unemployment in rural areas of Bali Province, Bali Government had launched

Primatani Programme during 2005 and 2009 then it has been transformed into Integrated

Agricultural System Programme (Simantri) applied up to now (Budiasa 2012; Elisabeth 2012;

Anugrah et al. 2014; Anugrah 2015; Anugrah et al. 2015). The Simantri programme has now been

spreading in many districts providing a package of 40 goats plus goat housing and a short training

of goat rearing management for a group of goat farmers (Ministry of Agriculture and Livestock of

Bali Province 2015). All seven districts in the present study also received packages of goat

Simantri Programme. Since the first Simantri programme was launched to Bali Province in 2009,

smallholder farmers in Busungbiu District in Buleleng Regency as well as in Pupuan District in

Tabanan Regency milked their PE crossbreds (pers. obs.). As a result, households in Busungbiu

District, took the opportunity to gain extra income by selling goats milk and milk products (Arya

2014; Arya et al. 2014), smallholder farmers in Mengwi District, Badung Regency improved their

income by producing organic fertilizer (Cempaka et al. 2016) and alleviated poverty and

unemployment in Kelating Village, Tabanan Regency (Wibawa & Yasa 2013) as well as to pave the

way for sustainable organic agriculture in Bali Province (Budiasa 2012; Anugrah et al. 2014;

Anugrah 2015).

Bali Government in accelerating the sustainable growth and development of agriculture, as well as

to alleviate poverty and unemployment in rural areas of Bali Province ―sharing‖ rights in managing

production forest ―social forestry‖ to smallholder farmers in Sumberklampok Village, Buleleng

Regency. Smallholder farmers were entitled to plant and harvest short-term crops such as

vegetable, fruits crops as well as roughage and grass for their livestock while the government

owned the main crops. As a result, almost all the households in Sumberklampok Village reared

Bali cattle and goats as their main income resource (Surata et al. 2014). In similar manner,

smallholder farmers in Pempatan Village, Rendang District in Karangasem Regency had privilege

to access conservation forest of Abang Agung Mountain for planting roughage for their livestock.

Encouraging the smallholder farmers in Bali Province to access the conservation forests could be


55


one of the development strategies that will help in sustainability of quantity and quality of feeds for

their livestock, practical and convenient feed resources as well as reducing feed cost thus ensuring

high income per household from goat production as well as their integrated farming.

However, field survey conducted in present study showed no official links between smallholder

farmers, smallholder farmer association or the Department of Agriculture in Bali Province and

Research Institute for Animal Production (Balitnak-Ciawi) and Research Institute for Goat

Production (Sungei Putih) to ensure the sustainable development of goat production in Bali

Province by providing them the quality goat breeds. Information related to the productive and

reproductive performance of the first imported 3,300 of Kacang, PE, and Benggala goats (360

males and 2,940 females) about 36-30 years ago to Bali Province is little known except for their

numbers that had been increased to 68,457 goats in 2014 (BPS-Bali 2015). The exotic goat breeds

such as Saanen, Anglo-Nubian, Boer or pure Etawah goats that have been observed in IRIAP

(Balitnak-Ciawi) (Praharani et al. 2013; Praharani 2014; Praharani et al. 2015) or in RIGP (Sungei

Putih) (Mahmilia & Tarigan 2004; Elieser et al. 2006; Mahmilia 2007; Mahmilia & Elieser 2008;

Mahmilia et al. 2009; Mahmilia 2010; Mahmilia & Doloksaribu 2010; Mahmilia et al. 2010) and

they have adapted to West Java or North Sumatera climates, spare feeds and water resources, and

various diseases, surprisingly they were not exported to Bali Province for upgrading their

indigenous breeds through crossbreeding. No published references have mentioned that Indonesian

Government or other institutions have officially imported the exotic goat breeds for improving goat

production in Bali Province after the first goat introduction to smallholder farmers in Bali Province

in 1987 (Mantra 1991, 1994). Strategic plans of the Indonesian Minister of Agriculture for 2015-

2019 did not have specific strategic plans for development of exotic goat breeds imported to

particular district for improving goat rearing under smallholder production system in Bali Province

(Anonymous 2015c).

4.8 Conclusion

Overview of goat production systems in Bali Province had important implications for the

improvement of goat rearing of Bali smallholder farmers. The study concluded that goat rearing

under smallholder production systems was economically viable as it were supported by the goat

breeds that well adjust to the Bali environment included its climate, the distribution of goats,

agricultural systems, the availability of agriculture and industry by-product, goat rearing systems,

the role of Indonesian Government towards the improving goat production and rearing

management. Providing the overview of goat production systems meant providing the strengths,

weaknesses, opportunities and threats faced by smallholder farmers in rearing goats. Smallholder


56


farmers, Bali Government, stakeholders and institution involved in goat industry in Bali could draw

up plans to take advantage of the strengths and opportunities as well as to counter the threats if

possible, and minimize or reduce the weaknesses. In future, smallholder farmers could sustain the

development of their goat. In most cases, goat farming is part of an integrated agricultural farming

system. Goats consume agricultural by-products and provide employment. Goats produce fertilizer

for agricultural crops, as well as income for farmers.

Chapter 5 Rendang District, Karangasem Regency

57


Chapter 5

Current and future goat production in Karangasem Regency, Bali Province, Indonesia:

A case study in Rendang District.

5.1 Introduction

The goat population in Karangasem Regency has fluctuated over the last five years. It was 22,057

goats in 2011, it dropped to 18,126 goats in 2012 and 17,316 goats in 2013, and then it increased

slightly to 19,280 goats in 2014 (BPS-Bali 2015). However, available literature presented little

information on the current situation of goat rearing under smallholder production systems in

Karangasem Regency (Doloksaribu & Subagiana 2009). A case study was conducted between 3rd

April to 30th

September 2014 in Pempatan Village in Rendang District since about 20.4% of the

goat population in Karangasem were found in this district (BPS-Bali 2015). Karangasem Regency

had the largest number of 11,510 poor people or 9% of the total population of Karangasem Regency

and had the lowest poverty of IDR 322,000 or equivalent to US$32.2 per capita per month among

regencies of Bali Province in March 2015. It had the lowest for the Human Development Index

(HDI) of 64.7 while Denpasar City had the highest HDI of 82.2. Agriculture, forestry and fishery

were the main sectors that supported the economy of Karangasem Regency. These sectors had IDR

3.242 trillion or 26.3% of the total of IDR 12.304 trillion for the Karangasem Regency Gross

Regional Domestic Product (GRDP) (BPS-Bali 2015; BPS-Indonesia 2015; BPS-Karangasem

2016). In addition, Rendang District was a designation district for improving goats that was

officially promulgated by the Karangasem Government (Anonymous 2016b; BPS-Karangasem

2016). Therefore, improving goat productivity by smallholder goat farmers in Rendang District

could have vast potential for their socio-economic upliftment. The objective of this chapter was to

establish a database of the reproductive and productive efficiency of goat farming under

smallholder production systems in Rendang District in Karangasem Regency, as well as a socio-

economic analysis of these systems. The database was used to set up development strategies,

through identifying their constraints to, challenges of and opportunities for improving goat

production, in Bali Province.

5.2 Research design and Methods

The general research design and methods used in this study are described in Chapter 3 with minor

adjustments. The goat farming studied in Rendang District encompassed 11 villages and nine

cultural villages that cover 53.78 km2 with 2,267 households and 9,431 people in 2010 (BPS-Bali

2015). The 11 villages were Pule, Pure gae, Waringin, Keladian, Putung, Alasngandang, Pempatan,

Teges, Geliang, Kubakal and Pemuteran which were situated in the middle of a 17,000 ha


58


conservation forest (BPS-Bali 2015). All 63 goat-owning families were interviewed, based on

structured questionnaires, and 1,169 goats were observed directly to obtain data that included breed-

type, sex, lactation status, age, dentition status (I0, I1, I2, I3, I4, toothless), FAMACHA©

score,

bodyweight, body measurements, birth type (single and multiple), and parity. Direct animal

observations were recorded over a four months period. Labourer was a household member

regardless of their sex who was 15 years old or older and was involved in goat farming. The inputs

included feeds, veterinary services, drugs, and labour cost i.e. labourers (from the family). The

outputs obtained included sales of live animals, manure or goat products consumed at home which

were then converted into cash (IDR million). IDR 1 million was equivalent to AUD$100.00.

5.3 Results

5.3.1 Household labourers and their profiles

Background information on household labourers and their profiles in rearing goats is shown in

Table 1 (Appendix 1). In all 63 households, husbands and wives were interviewed, and they both

confirmed additional family members who were involved in goat rearing. Every household studied

in Rendang District owned and cultivated on average 2 ha land integrated with goat rearing of

various flock sizes while herbaceous roughage were planted in conservation forest. All households

were Balinese Hindu vegetable farmers who reared goats and occasionally Bali cattle as part of an

integrated agricultural farming system.

The head of the household was usually married to one wife and they had one or two children.

Children who were 15 years old or older contributed to goat keeping activities, and were considered

as family labourers. All family labourers regardless of their sex were involved in vegetable farming

and goat rearing equally. All the households interviewed had other activities including caring for

their Bali cattle, tending vegetable farms, marketing vegetable produce, household work, off-farm

activities and social activities and resting. The labour input was approximately 0.5 hour per

labourer per day allocated to goat rearing or 180 equivalent working hours annually (Lagemann

1977; Muljadi et al. 1983; Supriadi et al. 2009). Therefore, when a household had the largest

number of six household labourers, it was assumed that the six household labourers spent three

hours per day to rear a flock no matter what the flock size was. This indicated that the household

spent six labourers x 0.5 hour x 365 days=1,095 hours to rear a flock of goats annually. In contrast,

a household with two labourers took 365 hours to rear a flock of goats annually.

The Bali Government categorized unskilled workers, which included farm workers. Farm workers

were assumed to have the lowest level of education i.e. Primary School or Grade 1-6, as well as the


59


lowest productivity compared to those who work in the trade, restaurants, and hotels sectors (BPS-

Bali 2015). The wage for a household labourer was IDR 40,000 or equivalent to AUD$4.00 per an

eight-hour work day (BPS Bali 2015). Therefore, the labour cost input for a household who had

two labourers was two labourers x IDR 3,125 x 365 days=IDR 2,281,250 annually while it was IDR

6,843,750 annually for a household who had six labourers. However, the labourer cost input for

Rendang District was adjusted to be IDR 50,000 per day. This adjustment was made as there was a

range of IDR 40,000 to 60,000 as a daily wage for a labourer who worked in the agricultural sector

(BPS Bali 2015).

The effects of the number as well as the productivity of family labourers on turn off rate, GM (A-B)

and GM/doe of goats reared in Rendang District will be further investigated in a latter section of

this thesis. Production parameters of 1,169 goats reared in Rendang District is shown in Table 2

(Appendix 1). Overall, goat rearing in Rendang District had averages of gross margin or GM(A-B)

and GM/doe were IDR 6.330 ± 1.626 million and IDR 0.350 ± 0.274 million, respectively.

Assumptions for cost of inputs used for raising goats included the average drenching cost of IDR

0.056 ± 0.005 million and roughage cost of IDR 6.773 ± 0.619 million, dagdag cost of IDR 0.520

million and labour cost of IDR 3.078 ± 0.128 million. Assumptions for price of outputs used were

the average price of goats sold was IDR 15.063 ± 1.963 million, and price of manure sold was IDR

1.693 ± 0.155 million. Gross Margin/doe is a "snapshot" observation in this study. It is feasible

that a farmer could sell most of their animals in one year, and have a higher GM/doe. Thus, they

would have fewer animals to sell the following year and this would result in a loss. A more

accurate measurement would be the average GM/doe over a number of years, but this was not

possible in the present study.

The number of household labourers that was calculated as the annual equivalent working hours

significantly affected GM/doe (P<0.05) (Table 3 in Appendix 1). The largest number of labourers

per flock i.e. six labourers generated the significantly lowest GM/doe of IDR (6.182 ± 2.071)

million. This indicated that larger numbers of household labourers were inefficient when they

reared small flocks.

The flock with six labourers reared 15 goats and sold two goats, and had a 13% turn off rate with a

total income of IDR 5.369 million while the variable cost was IDR 12.884 million. The cost of six

labourers was IDR 6.844 million and the feed cost was IDR 5.995 million. If this farmer could

achieve a ≤33% turn off rate, they would be able to have more positive GM(A-B) and GM/doe by

selling three or four more goats prior to Eid Qurban (Table 3 in Appendix 1).


60


The level of farmers‘ education per se, would be expected to improve the efficiency of goat

production, as it was hypothesised that farmers with a better education would implement improved

management practices. However, this study revealed that the level of education of the household

did not significantly affect the turn off rate, GM(A-B) or GM/doe (P>0.05) although there was a

tendency that farmers with the highest level of education had the highest GM/doe (Table 4 in

Appendix 1).

The level of farmers‘ education also did not significantly affect the labourer ratio, the number of

does owned and number of goats sold per household (P>0.05) (Tables 4 and 5 in Appendix 1).

Farmers that had the highest education level tended to have the highest labourer ratio of 11 ± 3

goats per labourer and the highest turn off rate of 65 ± 14% and generated positive values for both

GM(A-B) of IDR 15.110 ± 5.747 million and GM/doe of IDR 1.584 ± 0.959 million.

5.3.2 Goats and their profiles

Smallholder goat farmers in Rendang District reared goats that were a mixture of Gembrong,

Benggala, Kacang, Etawah Grade, PE and their crossbreds or backcrosses (Plate 2.1). The number

of female goats (2,364, mostly adult females) were significantly more than the 1,001 male goats

recorded (P<0.05) (Tables 5.1, 6 and 7 in Appendix). The average bodyweight, chest

circumference, height at withers and rump height for male weaners were significantly higher

(P<0.05) than those for female weaners (Tables 6 and 7 in Appendix 1).

Bodyweights, based on their physiological state, of 1,169 goats were recorded once to four times

during observations in 2014 in Rendang District (Table 5.1). The numbers of female goats of all

physiological states were higher than male goats in April, June, August and September 2014 (Table

5.1). The ratio between females to males of all physiological states of goats was 2:1 except for

mature goats where the ratio was 6:1. This indicated that the majority of animals turned off were

males. Flock sizes had a high correlation (P<0.05) with the number of different physiological states

of goats owned by the farmers. This profile varied depending on the month of observation and the

period when most kids were born in February and July (Figure 5.1).


61


Table 5.1 Average bodyweights of different classes of goats recorded once to four times during four

observations in Rendang District, Karangasem Regency. Class of goat Number and bodyweight of goats (Mean ± SEM kg, n) in April 2014

Female Male Total

All preweaned (d1 - 135) 12.6 ± 0.5, n=121 13.3 ± 0.7, n=105 12.9 ± 0.4, n=226

All weaner (d136 - 290) 20.7 ± 0.9, n=39 21.5 ± 1.1, n=35 21.1 ± 0.7, n=74

All yearling 28.5 ± 0.9, n=64 29.5 ± 1.3, n=42 28.9 ± 0.8, n=106

M buck ----- 43.6 ± 1.9, n=31 43.6 ± 1.9, n=31

F pregnant 41.0 ± 0.9, n=110 41.0 ± 0.9, n=110

F lactating 34.7 ± 0.7, n=121 34.7 ± 0.7, n=121

F dry 38.3 ± 1.2, n=58 38.3 ± 1.2, n=58

All goats 29.4 ± 0.6, n=513 22.2 ± 0.9, n=213 27.3 ± 0.5, n=726

Class of goat Number and bodyweight of goats (Mean ± SEM kg, n) in June 2014

Female Male Total


All weaner (d136 - 290) 20.1 ± 0.8, n=62 23.5 ± 0.8, n=53 21.7 ± 0.6, n=115

All yearling 27.4 ± 0.8, n=71 28.1 ± 0.9, n=59 27.7 ± 0.6, n=130

M buck ----- 42.1 ± 1.5, n=44 42.1 ± 1.5, n=44

F pregnant 42.2 ± 0.9, n=68 42.2 ± 0.9, n=68

F lactating 36.7 ± 0.8, n=86 36.7 ± 0.8, n=86

F dry 37.3 ± 0.6, n=150 37.3 ± 0.6, n=150

All goats 28.4 ± 0.6, n=565 22.2 ± 0.8, n=267 26.6 ± 0.5, n=832

Class of goat Number and bodyweight of goats (Mean ± SEM kg, n) in August 2014

Female Male Total


All weaner (d136 - 290) 17.2 ± 0.5, n=83 19.4 ± 0.8, n=61 18.2 ± 0.4, n=144

All yearling 26.3 ± 0.6, n=100 27.8 ± 0.8, n=51 26.8 ± 0.5, n=151

M buck ----- 40.0 ± 1.2, n=47 40.0 ± 1.2, n=47

F pregnant 42.5 ± 1.4, n=23 42.5 ± 1.4, n=23

F lactating 37.4 ± 0.6, n=131 37.4 ± 0.6, n=131

F dry 37.2 ± 0.6, n=138 37.2 ± 0.6, n=138

All goats 27.7 ± 0.5, n=574 20.5 ± 0.8, n=263 25.4 ± 0.5, n=837

Class of goat Number and bodyweight of goats (Mean ± SEM kg, n) in September 2014

Female Male Total


All weaner (d136 - 290) 18.8 ± 0.6, n=55 21.1 ± 1.1, n=43 19.8 ± 0.6, n=98

All yearling 26.4 ± 0.6, n=108 27.6 ± 0.8, n=53 26.8 ± 0.5, n=161

M buck ----- 40.2 ± 1.4, n=43 40.2 ± 1.4, n=43

F pregnant 40.6 ± 2.2, n=10 40.6 ± 2.2, n=10

F lactating 38.3 ± 0.6, n=122 38.3 ± 0.6, n=122

F dry 36.8 ± 0.6, n=108 36.8 ± 0.6, n=108

All goats 27.7 ± 0.6, n=500 22.0 ± 0.8, n=231 25.9 ± 0.5, n=731

F=Female, M=Male. All preweaned=aged 0 – 4.5 months; All weaner=4.5 month – I0; All yearling=I1; F pregnant, F lactating, F

dry, and buck had I1 – toothless. Means in a column with different superscripts differed significantly at the .05 level.

Some late pregnant females as well as too heavy bucks were not weighed for safety reasons.


62



households in Rendang District, Karangasem Regency.

There were 108 dry females or 15% of the 731 goats recorded in 63 flocks in September 2014

(Table 5.1). Of the 63 flocks in Rendang District, 71.4% or 45 flocks had no pregnant females in

September 2014. Of the 21 smallholder farmers who had the smallest flock sizes of 1≤10 goats,

47% had no pregnant females in September 2014. In September 2014, 92% and 100% of the flocks

with sizes of 21≤30, and 31≤85 goats, respectively had no pregnant females. Fifty three per cent of

farmers who had the flock size 11≤20 goats had bucks and pregnant females (Table 5.1 and Figure

5.1).


the first six months in 2014 in Rendang District, Karangasem Regency.

The numbers of kids‘ born, that died, survived, were sold or reared affected the production

parameters of goats reared in Rendang District. In 2014, 362 productive females that had


63


I0/I1/I2/I3/I4 (the ―I‖ with subscript indicated the number of permanent incisors) or toothless

dentition gave 413 parturitions that delivered 568 kids (Figure 5.2).

Kidding rate (568 kids born per 362 does of reproductive age/year) was 157% for kids born from

the start of January to the end of September 2014 in Rendang District. The ratio between female

and male kids born was 289:279, i.e. 1:1. Of the 413 parturitions, 65% were single born (268 kids),

followed by 33% twins and 2% for triplet and quadruplet born kids. The average litter size was

1.66 for kid‘s birth in 2014. There were 396 does of the total 1,169 goats reared in Rendang

District and 91% of the does kidded during the first 9 months in 2014. Of the 568 kids born, 62%

were born from does that were kept in colony housing.

All kids that were born from the start of January to the end of September 2014 in Rendang District

had an average birth weight of 3.1 kg and a weaning weight of 18.2 kg at day 135 with an average

bodyweight of 10.3 ± 0.17 kg during the 135 days preweaning period (Figure 5.3). The average

daily gain from day 1 to day 135 was 128 ± 3.6 g/d. The average bodyweight of early post-weaned

kids up to day 290 was 22.8 ± 0.29 kg and their average daily gain from day 136 to 290 was 112 ±

3.2 g/d (Table 5.2). There were no significant differences (P>0.05) of birth weights between female

(2.99 kg) and male (3.14 kg) kids. Early post weaning kids achieved 18.8 kg at day 150 and 32.3

kg at day 290. This study revealed that the correlation between age and bodyweight from birth to

290 days was strong (R2=0.81) (Figure 5.3 & Table 5.2). The average birth weight of kids born in

Rendang District in 2014 was 3.1 kg and weaning weight was 18.2 kg, delivered by females that

had an average bodyweight of 40 to 42 kg (Figure 5.3 and Table 5.1).

Figure 5.3 Growth rates and 1,265 bodyweights of 568 kids from birth until post weaning age i.e.

290 days, when kids were weaned at day 135, in 2014 in Rendang District, Karangasem Regency.


64


According to published data, a normal growth curve is curvilinear, but the observations in this study

only covered the earlier linear portion of the growth curve, so a linear regression adequately fitted

the data. The observations had not been extended into adulthood so the age at which bodyweight

would plateau could not be predicted. Age and sex significantly affected (P<0.05) bodyweight and

average daily gain of kids aged 1 to 290 days (Figure 5.3). The average bodyweight of weaners

aged 136 to 290 days was 22.8 ± 0.3 kg, n=429 which was significantly higher (P<0.05) than the

average bodyweight of preweaned kids aged 1 to 135 days i.e. 10.3 ± 0.2 kg, n=836. However, the

average daily gain of weaners aged 136 to 290 days was 112 ± 3.5 g/d, n=362 which was

significantly lower (P<0.05) than the average daily gain of preweaned kids aged 1 to 135 days i.e.

128.1 ± 3.3 g/d, n=404. The average bodyweight of post weaned male kids aged 136 to 290 days

was 24 ± 0.4 kg which was also significantly higher (P<0.05) than the average bodyweight of

preweaned male kids aged 1 to 135 days which was 10.6 ± 0.3 kg. There was no significant

difference (P>0.05) between the bodyweight of preweaned female and male kids whereas it was

significantly different (P<0.05) between the bodyweight of weaned female and male kids.

The average daily gain of post weaned female kids aged 136 to 290 days was 110 ± 4.5 g/d which

was significantly lower (P<0.05) than the average daily gain of preweaned female kids aged 1 to

135 days which was 113.5 ± 5 g/d. The average daily gain of post weaned male kids aged 136 to

290 days was 115 ± 5 g/d was also significantly lower (P<0.05) than the average daily gain of

preweaned male kids aged 1 to 135 days which was 143 ± 5 g/d. There was a significant difference

(P<0.05) between average daily gain of preweaned female and male kids while there was no

significant difference (P>0.05) between the average daily gain of weaned female and male kids.

A total of 519 kids were born in Rendang District during the observation period in 2014. Of these

23% were born in February and 20% were born in July. The least number of kids born were in

September (1%) and in April (5%) (Table 5.1 and Figure 5.4). However, when kidding season was

categorized based on flock size, 34% of 64 kids born in flocks of 1≤10 goats were born in February

while 30% of 123 kids in flocks of 11≤20 goats were born in July. Of 129 kids born in flocks of

21≤30 goats, 20% and 18% of them were born in February and July, respectively. However, 25%

and 20% of 203 kids born in flocks of 31≤85 goats were born in February and July, respectively

(Figure 5.5). These figures were probably related to the rainfall in Karangasem Regency when kids

were born in months that had average rainfall in February (173 mm) and in July (217 mm) (Figure

4.1).


65


Figure 5.4 Flowchart of timing of kids born, kidding intervals, days open and gestation periods of

goats reared in Rendang District, Karangasem Regency in 2014.

Figure 5.5 Percentage of kids born based on flock size and the time of kids born from January 2014

to September 2014 in Rendang District, Karangasem Regency.

Weaning rate (519 kids weaned per 362 does of reproductive age/year) was 143% for kids born

from the start of January to the end of September 2014 in Rendang District. Of the 519 kids

weaned, 62% kids were born and reared in colony housing.

The average of 196 kidding intervals of does from their first to their tenth parity in 2014 was 244 ±

4.7 days, and does in individual flocks ranged from the shortest of 151 days to the longest of 509

days (Figure 5.4 and Table 5.2). This indicated that all does, irrespective if they were kept in

battery or colony housing, kidded three times in two years.

2014 2015 2016

Gestation Period

(± 5 months)

Days open Gestation Period

(± 5 months)


(± 5 months)


(± 5 months)

Kidding interval (± 8 months) Kidding interval (± 8 months) Kidding interval (± 8 months)

F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J

F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J

Kidding interval (± 8 months) Kidding interval (± 8 months) Kidding interval (± 8 months)


(± 5 months)


(± 5 months)


(± 5 months)

Days open

2014 2015 2016

C


66


Table 5.2 Kidding interval (days), BW preweaned (kg), ADG preweaned (g/d), BW post weaned

(kg) and ADG post weaned (g/d) of 1,169 goats reared by 63 households in Rendang District,

Karangasem Regency. Production parameters each household Mean ± SEM n Range Minimum Maximum Mode

Kidding intervals (days) 244 ± 4.7a 196 358 151 509 210

Single 243 ± 5.5bc** 114 321.5 151 472.5 244

Twin 244 ± 9ac 67 340 151 491 210

≥Twin 253 ± 19.5ac 15 335.5 173.5 509 237.5

BW preweaned (kg) (d1 to 135) 10.3 ± 0.17 836 25 2 27 5

ADG preweaned (g/d) (d1 to 135) 128 ± 3.6 404 334 16 350 130

BW post weaned (kg) (d136 to 290) 22.8 ± 0.29 429 29 11 40 20

ADG post weaned (g/d) (d136 to 290) 112 ± 3.2 362 338 12 350 130

BW=Bodyweight, ADG=Average Daily Gain. Means in a column with different superscripts differed significantly at the .05 level.

Kidding interval was not significantly different (P>0.05) between type of birth i.e. single, twin and

multiple kiddings. However, does that had single kids (243 ± 5.5 days) or twin kids (244 ± 9 days)

tended to have shorter kidding intervals than does that had multiple kids (253 ± 19.5 days) (Table

5.2). There was a significant difference (P<0.05) in kidding interval between female and male

single births. The kidding interval for does that gave birth to male single birth kids was 231 ± 5.8

days, being significantly (P<0.05) less than the kidding interval for does that gave birth to female

single birth kids (249 ± 18.6 days) when does were kept in colony housing. In contrast, the kidding

interval for does that gave birth to female single births kids was 238 ± 10.2 days, being significantly

(P<0.05) less than the kidding interval for male single birth kids (253 ± 19.5 days) when does were

kept in battery housing (Table 5.2).

5.3.3 Socio-economic analysis

Overall, the total GM/doe was IDR 22.040 million with an average of IDR 0.350 ± 0.274 million,

ranging from a loss of IDR 6.466 million to a profit of IDR 4.707 million. Of the 1,169 goats

studied, 587 goats were sold in 2014 for the total price of IDR 949 million that contributed 90% to

the total income of IDR 1,055.671 (Figure 5.7). Comparison of the GM/doe between the top 20 and

bottom 20, across the 63 households studied in Rendang District, is shown in Table 5.3.

Of the top 20 households for GM/doe, all households had positive values of GM/doe ranging from

the lowest of IDR 1.631 million when the household had seven goats including two does and sold

five goats and had a 76% turn off rate. This indicated that having two does could cover the total

variable costs including when two household labourers were employed. This also indicated that a

doe in a flock of seven goats generated IDR 1.631 million GM/doe (Table 5.3).


67




farms under smallholder production systems in Rendang District, Karangasem Regency.

Farmer

No. of

goats

sold/year

Turn off

rate (%)

Flock size

(goats)

Labourer

to goat

ratio

No. of

does

owned

(IDR million)

Total

income

Total

variable

costs GM(A-B) GM/doe

Top 20

1 Sunadi 37 96 39 19.5 10 64.225 17.153 47.072 4.707

2 Ratep 13 111 12 3.0 4 25.762 9.498 16.263 4.066

3 Dika 11 76 14 7.0 3 19.944 7.953 11.991 3.997

4 Mekartani 35 102 34 11.3 12 59.769 16.454 43.315 3.610

5 Jatrasentil 32 100 32 10.7 11 52.253 15.718 36.535 3.321

6 Puspa 16 76 21 10.5 7 29.916 10.529 19.387 2.770

7 Tegteg 13 83 16 8.0 5 22.127 8.689 13.437 2.687

8 Nadi 21 93 23 11.5 9 34.765 11.265 23.500 2.611

9 Muliana 19 75 25 8.3 8 32.281 13.142 19.139 2.392

10 WSuarka 11 89 12 6.0 6 20.428 7.217 13.211 2.202

11 Genap 19 57 33 8.3 8 34.344 17.226 17.118 2.140

12 WSudiarta 16 84 19 3.8 6 25.734 13.215 12.519 2.086

13 Suma 8 89 9 3.0 3 13.488 7.254 6.234 2.078

14 MDana 19 85 22 11.0 8 27.341 10.897 16.444 2.055

15 Rumasih 27 61 44 22.0 15 48.682 18.993 29.688 1.979

16 Saba 8 80 10 5.0 5 16.246 6.481 9.765 1.953

17 Arnyana 27 67 40 20.0 16 47.650 17.521 30.129 1.883

18 Santika 19 75 25 8.3 11 32.948 13.142 19.806 1.800

19 GArdana 8 50 16 8.0 4 15.460 8.689 6.771 1.693

20 Aryanti 5 76 7 3.5 2 8.639 5.377 3.261 1.631

Bottom 20

1 Tunas - - 5 1.3 1 0.456 6.922 (6.466) (6.466)

2 WSudarta 3 18 15 2.5 1 6.702 12.884 (6.182) (6.182)

3 Sumardi - - 6 3.0 1 0.547 5.009 (4.462) (4.462)

4 Sari - - 5 2.5 1 0.456 4.641 (4.185) (4.185)

5 Wirata - - 10 3.3 3 0.912 7.622 (6.709) (2.236)

6 Yadna - - 12 6.0 3 1.095 7.217 (6.122) (2.041)

7 Padma - - 11 5.5 3 1.004 6.849 (5.845) (1.948)

8 Susun - - 11 3.7 4 1.004 7.990 (6.986) (1.746)

9 NiniPekak - - 2 1.0 2 0.182 3.537 (3.355) (1.677)

10 Durma - - 10 5.0 4 0.912 6.481 (5.569) (1.392)

11 Jaten - - 18 9.0 6 1.642 9.425 (7.783) (1.297)

12 Rata 3 21 13 4.3 4 4.520 8.726 (4.206) (1.051)

13 Sripa - - 16 5.3 8 1.460 9.830 (8.370) (1.046)

14 Tiarsa 3 15 18 6.0 6 6.309 10.566 (4.257) (0.709)

15 Letri 5 20 27 5.4 9 10.464 16.159 (5.695) (0.633)

16 Suardana 3 38 7 2.3 2 5.305 6.518 (1.212) (0.606)

17 Sukadana 5 21 25 8.3 5 10.281 13.142 (2.861) (0.572)

18 Bingin 3 33 8 2.7 5 4.063 6.886 (2.822) (0.564)

19 Ngarti 3 30 9 3.0 4 5.488 7.254 (1.766) (0.441)

20 Karsa 3 18 15 5.0 5 8.035 9.462 (1.426) (0.285)

Figures in brackets mean their values were negative.

The largest GM/doe per household studied was IDR 4.707 million when the household had a flock

of 39 goats including10 does, and they had the largest number of goats sold/year in Rendang

District i.e. 37 goats or had a 96% turn off rate in 2014. This household generated a total income of

IDR 64.225 million and a gross margin of IDR 47.072 million. This also indicated that a doe in a

flock of 39 goats generated IDR 4.707 million GM/doe. The top 20 for GM/doe indicated that the


68


larger the number of does owned per household, the larger amount gained per doe per household

(Table 5.3).

In contrast, the lowest GM/doe per household in Rendang District was a loss of IDR 6.466 million

and a total income of IDR 0.456 million when the household had a flock size of five goats including

one doe in the flock and they sold no goats in 2014. Of the 20 bottom households for the GM/doe,

11 households (55%) sold no goats, seven households sold three goats each and two households

sold five goats each although they had relatively larger flock sizes. The reason for these households

to be the bottom 20 for GM/doe were all the households had less than 40% turn off rate. This had a

positive perspective because they were waiting to sell their goats, resulting in higher GM/doe, just

prior to Eid Qurban. The bottom 20 households, for GM/doe, also indicated that some households

in Rendang District should increase the number of does in their flocks to improve their GM/doe

(Table 5.3).

Flock sizes that were categorized as four groups i.e. 1≤10, 11≤20, 21≤30 and 31≤85 goats

significantly affected GM(A-B), GM/doe and flock size (P<0.05) but not the turn off rate (P>0.05)

(Table 11 in Appendix 1). The lowest flock size 1≤10 goats generated negative values for both

GM(A-B) and GM/doe. As the flock sizes increased so did the number of does owned per flock

and turn off rate, but this pattern was not followed by GM(A-B) and GM/doe (Tables 11 and 12 in

Appendix 1).

Of the 63 flocks in Rendang District, flocks were categorised into 21 flocks that had 1≤10 goats, 19

flocks that had 11≤20 goats, 12 flocks that had 21≤ 30 goats and 11 flocks that had 31≤85 goats

(Figure 5.6). Of the 21 smallest flocks, only 19% of these flocks had positive values for GM(A-B)

and GM/doe when the households had at least a 33% turn off rate per year. Those households

received a total income of IDR 12.400 million for selling goats and manure, and GM(A-B) was IDR

5.900 million and GM/doe was IDR 1.200 million when they sold 6 goats per year. This indicated

that having small flock sizes did not necessarily mean always having a negative gross margin. As

the sizes of flocks increased, the positive values of GM(A-B) and GM/doe also increased; they were

42%, 67% and 91% for the flock sizes of 11≤20, 21≤30, and 31≤85 goats, respectively (Figure 5.6).


69



four flock sizes of goats reared in Rendang District, Karangasem Regency.

A simulation generated from the calculations of GM(A-B) and GM/doe, in Rendang District, could

help households see how important flock size is, as well as the proportion of does in the flock

(Table 5.4).

Table 5.4 Simulation on how flock size and the number of does owned affects the GM(A-B) (IDR

million) and GM/doe (IDR million) of goats reared in Rendang District, Karangasem Regency. Description Simulation of production parameters in Rendang District

Flock 1 Flock 2 Flock 3 Flock 4

Flock size (goats) 2 33 33 18

No. of doe/flock (does) 2 30 11 6

No. of goats sold/year 3 45 17 9

Prices of goats sold (IDR million) 4.500 67.500 25.500 13.500

Prices of manure sold (IDR million) 0.182 3.011 3.011 1.642

Total income (IDR million) 4.682 70.511 28.511 15.142

Turn off rate (%) 150 136 51 50

Drenching cost (IDR million) 0.006 0.099 0.099 0.054

Roughage cost (IDR million) 0.730 12.045 12.045 6.570

Dagdag cost (IDR million) 0.520 0.520 0.520 0.520

Cost for 2 labourer/household (IDR million) 2.281 2.281 2.281 2.281

Total variable costs (IDR million) 3.537 14.945 14.945 9.425

GM(A-B) (IDR million) 1.145 55.566 13.566 5.717

GM/doe (IDR million) 0.573 1.852 1.233 0.953

The 11 households having the largest flock sizes 31≤85 goats had planned to sell more goats prior

to Eid Qurban on the 5th

October 2014 when prices reached their peak. This indicated that this

17.5% of households in Rendang District increased the number of goats they sold, their turn off

rate, the money gained from selling goats, GM(A-B) and GM/doe during the Eid Qurban. It should

be noted that the Eid Qurban is a Muslim festival. The Muslim calendar is 354 to 355 days long, so

the date for the Eid Qurban festival changes by about 11 days per year.

Each household sold on average 9.3 ± 1.2 goats in 2014 (Table 5.5). Preweaned kids, 1.8 ± 0.3

males and 1.6 ± 0.3 females, were the largest number sold while 0.4 ± 0.1 male and 0.5 ± 0.1 female

yearlings and 0.5 ± 0.1 mature bucks were the lowest number of goats sold. No pregnant or


70


lactating females were sold (Table 5.5). This indicated that male and female yearlings and mature

bucks were kept to be sold just prior to Eid Qurban. Thus, turn off rate would be increased,

particularly in those that had the large flocks.

Table 5.5 Average number of goats of different classes sold per households in Rendang District,

Karangasem Regency. Class of goat Mean ± SEM, n=63 Range Minimum Maximum Mode

Flock size (goats) 18.5 ± 1.7 83 2 85 7

F preweaned 1.6 ± 0.3 12 0 12 0

F weaner 0.5 ± 0.2 10 0 10 0

F yearling 0.5 ± 0.1 6 0 6 0

F dry 1.2 ± 0.2 6 0 6 0

M preweaned 1.8 ± 0.3 12 0 12 0

M weaner 0.5 ± 0.2 12 0 12 0

M yearling 0.4 ± 0.1 6 0 6 0

M buck 0.5 ± 0.1 4 0 4 0

Average of goats sold 9.3 ± 1.2 28 0 28 0

Figure 5.7 Number of goats, of different physiological states, sold per household and estimated

price (IDR million) of goats reared in Rendang District, Karangasem Regency.

The average turn off rate of goats reared in Rendang District was 44 ± 4% where on average each

household sold 9.3 ± 1.2 goats with a total average income per flock of IDR 15.063 ± 1.963 million

in 2014 (Table 5.5 and Figure 5.7). Four-hundred and forty four goats in different physiological

state were sold for the total price of IDR 711.750 million or approximately AUD$71,175/63 flocks

during the nine months in 2014. It was 587 goats in different physiological states that were sold out

of 1,169 goats for the total price of IDR 949 million or approximately AUD$94,900/63 households

in 2014. Sale of goats was IDR 161.669 million per 100 goats per year or IDR 0.812 million per

1,169 goats reared in Rendang District (Figure 5.6). The prices for goats sold for different purposes

are given in Table 13 (Appendix 1).


71


5.3.4 Effects of managerial and environmental factors on production parameters

5.3.4.1 Objectives of goat keeping

All (100%) households interviewed kept goats as a source of fertilizer as they used the goat manure

to improve soil fertility in their vegetables farming. By using the goat manure, households reduced

their production costs. Other benefits of rearing goats were the extra income resources of selling

goat manure.

The second priority for keeping goats was to utilise roughage as households had free access to the

conservation forest to grow roughage in big land for animal feeds. Growing a mixture of roughage

in the conservation forests provided sufficient quantity and quality of roughage throughout the year.

The third priority was to increase income as the ―living bank‖ with goats sold when cash was

needed.

Only households who had large flock sizes had priority of selling goats, particularly prior to Eid

Qurban when Muslims demanded yearling, blemish free, horned male goats, or Mecaru goats when

Balinese Hindus demanded blemish free, horned black goats. For Mecaru weaners, they were sold

for both breeding stock and Mecaru ritual purposes. Selling goats for Eid Qurban or for Mecaru

purposes gained more profit than selling live goats for breeding stock or culled goats for the

purpose of making satay (meat). None of the households raised goats solely for breeding, or for

fattening or solely for home consumption. Households sold no goat meat (only live animals), goat

milk, or their products.

5.3.4.2 Feed and feeding management

Cut and carry feeding systems were the only feeding system used; all goats were fed twice a day at

noon and in the evening at 5:00 pm. Households estimated the amount of fresh Caliandra

calothrysus, Pennisetum purpureum, Artocarpus heterophyllus and Sesbania sesban fed to their

goats was as much as 5 kg/goat/day regardless of their physiological state. Households had free

access to grow herbaceous roughage in the conservation forest that provided sufficient quality and

quantity of roughage throughout the year for their goats. Dagdag soup consisting of boiling water

with rice pollard, salt, urea and chokos, cabbage, young jackfruits, sweet potatoes, and cassava

leftovers from their vegetable harvestings were also provided twice or three times in a week.

Concentrate starter or commercial concentrates were never given purposefully to goats.


72


Results of this study revealed that feed cost was the highest cost i.e. IDR 459.400 million, or 70%

contributed to the total variable costs of IDR 656.900 million. The average feed cost was IDR

7.293 ± 0.619 million ranging from IDR 1.250 million for rearing 2 goats and IDR 31.540 for

rearing 85 goats. The number of household labourers for rearing 2 and 85 goats were 2 and 3

labourers, respectively. This study revealed that the highest ratio household labourer to flock size

could cover the labourer as well as feed cost thus it was considered efficient in improving goat

production.

5.3.4.3 Health and disease control management

Although the incidence of anaemia was low, as indicated by the low average FAMACHA©

score

i.e. 1.8, households injected their goats with Klosan200™

(an anthelmintic) regularly. Kid mortality

was 8.6% or 519 kids survived until they reached weaning age at about 4.5 months (Figure 5.2).

Kids mostly died during parturition or in the early stages after birth. Health problems i.e.

metabolism disturbances, toxicity, bloat and scabies commonly occurred in preweaned kids born in

Rendang District. The feeding management resulted in growth rates for different physiological

states of goats, particularly preweaning kids with an average daily gain of 128 ± 3.6 g/d/kid (Tables

5.2 and 14 in Appendix 1). This low kid mortality and high daily gain potentially improved

efficiency of goat rearing in Rendang District.

5.3.4.4 Housing system

Goats were confined, almost all of the time, with feed and water brought whether into battery or

colony housing systems that were constructed from locally available materials. In the colony

housing systems, goats regardless of their physiological state were penned in groups on the ground.

This was the most common housing used for goats. The results showed that the ground was always

dry as dry branches of Caliandra calothrysus, Pennisetum purpureum, Artocarpus heterophyllus

and Sesbania sesban were spread over the floor in this housing system. The cost to build colony

housing was usually cheaper than battery housing, as the housing only needed a fence made of

wood, bamboo or bricks. In contrast, goats were housed individually in battery housing that usually

needed more wooden posts, bamboo and roofs. Households usually used bamboo or jackfruit trees

that grew freely in the conservation forest for the housing.

Most of the goat housing was located in front of the farmers‘ house, so observing the does‘ oestrus

often resulted in manageable breeding. The average weaning period was 135 days and does,

particularly those reared in battery housing, were usually re-mated as soon as the does had their

oestrus postpartum. Households paid more attention towards observing oestrus females that were


73


kept in individual or group battery pens, and households had to bring the bucks in to mate with

oestrus females at the appropriate time. However, does that were housed in colony housing were

mated by bucks, within the colony, particularly the dominant ones.

Thirty-four out of the 63 goat flocks used battery housing. A total of 724 and 445 goats were reared

in battery and colony housing, respectively. Thus the number of goats sold/year from battery

housing i.e. 11 ± 1.1 goats was not significantly different (P>0.05) from colony housing 11 ± 1.1

goats that resulted in the same pattern for the turn off rate as well as GM(A-B) and GM/doe

(P<0.05) (Tables 5.8 and 5.9). There were no differences of GM(A-B) and GM/doe for goats reared

in battery or colony housing systems, and results of this study showed that goats reared in colony

housing tended to have shorter average kidding intervals (Table 5.6) and to have heavier average

bodyweights (Table 5.10).

Overall, does had an average kidding interval of 244 ± 4.7 days or kidded three times in two years

(Table 5.2). The kidding interval of goats reared in colony housing was 238 ± 6.8 days, which was

shorter than those goats reared in battery housing, which was 249 ± 6.3 days, but this difference was

not significantly different (P>0.05) (Table 5.6). Results of this study indicate that the free access of

bucks to mate with does in colony housing allowed them to detect as well as to mate does that had

their first postpartum oestrus. This easy access may shorten the length of kidding intervals of goats

in colony housing.

The kidding interval of goats reared in the two housing systems were also not significantly different

(P>0.05) between the types of birth. However, does that had multiple kiddings tended to have the

longest period of kidding interval (253 ± 19.5 days), followed by does that had twins (244 ± 9 days)

and females that had single kids (243 ± 5.5 days) (Table 14 in Appendix 1).

There was no significant difference (P>0.05) between kidding intervals of does kept in the two

housing systems, however, does kept in colony housing tended to have shorter kidding intervals

than does kept in battery housing (Table 5.6).


74


Table 5.6 Effects of housing (battery and colony) systems on kidding intervals of different kidding

birth types of does reared in Rendang District, Karangasem Regency. No. of households Kidding interval (days)

Kidding interval (days) Battery Colony Battery Colony

Whole flock 120 76 249 ± 6.3a 238 ± 6.8b

Single 73 41 246 ± 7.5a 238 ± 7.5 b

Twin 43 24 251 ± 12.1a 232 ± 12.6 b

≤Twin 4 11 259 ± 7.4 250 ± 26.7c


Single 73 41 246 ± 7.5 238 ± 7.7

Female 39 15 238 ± 10.2 249 ± 18.6

Male 34 26 255 ± 11.0 231 ± 5.8


Twin 43 24 251 ± 12.1 232 ± 12.6

Female 14 5 259 ± 20.3 256 ±29.6

Male 14 9 239 ± 22.6 219 ± 18.6

Mix 15 10 255 ± 21.1 231 ± 21.2


≤Twin 4 11 259 ± 7.4 250 ± 26.7

Multiple Female 1 1 251* 231*

Multiple Male 2 1 267 ± 14.7 232*

Multiple Mix 1 9 253* 254 ± 32.9

*. Could not be computed because at least one of the variables was constant.

The length of kidding intervals between the different parities of does, was significantly different

(P<0.05), however, the length of kidding intervals of the different parities were not affected

significantly (P>0.05) by housing systems where the does were kept (Table 5.7).

Table 5.7 Effects of housing (battery and colony) systems on kidding intervals of different parities

of does reared in Rendang District, Karangasem Regency in 2014. No. of goats recorded Mean ± SEM

Housing system Kidding interval of does

Estimated age (month) Parity Battery Colony Battery Colony

12 - 20 1st - 2nd 44 28 264 ± 9.2a 241 ± 8.8a

21 - 29 2nd - 3rd 28 9 249 ± 12.9ac 262 ± 29.4abcdf

30 - 38 3rd - 4th 26 8 232 ± 12.1ac 226 ± 15.2abcdf

39 - 47 4th - 5th 6 8 294 ± 56.6ac 260 ± 37.9abcdf

48 - 56 5th - 6th 2 7 198 ± 45.2b 211 ± 11.5bcgd

57 - 65 6th - 7th 1 5 269* 229 ± 14.7cg

66 - 74 7th - 8th 1 3 244* 205 ± 24.8adfg

75 - 83 8th - 9th 1 3 192* 235 ± 61.7d

84 - 92 9th - 10th 1 1 192* 240e

All parities 1st - 10th 110 72 252 ± 6.6c 239 ± 7.3f


Means in a column with different superscripts differed significantly at the .05 level.

Both values GM(A-B) and GM/doe of does reared in battery and colony housings were not

significantly different (P>0.05) (Table 5.8) as well as were not significantly different (P>0.05) in

each of all four flock size categories (Table 5.9). Except in flock size 21≤30 goats, both values for

GM(A-B) and GM/doe of goats reared in colony housing tended to be higher than of goats in

battery housing. This indicated that the largest flock sizes in battery housing had opportunities to

sell more goats just prior to Eid Qurban.


75



GM(A-B) and GM/doe of goats reared in Rendang District, Karangasem Regency.

No. of households Battery Colony

Flock size (goats) Battery Colony Turn off rate (%)

1≤10 9 12 33 ± 11a 39 ± 9a

11≤20 9 10 35 ± 11a 40 ± 10a

21≤30 8 4 58 ± 11a 42 ± 16a

31≤85 8 3 56 ± 11b 74 ± 18b

1 - 85 34 29 46 ± 5 49 ± 7

Flock size (goats) Battery Colony Gross Margin (A-B) (IDR million)

1≤10 9 12 (0.592 ± 3.107)a (0.961 ± 2.691)a

11≤20 9 10 1.104 ± 3.107a 2.126 ± 2.948a

21≤30 8 4 12.330 ± 3.296b 3.645 ± 4.661b

31≤85 8 3 23.430 ± 3.296c 27.930 ± 5.382c

1 - 85 34 29 9.069 ± 1.601 8.184 ± 2.041

Flock size (goats) Battery Colony Gross Margin/doe (IDR million)

1≤10 9 12 (1.202 ± 0.678)ac (0.308 ± 0.587)a

11≤20 9 10 0.175 ± 0.678a 0.019 ± 0.643a

21≤30 8 4 1.426 ± 0.719bd 0.494 ± 1.017bd

31≤85 8 3 1.758 ± 0.719d 2.448 ± 1.175d

1 - 85 34 29 0.539 ± 0.350 0.663 ± 0.445




Determining how households in Rendang District housed their goats was important to see if housing

had any effect on productivity. Flock size, particularly the number of does owned by households,

significantly affected (P<0.05) the turn off rate, GM(A-B) and GM/doe of goats reared in Rendang

District (Table 5.9).

Table 5.9 Effects of housing (battery and colony) systems and flock size on labourer ratio, number

of does owned per household (does) and number of goats sold per household in Rendang District,

Karangasem Regency.

No. of households Battery Colony

Flock size (goats) Battery Colony Labourer to goat ratio

1≤10 9 12 3 ± 0.9a 3 ± 0.7a

11≤20 9 10 6 ± 0.9b 6 ± 0.8b

21≤30 8 4 9 ± 0.9c 9 ± 1.3c

31≤85 8 3 19 ± 0.9d 13 ± 1.5d

1 - 85 34 29 9 ± 0.4 8 ± 0.6

Flock size (goats) Battery Colony Number of does owned per household (does)

1≤10 9 12 3 ± 1.2a 3 ± 1.0a

11≤20 9 10 5 ± 1.2a 5 ± 1.1a

21≤30 8 4 8 ± 1.3b 8 ± 1.8b

31≤85 8 3 14 ± 1.3c 12 ± 2.1c

1 - 85 34 29 7 ± 0.6 7 ± 0.8

Flock size (goats) Battery Colony Number of goats sold per household (goats)

1≤10 9 12 3 ± 2.0a 3 ± 1.8a

11≤20 9 10 5 ± 2.0a 6 ± 1.9a

21≤30 8 4 14 ± 2.2b 9 ± 3.1b

31≤85 8 3 24 ± 2.2c 26 ± 3.6c

1 - 85 34 29 11 ± 1.1 11 ± 1.3




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This study revealed that the larger sizes of flocks, particularly the number of does owned by the

households, the larger values of GM(A-B) and GM/doe contributed to their income (Tables 5.8 and

5.9). This was due to the increased opportunity for does to produce kids and thus the opportunity

for sale of more goats.

The housing systems and the sizes of flocks owned per household were analysed for their effects on

bodyweights (Table 5.10). The average bodyweight of goats was not significantly different

(P>0.05) between the two housing systems, however, the average bodyweight of goats reared in

colony housing tended to be heavier. This was probably due to the largest flock sizes of goats

reared in colony housing were significantly higher (P<0.05) for the flock size 21≤30 goats and

tended to be higher for the flock size 31≤85 goats.

Table 5.10 Effects of housing (battery and colony) systems and flock size on 3,133 bodyweight

recordings of 1,169 goats reared in Rendang District, Karangasem Regency.

No. of bodyweights of goats recorded Bodyweights of goats (kg), Mean ± SEM

Flock size (goats) Battery Colony Battery Colony

1≤10 148 234 28.9 ± 1.1ae 27.6 ± 0.8a

11≤20 296 401 27.6 ± 0.8bdf 25.3 ± 0.7b

21≤30 540 301 25.1 ± 0.6ac 27.8 ± 0.8c

31≤85 957 256 25.7 ± 0.4de 25.9 ± 0.9d

1 - 85 1941 1192 26.1 ± 0.3cf 26.5 ± 0.4e


Table 5.10 shows a bodyweight pattern that larger flock sizes of goats both in battery and in colony

housing systems tended to have goats of lower bodyweights. This study revealed that the

bodyweight of goats in smaller flocks were significantly higher (P<0.05) than goats in larger flocks.

5.4 Discussion


Identifying the roles and the profiles of smallholder farmers involved in goat rearing under

smallholder production systems in Rendang District could be used to improve their goat production.

The average age of 40.5 ± 1.3 years of smallholder farmers was in agreement with the Act of the

Republic of Indonesia number 13 year 2003 concerning manpower that categorized ages as

productive between 15 years and 64 years. With the average length of their 10.6 ± 1.0 years of goat

rearing experience made them energetic enough to cultivate their crop farms integrated with goat

rearing (Table 1 in Appendix 1).

The size of land owned and cultivated in this study of 2 ha per household, along with the free access

to grow roughage in conservation forest, was bigger than the average size of land cultivated per

household in other Asian countries i.e. less than 2 ha with the smallest sizes of 0.3 to 0.6 ha


77


reported by Devendra (2007). It was also bigger than 0.3 to 0.5 ha cultivated per household by

smallholder farmers in Central Java (Suranindyah et al. 2009a; Suranindyah et al. 2009b) or 0.17 ±

0.03 ha, 0.31 ± 0.04 ha and 0.59 ± 0.08 ha owned by small ruminant farmers in lowlands, middle

zone, uplands of agro-ecological zones in Central Java, Indonesia, respectively (Budisatria et al.

2007). Unlike the typical smallholder farmers in Java Island that had limited land or were landless

(Budisatria et al. 2007; Suranindyah et al. 2009a; Suranindyah et al. 2009b), smallholder farmers in

Bali owned and cultivated their own land (Nitis 1997; Nitis et al. 2004). The ownership as well as

the size of land (2 ha) cultivated per households, only for growing crops using goat manure as

organic fertilizer by the smallholder farmers in Rendang District, were a major strength to

improving goat production as well as their crop farms. This result was confirmed by Hidayat

(2007) who reported that land and flock size were significant components that contributed to the

profits of IDR 6.219 million gained from integrated paddy, fish and goat farming in Banyumas

Regency in Central Java Province. The average GM(A-B) gained IDR 6.330 ± 1.626 million per

household from goat farming studied in Rendang District was higher than in Banyumas Regency

reported by Hidayat (2007). Cultivating 2 ha land per smallholder household in Rendang District

could be one of the development strategies that will help in improving their income by fertilizing

the land with organic fertilizer and selling more vegetable crops along with more goats.

The ratio of labourers to flock sizes had a strong positive effect (P<0.05) on turn off rate and

GM/doe. This study revealed that having more labourers per flock size did not necessarily mean

being more efficient or having improvements in production parameters. In contrast, having a

smaller flock size did not necessarily mean being less efficient or having negative values of

GM/doe. As long as the ratio of labourers to flock size could have sufficient numbers of goats sold

or had sufficient turn off rate i.e. at least 33.3% turn off rate, that covered their labourer cost, the

farmers could make positive GM/doe. However, 52% of the households in this study, had 3 to 6

labourers per flock and managed lower than 7.4 ± 0.7 goats per household. This was considered

inefficient in labour cost and thus reduced the GM(A-B) and GM/doe per flock. The four labourer

groups became a constraint to goat production in Rendang District unless they increased the size of

their flocks from a minimum of 22 to at least 44 goats per household (Table 3 in Appendix 1).

Results of this study revealed that labour cost was the second highest cost i.e. IDR 193.900 million

or 29.5% contributed to the total variable costs of IDR 656.900 million. The ratio of labourers to

goats managed as well as the flock size, particularly the number of does in the flock, had a strong

positive effect (P<0.05) on the value of GM/doe. Only when the ratio of labourers to the number of

goats managed improved above 7.4 ± 0.7 goats per labourer, and then it reduced the total variable


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costs and thus improved the efficiency of goat production. The value added estimates from small

ruminants per hour of family labour input in this study were higher than reported by Budisatria et al.

(2008) who calculated it to be 33-38% below the minimum wage labour rate

Although a household had the same size of flock, the GM/doe generated could be varied i.e. high

negative to high positive values. These values were affected by the number of does in the flock,

number of household labourers, number of goats sold, mortality rate, kidding interval, kidding rate,

weaning rate, feed costs and health control management costs. The results of this study revealed

that negative GM/doe were generated from small flock sizes that were kept for social rather than

economic reasons. Goats may be looked on as a security (a living bank) and households may

undervalue their labour inputs, perhaps because of unemployment. Other reason could be

households waited to sell their goats just prior to Eid Qurban for higher prices (Budisatria et al.

2008)

The cost of two family labourers in Rendang District was estimated as IDR 2.281 million annually.

Three kids needed to be produced and sold each year to cover the cost of the two labourers.

Therefore, having at least two does should be able to cover the cost of labourers or total variable

costs when it is assumed that does could produce kids three times in two years, for single type born

kids with zero mortality. Thus, the total variable costs for keeping two does was IDR 3.537 million

while the total income for selling manure and the three weaned kids was IDR 4.682 million. From

this, households could gain GM(A-B) IDR 1.145 million or GM/doe IDR 0.573 million annually.

This study revealed that as long as does could maintain three kiddings in two years, keeping at least

two does per flock they still could generate positive values of GM(A-B) and GM/doe annually.

However, to maintain profitable GM(A-B) and GM/doe from larger flock sizes, the ratio between

labourers per doe per flock size should be calculated carefully. A household should be able to

produce kids and sell at least a third of their flock size annually. This indicated that the minimum

annual turn off rate should be 33% per flock. To produce this number of kids, a household should

have at least 25% productive does with the assumption that does only deliver single type birth kids

every eight months with zero mortality rate. Simulation on how flock size and the number of does

owned affects the GM(A-B) (IDR million) and GM/doe (IDR million) is shown in Table 5.5.

The level of education of household labourers influenced significantly (P<0.05) the turn off rate,

GM(A-B) and GM/doe of goats reared in Rendang District (Table 4 in Appendix 1). This study

revealed that labourers who graduated from Grade 6 gained the lowest GM(A-B) of IDR 1.980 ±


79


1.236 million and had negative values of GM/doe. In contrast, labourers who graduated from Grade

12 gained the highest GM(A-B) and GM/doe as they had the largest flock size (24 ± 4 goats), the

largest number of does (8 ± 1 does) and the largest turn off rate (49 ± 10%).

This indicated that the households who had the highest education level had the ability to set up

profitable goat rearing programmes by having larger flocks (24 ± 6 goats) with sufficient numbers

of does (8 ± 1) per flock as well as the ability to manage their goat rearing (Table 5 in Appendix 1).

They also had the ability to sell more goats just prior to Eid Qurban for higher values of GM(A-B)

and GM/doe. This study revealed that the level of education of the household played an important

role in dictating higher production parameters. The level of household education per se would be

expected to improve the efficiency of goat production, but it is hypothesised that households with a

better education would implement improved husbandry practices.

In addition, 19% of the household labourers in Rendang District graduated higher than Grade 6 and

42% of them had been rearing goats from 10 to 34 years. This result was supported by Fuglie

(2010) who reported that the level of literacy and education in the Indonesian farm labour force,

made a modest but sustained contribution to Indonesian agricultural productivity growth. This was

confirmed with the hypothesis that farm workers who had a higher level of education-implemented

management practices that improved flock performance. Details of these management practices

will be outlined in later sections of this thesis.

The education level of household labourers i.e. 81% graduated from Grade 6 and 8% graduated

from Grade 12 in this study was lower than of household labourers in Tabanan Regency Bali

Province reported by Suciani et al. (2013). Suciani et al. (2013) reported that 46.7% of household

labourers graduated from Grade 12, while 33% and 20% of them completed their Grade 9 and

Grade 6, respectively. The education levels of household labourers in this study were also lower

than in Semarang City where Budiraharjo and Setiadi (2004) reported that 10.5% of household

labourers completed Grade 12. However, GM(A-B) gained by households in Rendang District

were higher than of households i.e. IDR 0.531 million per month in the Batungsel Village (Suciani

et al. 2013) or of households i.e. IDR 0.114 million per month, in Semarang City, Central Java

(Budiraharjo & Setiadi 2004). It may be assumed that increased education resulted in better

adoption of technology, innovational sector of economy and more efficient production (Netting

1993; Shindina et al. 2015). Beyond social importance, goat rearing under smallholder farming

systems in Rendang District had important impacts in the Bali economy on food production and job

generation as well as contributing to the income of smallholder farmers.


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To ensure that females in oestrus were mated at the correct time, farmers need easy access to a buck

(Devendra & McLeroy 1982; Devendra & Burns 1983; Peacock 1996; Jainudeen et al. 2000). This

indicated that unless bucks are well managed and transported between flocks lacking bucks, the

numbers of full-grown bucks in Rendang District should be at least 74 (i.e. 1 x 30 Small + 1 x 22

Medium + 2 x 11 Large flock size) instead of the 31–47 bucks recorded during the observations.

From the point of view of practical management, each goat farmer should have one to two bucks for

their larger flock size to mate with the 289 to 304 does. However, the relatively high average-

kidding rate of 157% and turn off rate of 44 ± 4% observed in this study indicates that the lack of

access to a buck was not a widespread problem.

The kidding rate of goats in this study i.e. 157% was lower than 173%, 183%, 196%, 172% and

169% for Alpine, LaMancha, Anglo-Nubian, Saanen and Toggenburg goats, respectively, reported

by Majid et al. (1993) or 234.1% for dwarf goats in south Côte d‘Ivoire reported by Armbruster and

Peters (1993) but slightly higher than 150% for Hungarian goats reported by Nemeth et al. (2004).

The result of this study was supported by Nemeth et al. (2004) who reported that increase in kidding

percentage could improve profitability.

The average mortality rate in the present study i.e. 9% was lower than the 25% mortality rate of

kids reared in Asian countries reported by Sherman (1998) or 18% to 23.5% in dairy kids reared in

Taiwan (Su et al. 2002) or 11.5% (ranging from 8.6% to 16.5%) in Angora goats in Africa (Snyman

2010). Results of this study indicate that high survival rates i.e. 143% of kids born in Rendang

District increased the efficiency of goat production. The results of this study were in agreements

with Perez-Razo et al. (1998) who reported that high survival rate of kids reared in Rendang District

minimized the cost of rearing as it resulted in more productive goats and thus provided more profit

to the households as more kids and goats sold. Maintaining good kid rearing management hence

high survival rates of newly born kids could be one of the development strategies that will help in

improving goat production in Rendang District.

The ratio of kid‘s deaths between females and males i.e. 1:1.2, mortality rate of twin born kids,

single born kids and triplet and quadruplets born kids in this study i.e. 63.3%, 26.5% and 10%,

respectively (Figure 5.2), were in agreement with Snyman (2010). Snyman (2010) also found that

mortality rate in male kids was slightly higher than that recorded for female kids while single-born

kids had the lowest mortality rate (10%), followed by twin born (13%) and triplet born (22%) by


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Angora kids. The present study indicated that households applied good rearing management,

particularly feeding a reasonable quantity and quality of feed to late pregnant females as well as

newborn kids that resulted in comparatively low (8.6%) kid mortality. This was supported by Paez

Lama et al. (2014) who reported that appropriate feeding management can enhance the physical and

metabolic development of the rumen (Paez Lama et al. 2014; Paez Lama et al. 2015) thus enabling

kids to achieve optimal growth rates thus increasing their productivity.

The average birth weight i.e. 3.1 kg and liveweight of does i.e. 40 to 42 kg (Figure 5.3 and Table

5.1) in this study were higher than of Gwembe Valley goats reported by Aregheore et al. (1992).

The Gwembe Valley goats had an average bodyweight before kidding of between 24 and 27 kg and

the mean birth weight of their kids ranged from 0.96 to 1.63 kg, reared in Zambia (Aregheore et al.

1992). These bodyweights were also higher than the bodyweights of Black Bengal does during the

month of conception that were 15.3 ± 0.5 kg; 17.1 ± 0.3 kg; 18.6 ± 0.7 kg and 21 ± 2 kg for bearing

single, twin, triplet and quadruplet kids pregnancy reared in India reported by Pan et al. (2015).

This study indicated that the high liveweight of does and birth weight of kids increased the

efficiency of goat production in Rendang District. This was supported by Delgadillo et al. (2007)

and Lopes et al. (2012) who reported that heavier birth weights of kids promoted an earlier age of

puberty and age at first kidding that simultaneously improved their productive and reproductive

performance thus increased profits to households.

The average bodyweight of preweaned male kids (10.6 ± 0.3 kg, n=404) studied in Rendang District

was not significantly different (P<0.05) from preweaned female kids (10 ± 0.2 kg, n=432).

However, the average daily gain of preweaned male kids 143 ± 4.7 g/d, n=197 was significantly

(P<0.05) higher than those for female kids 113 ± 4.6 g/d, n=207 (Figure 5.3). This was in

agreement with Ocak et al. (2006) who reported that male born kids showed faster growth rates than

females.

The average weaning weight i.e. 18.2 kg and average daily gain of preweaned kids i.e. 128.1 ± 3.3

g/d (Figure 5.3 and Table 5.1) in this study were slightly higher compared to those of Anglo-Nubian

crossbred kids (Praharani 2014). The results of this study were similar with those of the Etawah

kids reared in Java being 11 ± 0.1 kg, 14.7 ± 0.1 kg and 19 ± 0.1 kg for liveweight at 60, 90 and

120 days of age, respectively (Sodiq 2012). The birth weights and average daily bodyweight gains

of kids after the first month in this study tended to be higher than kids fed concentrate reported by

Sodiq (2012). The kids in this study probably ate the roughage or dagdag soup provided for mature

goats at their early ages. This indicated that these kinds of feeds or dam‘s milk had met the


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nutrients required by kids for their optimal growth after their first month of age. This was in

agreement with Tolu et al. (2009) who reported that the nutritional conditions in early lactation

were the critical points in terms of persistence of optimal growth after their first month of age.

The results in this study revealed that the average bodyweights of preweaned kids and their growth

rates improved the efficiency of goat production in Rendang District. This was supported by Luo et

al. (2000) who reported that the growth of kids prior to weaning is critical to their economic value,

as birth and weaning weights are related to kid survival and postnatal development. Furthermore,

this minimized the cost of rearing kids thus providing more profits to farmers (Malik et al. 1986).

The bodyweights and average daily bodyweight gains of kids in this study were comparable to

Etawah kids of the same ages, reared in Java (Sodiq 2012) and Anglo-Nubian crossbreds reared in

the Indonesian Research Institute for Animal Production in Bogor (Praharani 2014). Maintaining

persistence of optimal growth of goats studied in Rendang District could be one of the development

strategies that will help in improving their income.

Furthermore, the efficiency of goat production in Rendang District could be improved by paying

more attention to the two groups of does that mainly kidded in February (23%) and July 2014

(20%) (Figures 5.3 and 5.8). This study also revealed that kidding interval was about 8 months and

gestation period was about 5 months, therefore, some of the does that kidded in February would

have had kidding in October 2014. This indicated that in 2014 there would be three big groups of

kid born i.e. in February, July and October (Figure 5.8). Those does who kidded in July 2014

would have had kidding in March 2015 and in November 2015 whereas those does who kidded in

February and October 2014 would have had kidding in June 2015. Therefore, in 2015 there would

be also three big groups of kid born i.e. in March, June and November 2015. The timing of kids

born in year 2016 would have a similar pattern to 2014, and 2017 would have a similar pattern to

2015. By paying more attention to the season of birth, households in Rendang District were

expected to be aware on the length of the kidding intervals, days open as well as gestation periods.

The results of this study were supported by Meza-Herrera et al. (2012) who reported that by paying

more attention to the kidding season, households could anticipate for feeding and breeding

programmes as well as kid rearing management, particularly during parturition or the early stages

after birth. By paying more attention to the kidding season, households could reduce mortality rate,

thus increase efficiency of their goat production.

Having an average birth weight of 3.1 kg, average daily gain from day 1 to day 135 of 128 ± 3.6 g/d

and average daily gain from day 136 to 290 of 112 ± 3.2 g/d and comparable bodyweights of all


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physiological state of goats reared in Rendang District indicated that kid rearing management was

applied well. The growth rates of kids were also supported by their kidding seasons (Figures 5.4

and 5.5), and average rainfall (Figure 4.1). This indicated that sufficient rainfall provided sufficient

roughage for the does to produce adequate birth weights as well as to produce adequate colostrum

and milk for their newly born kids. At the same time, it also reduced stress to newly born kids from

wet and cool temperatures. This was in agreement with Meza-Herrera et al. (2012) who observed

that birth weights of 3.34 kg in spring were higher than 3.10 kg in winter for Boer X Anglo-Nubian

kids in Mexico. This physiological scenario could be the result of embryonic-foetal adaptive

responses representing homeostatic adaptations due to alterations including doe nutritional status,

available quantity and quality of food to both the embryo and the foetus as well as to a changing

external environment (Funston et al. 2010). This result was confirmed by Sandra and João (2016)

who reported that the kidding season that was supported by the sufficient availability of feed,

environmental and managerial conditions improved their reproductive performance, particularly

prolificacy.

Although late pregnant does gave birth in October and November when rainfall in Rendang District

were lower, they were fed sufficient quantity and quality of roughages and dagdag soup. This was

shown by their average of 41.5 ± 0.5 kg bodyweights for pregnant goats and the birth weight of kids

i.e. 3.1 kg and a weaning weight at day 135 i.e. 18.2 kg. This could be because pregnant does had

sufficient quantity and quality of the various roughages fed to meet their requirements. Increasing

the bodyweight profile of goats reared in Rendang District could be one of the development

strategies that will help in improving the efficiency of goats. This was supported by Delgadillo et

al. (2007) and Lopes et al. (2012) who reported that heavier birth weights of kids promoted an

earlier age of puberty and age at first kidding that simultaneously improved their productive and

reproductive performance thus increased profits to households.

The average kidding interval (Table 5.2) in this study were lower than those for PE crossbreds

reared in Bali Province observed by Sandi et al. (1989) who recorded 347 ± 66.2 days, 347 ± 64.2

days and 515 ± 46.6 days for single, twin and triplet born kids, respectively. These results were

also lower than in Kejobong goats reared in Central Java, Indonesia reported by Sodiq and Haryanto

(2007) (Table 2.8). The results were also lower than those in Boer goats i.e. 301 ± 9.9 days

observed by Elieser et al. (2012) or in Boerawa F1 crossbreds (288 ± 52.8 days), Boerawa

Backcrossed1 (276 ± 59 days) and Boerawa Backcrossed2 (272 ± 52.8 days) crossbreds reported by

Sulastri (2010) (Table 2.3). The relatively short kidding interval in this study revealed that the

breeding management applied in Rendang District contributed to the relatively efficient goat


84


production. This was supported by Abebe (2009) who reported that a shorter postpartum interval

will result in a shorter kidding interval that should not exceed 8 months (≤245 days) thus potentially

providing efficient goat production (Khanum et al. 2007; Sodiq & Haryanto 2007).

Households in Rendang District kept their does until their 10th

parity (Table 5.7) and keeping older

does, particularly aged between 75 to 92 months became a constraint reducing the production

parameters of goats reared in Rendang District. This was supported by Peacock (1996) who stated

that reproductive performance of does gradually decreased after reaching their 6th

parity. Devendra

and Burns (1983) also recommended to keep does up to their fourth or fifth kidding when does were

about 5 to 7 years of age for maximum litter size and efficient goat production.

The length of kidding interval in this study was supported by the length of days open that was about

3 months while the gestation period was about 5 months (Figure 5.4). The results in this study

indicated that smallholder farmers applied good breeding management of their goats. Managing

breeding plans, particularly the length of the days open improved the economic sustainability of

goat production systems in Rendang District. This result was supported by Mohamed et al. (2014)

who reported that hidden cost, particularly, days open cost was a huge part of operational cost in

goat farming. By managing the length of days open to be an average three months, farmers

improved the productivity of their goats and thus gained more profits.

Average kidding intervals in this study were shorter than of PE crossbreds reared in Central Java i.e.

320 days reported by Sodiq et al. (2004) or 267 days reported by Rianto et al. (2011). Achieving

kidding three times in two years for goats reared in Rendang District indicates that smallholder

farmers maintained good breeding management. This was in agreement with Lopes et al. (2012)

who reported that selecting does on kidding interval promoted simultaneous improvement in the

productive and reproductive traits. Maintaining an eight month kidding interval for does reared in

Rendang District could be one of the development strategies that will help in improving the goat

production by maintaining good breeding management thus improving their income.

The average flock size i.e. 17 ± 1 goats in this study was larger than 8 to 10 Kacang or PE goats per

flock reported by Fuah and Pattie (1992) in West Timor or a flock size of 3 to 5 goats per household

by smallholder farmers in Central Java (Suranindyah et al. 2009a; Suranindyah et al. 2009b). It was

also larger than reported by Budisatria et al. (2012) in three agro-ecological (down land, middle and

upland) zones in Central Java. This study revealed that the larger average flock size of 17 ± 1 goats

reared in Rendang District resulted in more efficient goat production. The flocks had better


85


proportions of does in the flocks, and the ratio of labourers to goats thus contributing higher GM(A-

B) and GM/doe per flock, compared to the reports of Fuah and Pattie (1992) and Budisatria et al.

(2012). This study revealed that by increasing the sizes of flock to 21≤30 goats and 31≤85 goats,

they increased GM(A-B) and this was confirmed by Singh et al. (2011) who reported that larger

flocks of goats achieved higher profits than small and medium flock sizes. Rearing larger flocks of

goats per household as well as owning at least 25% of does in their flocks in Rendang District could

be one of the development strategies that will help in improving goat production hence improving

their income.

As the proportion of does owned per flock strongly dictated the efficiency of goat production in

Rendang District, households mostly sold their male kids once they reached weaning with an

average bodyweight that ranged from 19.4 ± 0.8 kg to 23.5 ± 0.8 kg (Tables 6 and 7 in Appendix 1).

Thus, the numbers of female goats kept in flocks were higher than that of males as male kids were

sold earlier, as seen in Table 5.1. Results of this study showed that goat farmers maintained the

proportion of females that were similar at about 8 - 23% when they were I1 up to I4 dentition and

then decreased to be less than 4% when they were more than 6 years old. This indicated that

households were able to select productive females that had I0 dentition in appropriate proportions of

20–25% as replacements (Morand-Fehr et al. 2004).


This study shows that large flock size affected profitability, as there were more opportunities to

have a higher kidding rate thus the number of goats sold by smallholder farmers in Rendang

District, Karangasem Regency. Each household sold average 9.3 ± 1.2 goats in 2014 from the

average flock of 17 ± 1 goats where the average number of does owned was 6.3 ± 0.6 does. This

generated a 44 ± 4% average turn off rate for goats reared in Rendang District. Five hundred and

eighty seven goats in different physiological states were sold out of 1,169 goats that generated the

total income of IDR 15.063 ± 1.963 million per flock. This result was confirmed by Nemeth et al.

(2004) and Paez Lama et al. (2013) who reported that the growth and economic performance of

goat production was improved by improving the flock sizes.

Overall, if the assumption of having at least 25% of the flock were does in each household in

Rendang District was applied, there should be 290 does (25% X 1,169 goats) reared in Rendang

District. Assuming a doe produced single or twin kids three times in two years and a mortality rate

for kids was 10%, farmers should be able to produce and sell a total of 392 to 783 weaned kids, and

culled goats, annually or have about a 75% annual turn off rate. The number of does reared in


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Rendang District ranged from 240 to 304 does in 2014 (Table 5.1). This indicated flock dynamics

in Rendang District were maintained well. Therefore, farmers still had more goats to be sold prior

to Eid Qurban in 2014. Although the GM(A-B) and GM/doe of goat rearing by smallholder goat

farmers in Rendang District could potentially be improved, farmers kept goats as savings as they

also gained profits from their vegetables crops, particularly when the price of chillies increased.

The average total income i.e. IDR 16.757 ± 2.088 million generated from a flock size of 17 ± 1

goats with 6.3 ± 0.6 does owned per flock in this study were higher than 10 productive does and a

buck as reported by Suciani et al. (2013). The flock of 10 productive does and a buck contributed

to the Break Event Point (BEP) of about IDR 11.850 million annually to smallholder farmer‘s net

income in Tabanan Regency Bali (Suciani et al. 2013). The total income gained by smallholder

farmers in Rendang District were higher than IDR 0.531 million per month of smallholder farmers

in Batungsel Village (Suciani et al. 2013) or IDR 0.114 million per month of smallholder farmers in

Semarang City, Central Java reported by Budiraharjo and Setiadi (2004). Furthermore, when the

flock size of 21≤30 goats increased to 31≤85 goats, the total income also increased from IDR

21.830 ± 2.867 million to IDR 43.000 ± 2.994 million and resulted from an increase in the number

of does owned per flock from 8 ± 1 to 13 ± 1 does (Tables 2 and 12 in Appendix 1). This study

revealed that flock size and importantly the number of does owned dictated the efficiency of goat

production in Rendang District.

Turn off rate was significantly different (P<0.05) for flocks that had different numbers of labourers.

The only flock that had the largest number of labourers (6) or had a labourer ratio of 2.5 goats per

labourer had the lowest turn off rate of 13%. This was due to the flock (15 goats) having only one

doe, which resulted in negative GM(A-B) and GM/doe (Table 3 in Appendix 1). This indicated that

no matter how many household labourers there were, as long as the households had high labourer

ratios, they had more efficient goat production. Larger flock size, particularly having more

productive females in a flock was more important, to make a higher contribution to turn off rate,

GM(A-B) and GM/doe compared to the larger numbers of labourers per flock or type of housing

applied or level of education of the smallholders for these three production parameters.

To maintain annual positive GM/doe, the size of the flock, and importantly the proportion of does in

the flock, and their ratio of labourers to flock size strongly influenced production parameters. This

study revealed that kids born in 2014 in Rendang District only occurred in flocks that had at least

29.4 ± 0.70 goats. This study found that to sustain positive GM(A-B) and GM/doe, households had

to have at least a flock of 8 productive does that produced 24 kids in 2 years; so at least 12 kids


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were sold per year i.e. had a 37% turn off rate. Households who had these flock sizes were also

able to plan to sell goats just prior to Eid Qurban for higher profits.

Goat rearing under the smallholder production systems in Rendang District was characterized by

low external inputs, i.e. having household labourers and there were no external labourers on their

farms. It might be explained by the fact that the smallholder farmers calculated their own salary as

a part of their income, minimal cost of disease control, roughage planted in the conservation forest

and supplementary feeding using leftover vegetables that made dagdag soup. Both types of goat

housings were made from jackfruit trees or bamboo trees that were planted in the conservation

forest. The initial capital cost of having goats or rearing goats varied for the households.

Households received goats from their parents as heritage, while some shared goats with other

households within Rendang District. Households reared shared goats and when does kidded for the

first time, the first kids born belonged to the households and for the second kidding onwards, the

kids were shared half portions between the households and the goats owners. Other households

obtained their first goats through Bali Government Programmes/Aids.

Goat marketing in Rendang District was simple and direct with most of the transactions between

goat farmers and goat buyers occurring on goat farms. Goat buyers were categorised as four types:

breeder, meat retailers, satay sellers and occasional buyers. Households did not have any

constraints to marketing their goats. In contrast, they faced the challenge of fulfilling the demand

for goats within Bali Province, particularly for Eid Qurban celebration.

Meantime, the Department of Livestock and Veterinary Services, Bali Province reported that about

1,900 goats were slaughtered during Eid Qurban on 24th

September 2015 and it was an increased

demand of about 2% more than the previous year with increased prices about 20% to 40% more

than normal prices of goats sold. The Eid Qurban slaughtered goats were excluded from the 3,750

goats slaughtered monthly in 2015 in Bali Province (Anonymous 2015a). This increased demand

and prices due to the Eid Qurban were in agreement with the finding of Budisatria et al. (2008) who

noticed the market volume of small ruminants doubled and prices increased by about 25% in Java

Island where the majority was Muslim. It should be noted that the date for celebrating the Eid

Qurban festival advances about 5 days each year on the Gregorian calendar. This has implications

for breeding goats for sale. Furthermore, about 30 to 50 Mecaru goats were supplied by Rendang

District every October for the Balinese Hindu Purnama Sasih Kapat ceremony. This indicates that

households in Rendang District have the opportunities to respond to the high demand for goat meat

and Mecaru goats.


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Prospects for development of goat production are promising in Bali Province including in Rendang

District due to the abundance of feed resources and increasing demand for goats (BPS-Bali 2015)

(Table 4.4). Large numbers of goats were imported to Bali, particularly from NTB through Padang

Bay Harbour and East Java through Gilimanuk Harbour (Liestyawati, N. M. 2014, pers. comm. 11

April). The prices for goats sold for different purposes are given in Table 13 (Appendix 1).

Smallholder goat farmers in Rendang District updated the prices of goats and selling goats on farm

provided them a convenient marketing system. Thus, the ―one gate marketing system‖ that

maintained updated profitable market prices for goats created a strong position for farmers to dictate

market prices for their goats in Rendang District. All households interviewed in Rendang District

were members of a goat farmer association and they contributed money every month to form a

small cooperative. Smallholder farmers could borrow money with low interest rate in their

cooperative. Each of the members who needed money urgently sold his goats to the association

with the updated marketing price. The association then sold goats directly to buyers with an

updated marketing price. About 2.5% of goat selling prices are kept in their cooperative. This

system contributed higher incomes to their farmers among villages in Bali Province where other

farmers did not sell their goats through a goat farmers association. It was suggested that farmers

should have a ―one gate marketing system‖ to dictate market price as well as to have direct selling

to buyers. No households interviewed borrowed money from banks as capital for rearing goats;

therefore, no extra expenses were paid for bank interest.


Although bodyweight is an important economic trait in meat type animals, all households

interviewed in Rendang District were not sure how to predict the age of their goats and had never

weighed their goats even when they sold their goats. Furthermore, farmers had never recorded the

productive nor reproductive parameters of their goats. This is a constraint to rearing goats in

Rendang District as it means farmers have no data on how well their animals are performing.


Only 25% of the households that had flock sizes of 21≤30 goats and 31≤85 goats kept in battery

housing were able to produce and sell goat manure. The manure sold contributed IDR 106.671

million for the 63 flocks i.e. 10% to the total income of IDR 1,055.671 million. Goats that were

housed, their manure could only be collected from 80% of their production. The weight of the

manure then shrank by about 30% when it became organic fertilizer (Suharyanto & Rinaldi 2005).


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Goat manure is rich in nitrogen, phosphorus and potassium and is excellent manure for agricultural

production. Goat manure is considered cool, and it has a more balanced pH and less salt (Gaur et

al. 1990; Pagliari & Laboski 2012). The Indonesian Ministry of Agriculture reported that Indonesia

was only able to produce about 4.7 million tonnes of organic fertilizer or a third from the total

demand of 13.4 million tonnes of fertilizer in 2015 (Anonymous 2015b).

The daily goat manure production in this study was lower than reported by Suranindyah et al.

(2009b) who reported that an adult PE crossbred produced an average of 1 kg manure per goat per

day. However, this was higher than reported by Jingura and Matengaifa (2009) i.e. 0.4 kg manure

per goat per day or reported by Osuhor et al. (2002). Osuhor et al. (2002) reported that Red Sokoto

grazing native pasture and fed a concentrate supplement produced 0.38 kg and 0.37 kg manure per

goat per day for a buck and a doe, respectively, during the wet season. Corresponding values were

0.35 kg and 0.34 kg during the dry season where weights of adult does and bucks were 20 to 35 kg

and 25 to 40 kg, respectively. The birth weight of kids in this study i.e. 3.14 kg and 2.99 kg for

male and female kids, respectively, were higher than 2 kg and 1.5 kg of male and female Red

Sokoto kids, respectively (Osuhor et al. 2002). The average bodyweight for bucks i.e. 41.3 ± 0.5 kg

and adult females i.e. 36.8 to 41.5 kg in this study (Tables 6 and 7 in Appendix 1) were also higher

than reported by Osuhor et al. (2002).

The Simantri Programmes helped smallholder farmers in Rendang District to transform their

attitude from an ―animal keeper‖ to an ―animal producer‖ (Elisabeth 2012). Re-setting their goat

production goals will be one of the keys to improve their efficiency. This was in agreement with

Becx et al. (2012) and Gündoğdu (2012) who stated that entrepreneurship skills were required to

have an influence in shaping the quality of human resources thus having the ability to produce more

for markets, make a profit, increase possibilities to invest in inputs and new technology, and

increase overall productivity. Braker et al. (2002) added that to improve the efficiency of goat

rearing, smallholder farmers were expected to have a better understanding of the importance of their

location, the community, accessibility of knowledge and markets that dictated the success of the

commercialisation of livestock production.


The daily amount of a mixture of roughage fed to goats in this study was consistent with the

recommendation given by Peacock (1996). Freshly harvested leaves of Caliandra calothrysus were

generally highly palatable to ruminants where animals had prior experience with the forage and it


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had no known toxicities to ruminants. Caliandra calothrysus was high in protein, up to 280 g/kg,

(Kaitho et al. 1993). It also was high in condensed tannin contents, up to 11.07% (Ahn et al. 1989)

and reports of very high levels of proanthocyanidins, up to 200 g/kg (Jackson et al. 1996),

combined with relatively low nitrogen digestibility (< 43% ) (Ahn et al. 1989) and as a good source

of the vitamin carotene (Merkel et al. 1999) meaning that Caliandra calothrysus was an excellent

feed and highly adopted by households. Utilization of trees and shrubs has long been recognized to

be one of the most effective means of improving both the supply and the quality of forage in

tropical smallholder livestock systems (Gutteridge & Shelton 1994; Nitis 1999). The feeding

management applied by households in Rendang District resulted in reasonable bodyweights for all

physiological states (Tables 5.1, 6 and 7 in Appendix 1; and Figure 5.3).

Sesbania sesban was one of the exotic multipurpose fodder trees introduced to Bali Province for

livestock feed and soil conservation (Nitis 2006). Sesbania sesban was recognised across farming

systems for its production of relatively good quality feed (Nitis 2006; Oosting et al. 2011). For

example, long-term effect of supplementation of Sesbania sesban to male East African goats

improved their growth and reproduction performance (Kaitho et al. 1998). Utilization of trees and

shrubs had long been recognized to be one of the most effective means of improving both the

supply and the quality of forage in tropical smallholder livestock systems (Gutteridge & Shelton

1994) including in Bali Province (Nitis 2006). Leguminous fodder trees or shrubs have been used

to ameliorate feed constraints in developing countries and also to enhance soil fertility (Topark-

Ngarm & Gulteridge 1990).

The feed cost i.e. 70% was the largest cost that contributed to the total variable costs of IDR

656.900 million in this study was in agreement with FAOSTAT (2015) who reported that feeding

management was the most time consuming and costly for animal production. This finding was also

in agreement with Nemeth et al. (2004) who reported that the biggest costs were feedstuffs and then

labour. Free access to the conservation forest to grow various roughage as well as feeding their

goats with dagdag reduced the production costs thus improved the income of the smallholder

farmers in Rendang District. Free access to more conservation forest for planting roughage for

livestock feed by smallholder goat farmers in Rendang District could be one of the development

strategies that will help in improving goat production thus reduce feed cost.

Feeding goats with the leftovers from vegetable harvestings were a key livelihood resource for

households in Rendang District. This indicated that goat production in Rendang District reduced

crop residue allocations to soils with long-term implications for soil productivity. This was in


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agreement with Duncan et al. (2016) who reported that feeding crop residues to livestock does not

necessarily break the cycle of nutrient and biomass return to the soil since these can be returned in

the form of livestock manure. Goat manure provided a good source of relatively stable organic

carbon and of readily useable nutrients to improve soil fertility.


The housing management and the cutting time of roughages fed to goats reared in Rendang District

reduced the incidence of anaemia, particularly in the preweaned kids and weaners. This result was

supported by Grosso et al. (2016) who reported that maintaining hygienic housing systems

improved the efficiency of goat production. Furthermore, goat production improvements can be

achieved by adopting elevated housing systems for better internal parasite control (Haenlein &

Abdellatif 2004). Artocarpus heterophyllus, Gliricidia sepium, and Caliandra calothrysus and

herbaceous forages fed to goats in this study contained tannin as anthelmintic (antiparasitic)

properties against Haemonchus contortus worms (Kustantinah et al. 2014). The herbaceous forages

that were fed to goats had the potential to improve erythrocytic antioxidant status, cell mediated and

humoral immune response of goats (Pathak et al. 2017).

In addition, all households in Rendang District cut their roughage at least 50 cm above the ground,

and between 8.00 am and 12:00 noon. This was in agreement with Jones (1993) who reported that

about 80% of parasites lived in the first five centimetres of vegetation above the ground; therefore,

cutting the roughage above this height as well as cutting the roughages when the sun is strong

diminished the risk of parasite infection. Good health and disease control management of goats

reared in Rendang District promoted the improvement of goat production. This is supported by

Gunia et al. (2013) and Pathak et al. (2017) who reported that socio-economic health care and

sustainable eco-friendly disease control management substantially improved productivity of

individual animals, thus resulting in economic gains for smallholder goat farmers in an organic

environment.


Determining how smallholder farmers in Rendang District housed their goats was important to see

if housing (battery or colony) systems affected the productivity of their goats. Although the

numbers of does owned per household were lower, and there were fewer flocks housed in colony

housings than in battery housings, the goats tended to having shorter average kidding intervals and

heavier average bodyweights (P>0.05) in colony housings. Having shorter average kidding


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intervals and heavier average bodyweights for goats reared in colony housing in this study, could be

used as development strategies that will help in improving the productivity of goats.

Goats in small flock sizes reared in colony systems may lead to inbreeding, particularly when the

numbers of bucks were small, had high dominance order, or the bucks were used for a long time

(Peacock 1996; Jansen & Burg 2004). Putting goats into heterogeneous size or age groups in

colony housings may also have affected the weaker goat‘s ability to access feed, particularly when

feed provided were of insufficient quantity for all of the goats (Miranda-de la Lama & Mattiello

2010; Miranda-de la Lama et al. 2011). In contrast, smallholder farmers could pay more attention

to breeding and feeding management in battery housing systems. This was supported by Jansen and

Burg (2004) who reported that heat, mating, pregnancy and kidding of goats housed individually,

particularly in those of small flocks size could be manageable compared to large goat flocks reared

in colony housings. Martawidjaja (1992) recommended the construction of battery housing as the

internal environment is cool and dry thus providing a healthy environment to goats.

As battery or colony housing systems had their advantages and disadvantages, the results of this

study suggested that goats should be housed as a group in semi battery colony systems where

collecting goat manure would be easy. This was supported by Miranda-de la Lama and Mattiello

(2010) who suggested that goats should be housed in a group, homogenous in age or size for better

productivity. All goats studied in Rendang District, whether housed in battery or colony systems,

had access to shade or protection during the daytime, rain or cold nights that helped in improving

their productivity. This result was confirmed by Al-Tamimi (2007) and Daramola et al. (2012) who

reported that housing was a simple and efficient tool to minimise stress impacts as well as for

improving their welfare and thus improving their productivity.

5.5 Constraints to improving goat production in Rendang District, Karangasem Regency

The constraints to improving goat production in Rendang District, Karangasem Regency are:

The absence of does and bucks in the flocks;

A low ratio of household labourers to flock size;

Keeping old does too long on farms;

A lack of awareness on the objectives of goat keeping; and

Farmers having no records of their goats.

5.6 Challenges of improving goat production in Rendang District, Karangasem Regency

Challenges of improving goat production in Rendang District, Karangasem Regency are:


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To fulfil the demand for goat meat; and

Low feed costs due to free access to the conservation forest could potentially make Rendang

District a goat breeding centre

5.7 Opportunities for improving goat production in Rendang District, Karangasem Regency

Opportunities for improving goat production in Rendang District, Karangasem Regency are:

Strategies for having an additional source of income by selling goat manure;

Strategies for having an additional source of income by rearing Mecaru goats; and

Strategies for having an additional source of income by selling milk goat by introducing dairy

goats.

5.8 Conclusion

The results showed that goat rearing under smallholder production in Rendang District were

profitable. Goat rearing integrated with vegetable farming alleviated poverty, improved income and

created job opportunities providing food self-reliance and welfare for smallholder farmers.

Rearing management, flock dynamics, particularly the ratio of labourers to the number of goats

managed and kidding season significantly influenced productivity of goat production in Rendang

District. Crop farms integrated with goat rearing in Rendang District had positive impacts and met

the criteria for the development of sustainable agriculture by optimizing the use of local resources.

Bali Government allowed households to access the conservation forest to grow a mixture of

roughage for goat feed and this had tremendous impacts on the household‘s livelihood. Goat

rearing under smallholder production systems in Rendang District used minimal inputs and had

marketable products. The agricultural activity by the households in Rendang District could be one

of the answers to the pessimistic view of profitability on crop farms integrated with livestock, which

was coupled with rising land prices. These were conditions when capital investment in the

agricultural sector was not thought of as the best option in Bali Province. The agricultural activities

in Rendang District have played a vital role in ensuring food security, alleviating poverty,

improving household income, and conserving vital natural resources.

5.9 Suggestions

Suggestions include:

Providing the best quality of goat breeds such as Kacang, Etawah, Boer, Saanen, Anglo-Nubian

and their crossbreds as the top priority and could be made with collaboration between The

Indonesia Department of Agriculture in Bali Province, Department of Forestry, Bali Government


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and Research Institute for Animal Production (Balitnak-Ciawi). Government and Animal

Research Institutes have to empower smallholder goat farmers to promote the livestock industry

by encouraging smallholder goat farmers to undertake goat production for meat and milk. For

example, the package of Simantri Programme that consists of exotic goat breeds would be given

only to smallholder goat farmers that would milk their goats for either self-consumption or selling

for extra income.

By ensuring smallholder goat farmers rear dairy goats such as Etawah and Saanen goats, and as

such smallholder goat farmers could have goat milk for self-consumption as well as for

improving their income by selling goat milk.

By training smallholder farmers, to predict their goat‘s age based on the goat‘s teeth dentition

status (I0, I1, I2, I3, I4, toothless).

By keeping does only up to their fourth or fifth kidding, smallholder farmers could maintain does

for their maximum litter sizes and efficient goat production.

By re-composing the number of bucks and does in a flock as well as improving the flock size,

smallholder farmers could ensure that does will kid three times in two years.

By having a third of the flock as does, smallholder farmers could be able to have at least an

annual 33% turn off rate thus having positive values for GM(A-B) and GM/doe.

By practicing simple recordings of the productive and reproductive parameters of each individual

goat will enable smallholder farmers to analyse and to plan more efficient goat production.

By improving their existing feeding, and rearing management, particularly selection or breeding

management, could improve goat production in Karangasem Regency.

Smallholder goat farmers in Rendang District were members of a goat association as well as

members of a cooperative that helped them in marketing their goats and financial issues. By

marketing their goats through a ―One gate marketing system‖ that maintained updated profitable

market prices for their goats. In return, the farmers contributed about 2.5% of goat prices sold

through their system. This system had provided them a convenient marketing system and

provided more profits.

Optimization for optimum productivity is as follows:

1. The turn off rate needs to be sustainable. The sustainable turn off rate may be calculated as

follows:

Ntotal – the total number of goats in the flock (for example 20 head)

Ndoe – the total number of does of reproductive age in the flock (for example 12)

Nkidrate – kidding rate % (kids born per 100 does) (for example 150%)


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Nkidborn – total number of kids born (for example 18 = 12 x 150/100)

Nkidmortality – kid mortality rate (example 10%)

Nkidsale – kids available for sale (example 16.2% = [(100 – 10) x 10/100]

Nsustor – sustainable turn off rate for this example = 81% = 16.2/20%100

If the turn off rate is less than sustainable, the flock size will increase, putting pressure on feed

supplies and space. If the turn off rate is higher than the sustainable level, the flock size will

reduce.

2. Types of animals sold each year. The animals are sold to optimize the flock structure of the

remaining animals – the number of does, and the age profile of the does.

3. The time animals are sold and the age animals are sold can be optimized to maximize return to

the farmer.

4. Management is optimized to reduce mortality through disease, and to maximize growth rate

though good nutrition.

Chapter 6 Banjar, Busungbiu and Grogak Districts, Buleleng Regency

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Chapter 6

Current and future goat production in Buleleng Regency, Bali Province, Indonesia:

Case studies in Banjar, Busungbiu and Grogak Districts.

6.1 Introduction

Using the layout used in Chapter 5 as a template, factors influencing the efficiency of goat

production by smallholder farmers in Banjar, Busungbiu and Grogak Districts of Buleleng Regency

were assessed and are discussed in this chapter. Buleleng Regency had the largest goat population

in Bali Province (BPS-Bali 2015). Simantri, Social Aids and Assessment Institute for Agriculture

Technology (Primatani) Programmes motivate Bali farmers to improve their goat rearing

management (Elisabeth 2012). Case studies were conducted between 1st to 30

th March 2014 to

establish a database of current reproductive and productive efficiency of goat farming in Banjar,

Busungbiu and Grogak Districts as they contributed about 53% of the total size of Buleleng

Regency (1,365.88 km²) (BPS-Bali 2015). Innovative upgrading by crossing their goats with Boer

and Etawah Grade bucks improved the production of milk thus improved the GM(A-B) and

GM/doe of goats that were farmed in Buleleng Regency, particularly in Busungbiu District.

However, available literature presented little information on the improvement of goat production

under smallholder production systems in Buleleng Regency (Doloksaribu & Subagiana 2009). The

objective of this chapter was to establish a database of the reproductive and productive efficiency of

goat farming under smallholder production systems in Banjar, Busungbiu and Grogak Districts in

Buleleng Regency, as well as a socio-economic analysis of these systems. The database will be

used for establishing their future development strategies, through identifying their constraints to,

challenges of and opportunities for improving goat production in Bali Province.



adjustments. The 44 smallholder goat farmers studied in Banjar, Busungbiu and Grogak Districts of

Buleleng Regency encompassed five villages in three districts i.e. 7, 25 and 12 smallholder goat

farmers were in Banjar, Busungbiu and Grogak Districts, respectively. Busungbiu District that

covered three villages i.e. Sepang Kaja, Sepang Klod and Pucaksari Villages was hilly where

farmers grew crops such as coffee (Coffea spp.) or cacao (Theobroma cacao) integrated with goat

rearing. Banjar District, particularly in Gesing Village was located at the base of Abang Mountain

where farmers grew vegetables or fruits integrated with goat rearing (BPS-Bali 2015) (Tables 4.5

and 4.6). Grogak District, particularly in Sumberklampok Village that was located in coastal areas


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in the zone designated West Bali National Park, the livelihood of the Sumberklampok community

depended on local natural resources (Surata et al. 2014).

All 44 goat-owning families were interviewed, based on structured questionnaires, and 590 goats

were observed to obtain data i.e. breed-type, sex, age, dentition status (I0, I1, I2, I3, I4, toothless),

FAMACHA©

score, bodyweight, body measurements, birth type (single and multiple), and parity

were recorded over a month of direct animal observations. From the 590 goats, 323 kids were born

during the data collection. Data was only collected in March 2014; therefore, data on goat

reproductive performance was taken from the previous year. The average daily gain of goats reared

in Buleleng Regency was not available as the goats were only weighed once (Table 3.1). The

inputs included feeds, veterinary services, drugs, and labour cost i.e. labourers (from the family).

The outputs obtained included sales of live animals, milk, milk products; manure or goat products

consumed at home which were then converted into cash (IDR million). IDR 1 million was

equivalent to AUD$100.00.

6.3 Results




confirmed additional family members who were involved in goat rearing. In Grogak District, all

(100%) households interviewed were Muslims while in Busungbiu and Banjar Districts, all

households were Balinese Hindus who reared goats and occasionally Bali cattle as part of an

integrated agricultural farming system. One household graduated from University (score 4) and he

was the only one who sold fresh goat milk and milk products. He has been training and

encouraging other goat farmers in Busungbiu District for the last three years to produce fresh goat

milk as well as to manage its marketing. This study revealed that the level of education of the

household played an important role in dictating the best production parameters.

The households in the three districts interviewed had specific activities other than rearing goats. In

Banjar District, the farmers attended vegetable farms, fertilized soils, and marketed vegetable

produce. In contrast, in Grogak District, the farmers also reared Bali Cattle but they did not

cultivate any crops. In the season of coffee harvesting that usually runs from July to September, the

households in Busungbiu District usually worked cooperatively and their work rotated from one

farm to other farms. Household, kinship and household relationships of Balinese smallholder

farmers in Busungbiu District were interwoven with residence, labourer and the property of the


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farming systems. This relationship enabled them to rotate working hours in coffee plantations

during coffee harvesting. Meantime, land size cultivated in Busungbiu District was significantly

bigger i.e. 1.7 ± 0.1 ha (P<0.05) than 0.9 ± 0.3 ha and 0.6 ±0.2 ha in Banjar and Grogak Districts,

respectively while there were no differences in average number of labourers to flock size of 7 ± 1

goats among the three districts (P>0.05) (Table 1 in Appendix 1).

The effects of the number as well as the productivity of family labourers on turn off rate, GM (A-B)

and GM/doe of goats reared in Buleleng Regency will be further investigated in a later section of

this thesis. Production parameters of the 590 goats reared in Buleleng Regency is shown in Table 2

(Appendix 1). Approximately 0.5 hour per labourer per day was allocated to goat rearing or 180

equivalent working hours annually (Lagemann 1977; Muljadi et al. 1983; Supriadi et al. 2009) as

well as IDR 50,000 as a daily wage for a labourer who worked in agriculture (BPS Bali 2015).

Overall, the average of GM(A-B) and GM/doe for goat rearing by smallholder farmers in Buleleng

Regency were IDR (1.152 ± 1.499) million and IDR (0.086 ± 0.031) million, respectively when

they had 30 ± 5% annual turn off rate. Assumptions for the cost of inputs used for raising goats

included an average drench cost of IDR 0.040 ± 0.005 million and a feed cost of IDR 10.200 ±

1.156 million, and a labour cost IDR 2.345 ± 0.105 million. Assumptions for the price of outputs

used were the average price of goats sold was IDR 7.890 ± 1.811 million, price of manure sold was

IDR 1.210 ± 0.145 million and price of milk sold was IDR 2.013 ± 0.548 million.

Among the three districts studied in Buleleng Regency, only goat rearing by smallholder farmers in

Busungbiu District generated profits of IDR 2.662 ± 1.743 million and IDR 0.008 ± 0.036 million

for GM(A-B) and GM/doe, respectively, when they had 51 ± 6% annual turn off rate. In contrast,

Banjar District generated losses of IDR 1.547 ± 3.294 million and IDR 0.050 ± 0.067 million for

GM(A-B) and GM/doe when they had 26 ± 12% annual turn off rate. Grogak District generated

losses of IDR 4.572 ± 2.516 million and IDR 2.158 ± 0.051 million, respectively for GM(A-B) and

GM/doe when they had 11 ± 9% annual turn off rate. Banjar and Grogak Districts had turn off rates

that were half and a fifth lower than the turn off rate in Busungbiu District. This indicated that the

values of GM(A-B) and GM/doe for Banjar and Grogak Districts will potentially increase when

they increase their annual turn off rate or sell more goats prior to Eid Qurban (Table 2 in Appendix

1).

The households with three labourers or worked 547.5 hours/three household labourers/year had an

average flock size of 13.7 ± 3.5 goats, a turn off rate of 37 ± 12% and they tended to generate low


99


GM/doe of IDR (1.033 ± 0.070) but high GM(A-B) (P>0.5) (Table 3 in Appendix 1). The

households with three labourers had a significantly lower ratio of labourer to goats reared (4.7 ± 1.8

goats; P<0.05) than of the flocks with two labourers or one labourer i.e. 6.6 ± 1.0 and 12.8 ± 2.2

goats reared, respectively. The number of does owned, number of goats sold, prices of goats sold

and prices of milk sold per household were not significantly different in Buleleng Regency or

among districts (P>0.05). However, the three parameters of goat productions were significantly

different among districts where Busungbiu District was the highest for the three parameters and the

only district with positive values for both GM(A-B) and GM/doe (P<0.05) (Table 3 in Appendix 1).

This indicated that the higher numbers of household labourers resulted in inefficient labourer costs

when they reared small flocks.

Overall, the turn off rate, GM/doe, labourer ratio, number of does owned per household and prices

of milk sold per household of goat rearing by smallholders in Buleleng Regency were significantly

different between the education levels of the farmers (P<0.05) (Tables 4 and 5 in Appendix 1). This

study revealed that the household with the highest education level had the highest values of GM/doe

of IDR 0.034 ± 1.762 million and GM(A-B) of IDR 4.479 ± 8.813 million. This was partly because

the households with the highest level of education had the highest labourer ratio of 11.3 ± 4.5, the

number of does owned per household of 13 ± 5 does, and prices of milk sold of IDR 6.240 ± 2.747

million although they sold no goats in 2014 (Tables 4 and 5 in Appendix 1).


Smallholder goat farmers in Banjar, Busungbiu and Grogak Districts of Buleleng Regency reared

goats that were a mixture of Gembrong, Benggala, Kacang, Etawah Grade, PE, Boer, Boerawa and

their crossbreds or backcrosses (Plate 2.1). The number of females (430, mostly adult females) was

significantly more than the number of male goats recorded (160, P<0.05) (Table 6 in Appendix 1).

When the average body dimensions of goats of the same physiological state were compared, only

the body dimension measurements of male yearlings was significantly higher than those of female

yearlings (P<0.05) (Tables 6 and 7 in Appendix 1).

Among districts of Buleleng Regency, all average bodyweights of all physiological classes of goats

reared in Busungbiu District were the highest (P<0.05) (Tables 6 and 7 in Appendix 1) (Plate 2.1).

This was because the farmers had the objective of keeping dairy goats for better milk production by

crossing their goats with Boer and Etawah bucks that were imported from East Java Province. In

contrast, most of the PE crossbred goats reared in Grogak District had lowest of all the averages of

bodyweight and chest circumference (Tables 6 and 7 in Appendix 1; and Plate 2.1).


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The average flock size was 13 ± 1 goats and this ranged between 3 and 42 goats (Table 1 in

Appendix 1). There were 19 farmers who had the smallest flock size of 1≤10 goats and 17, 5 and 3

farmers who had larger flock sizes of 11≤20, 21≤30 and 31≤42 goats, respectively. There was no

statistical difference in flock sizes between districts (P>0.05).

Of 44 flocks in Buleleng Regency, 45% or 20 flocks had no mature bucks and 4.5% i.e. two flocks

had no does (Table 6.1). Of the 20 smallest flock sizes with ≤10 goats, 65% i.e. 13 flocks had no

bucks. As flock sizes increased, the number of flocks that had no bucks reduced; they were 37.5%

and 33% for the flock sizes of 11≤20 and 31≤42 that had no bucks, respectively (Figure 6.1).

Table 6.1 Flock sizes and average number of goats of different classes, owned per household in

Banjar, Busungbiu and Grogak Districts, Buleleng Regency. Class of goat Mean ± SEM, n=44 Range Minimum Maximum Mode

F preweaned 2 ± 0, n=93 9 0 9 0

F weaner 1 ± 0, n=29 3 0 3 0

F yearling 1 ± 0, n=57 7 0 7 0

F pregnant 3 ± 1, n=130 24 0 24 0

F lactating 1 ± 0, n=68 7 0 7 1

F dry 1 ± 0, n=53 8 0 8 0

M preweaned 1 ± 0, n=62 5 0 5 0

M weaner 1 ± 0, n=36 6 0 6 0

M yearling 1 ± 0, n=27 4 0 4 0

M buck 1 ± 0, n=35 5 0 5 0

Class of goat Mean ± SEM, n=44 Range Minimum Maximum Mode

All females 10 ± 1, n=430 38 0 38 6

All males 4 ± 0, n=160 10 0 10 1

Flock size 13 ± 1, n=590 39 3 42 5

The average number of pregnant females per flock was 3 ± 1 (Table 6.1; and Figure 6.1). There

were 251 does or 42.5% of the 590 goats recorded in the 44 flocks in March 2014. This indicated

that the replacement of does was about 37% as there were 93 preweaned female kids while there

were 62 preweaned male kids. In contrast, the number of male yearlings (average 1 ± 0) and female

weaners 1 ± 0 were the class with the least number of goats. Of 44 flocks in Buleleng Regency,

22.7% or 10 flocks had no pregnant females in March 2014. Of 20 smallholder farmers who had

the smallest flock sizes i.e. ≤10 goats, 40% had no pregnant females in March 2014. Of the two

largest flocks i.e. each with 42 goats, the ratio between female and male goats were 37 females to 5

males and 38 females to 4 males.

The average number of goats of different classes owned by households, regardless of their flock

size, is shown in Table 6.1. Figure 6.1 shows the same information based on flock sizes to illustrate


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that larger flock sizes owned by households were better than smaller ones, with the composition of

goat classes owned by household being important.

Figure 6.1 Flock sizes and average number of goats in different physiological state owned by

households in Banjar, Busungbiu and Grogak Districts, Buleleng Regency.

The numbers of kids‘ born, that died, survived, were sold or reared affected the production

parameters of goats farmed in Buleleng Regency. Kidding rate was 166%. In 2014, 323 kids were

born from 195 parturitions from 251 productive females that had I0/I1/I2/I3/I4 or toothless dentition

(Figure 6.4). The ratio between female and male kids born was 171:152. Of the 195 parturitions,

48% were twins (186 kids), followed by 44% single born (86 kids), 7% for triplets (39 kids) and 1%

were quadruplets i.e. 12 kids.


the first six months in 2014 in Banjar, Busungbiu and Grogak Districts, Buleleng Regency.

The kidding rate 177% (68 kids born per 38 does of reproductive age/year) in Banjar District was

the highest. This was followed by Busungbiu District with 137% (224 kids born per 164 does of


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reproductive age/year) and the lowest kidding rate was in Grogak District with 63% (31 kids born

per 49 does of reproductive age/year). Of the 323 kids born, an average of 3 ± 2 kids, n=12 was

born in colony housing in Grogak District, which was significantly lower than 9 ± 1 kids and 10 ± 2

kids in battery housing in Busungbiu and Banjar Districts, respectively (P<0.05).

The average kidding interval from 195 does that kidded from the first to the seventh parity was 242

± 5 days. This indicated that on average does had three kidding in every two years. Does with

triplet type birth kids had significantly shorter (P<0.05) average kidding intervals than those that

had single or twin type birth kids. Average kidding intervals were 243 ± 5 days, 244 ±9 days and

226 ± 22 days for single, twin and triplet kids, respectively.

Weaning rate (269 kids weaned per 251 does of reproductive age/year) was 107% for kids born

from the start of January to the end of March 2014 in Buleleng Regency. Kids reared in colony

housing in Grogak District tended to have a lower mortality rate 0.2 ± 0.6 or 3 kids (P<0.05) than

kids in Banjar with 1.6 ± 0.8 or 11 kids or for kids in Busungbiu District i.e. 1.6 ± 0.4 or 40 kids (24

female and 16 male kids). The higher kid mortality in Busungbiu District was mainly due to

predation by wild dogs. The average weaning period was 135 days and does, particularly those in

battery housing, were usually re-mated as soon as the does had their oestrus postpartum. Farmers

usually bathed their oestrus postpartum does to be re-mated as they believed that by bathing does,

the does were ‗fresher‘ and were more likely to eat more and to mate again. Farmers in Busungbiu

District usually fed their oestrus postpartum females with samblung leaves that they believed would

increase their does sexual desires.

Of 44 flocks observed in Buleleng Regency, 45% or 20 flocks had no bucks and 4.5% i.e. two

flocks had no does. Furthermore, another 10 flocks had no pregnant females in March 2014 and

these were major constraints to production of goats in the Buleleng Regency. Of the 20 smallest

flock sizes with ≤10 goats, 65% i.e. 13 flocks had no bucks. As flock sizes increased, the number

of flocks that had no bucks reduced; they were 37.5% and 33% for the flock sizes of 11≤20 and

31≤42 that had no bucks, respectively (Table 12 in Appendix 1).


Analysis of GM(A-B) and GM/doe from goat rearing by smallholder farmers in Buleleng Regency

were essential to determine the constraints to, challenges of and opportunities for rearing more

goats in more efficient management. The average of IDR 2.086 ± 1.634 million GM(A-B) and IDR

(0.408 ± 0.346) million GM/doe of goats reared in Buleleng Regency were generated from an


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average number of 5 ± 1 goats sold providing an average price of IDR 12.130 ± 1.893 million per

flock. Two-hundred and thirty-two goats were sold in Buleleng Regency with the total price of IDR

386 million or approximately AUD$38,600/44 flocks during the year 2014 (Table 2 in Appendix 1).

Values of GM(A-B) and GM/doe were determined largely by the average number of goats sold/year

at IDR 12.130 ± 1.893 million, then by the average milk sold of IDR 4.084 ± 0.349 million and

average manure of IDR 1.656 ± 0.115 million. Due to 36% of households not selling goats and

98% of farmers who had a turn off rate of <50%, GM(A-B) and GM/doe were relatively low.

Of 44 households in Buleleng Regency, 54.5% households had negative values of GM(A-B) and

GM/doe in 2014 (Table 2 in Appendix 1). Farmers who had a small flock size farmed goats as the

main source of fertilizer for crop growers as well as the ―living bank‖. They sold their goats

whenever cash was needed. The lowest GM(A-B) was IDR (13.281) million that was from having

34 goats with a 0% turn off rate when they were able to sell milk production, while the largest

GM(A-B) was IDR 46.665 million that was from having 42 goats with a 38% turn off rate.

The top 18 households for GM/doe had positive values for GM/doe (Table 11 in Appendix 1). The

largest GM/doe per household studied was IDR 2.346 million when the household had a flock of 24

goats that included 9 does, and they sold 20 goats and had a 83% turn off rate. This household

generated a total income of IDR 41.510 million and a gross margin of IDR 21.117 million. This

also indicated that a doe in a flock of 24 of goats generated IDR 2.346 million GM/doe. The top 20

for GM/doe indicated that the larger number of does owned per household, the larger amount

gained per doe per household. In other words, the number of does owned per household determined

the value of does in a flock.

However, the top 20 farmers for GM/doe in Buleleng Regency showed that the farmers sold from 0

to 32 goats and they had a range of 0 to 150% turn off rate. In contrast, the lowest GM/doe per

household in Buleleng Regency was a loss of IDR 8.434 million and a total income of IDR 0.639

million when the household had a flock size of seven goats including one doe in the flock and they

sold no goats in 2014.

Overall, total GM/doe was a loss of IDR 27.430 million with an average of IDR (0.623 ± 0.300)

million, ranging from a loss of IDR 8.434 million to a profit of IDR 2.346 million. Total milk sold

was IDR 95.040 million with an average of IDR 2.160 ± 0.476 million, ranging from nil to IDR

14.880 million that contributed 18% to the total income of IDR 558.900 million. Of the 590 goats

studied, 32 goats were sold in 2014 for the total price of IDR 386 million that contributed 72% to


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the total income (Figure 6. 4). Comparison of the GM/doe between the top 20 and bottom 20 across

the 44 households studied in Banjar, Busungbiu and Grogak Districts is shown in Table 6.2.



farms under smallholder production systems in Banjar, Busungbiu and Grogak Districts, Buleleng

Regency.

District No. of

goats

sold/year

Turn off

rate (%)

Flock

size

(goats)

Labourer

to goat

ratio

No. of

does

owned

(IDR million)

Total

income

Total

variable


Top 20

1 Banjar 20 83 24 12.0 9 41.510 20.393 21.117 2.346

2 Busungbiu 12 150 8 4.0 6 21.610 8.665 12.945 2.157

3 Busungbiu 18 86 21 10.5 9 36.736 18.194 18.542 2.060

4 Grogak 16 76 21 7.0 6 31.296 19.335 11.961 1.994

5 Busungbiu 10 77 13 4.3 6 21.066 13.471 7.595 1.266

6 Busungbiu 32 76 42 21.0 27 67.292 33.587 33.705 1.248

7 Busungbiu 8 80 10 5.0 5 15.812 10.131 5.681 1.136

8 Grogak 12 60 20 10.0 9 27.145 17.461 9.684 1.076

9 Busungbiu 8 62 13 6.5 5 17.586 12.330 5.256 1.051

10 Busungbiu 8 57 14 7.0 5 17.677 13.063 4.614 0.923

11 Busungbiu 6 75 8 4.0 3 11.230 8.665 2.565 0.855

12 Busungbiu 8 50 16 16.0 6 17.840 13.389 4.451 0.742

13 Busungbiu 6 86 7 2.3 6 13.019 9.073 3.946 0.658

14 Busungbiu 0 0 34 11.3 13 33.342 28.864 4.479 0.344

15 Busungbiu 4 80 5 2.5 2 6.956 6.466 0.490 0.245

16 Busungbiu 6 55 11 5.5 4 11.504 10.864 0.639 0.160

17 Busungbiu 8 50 16 8.0 3 14.960 14.529 0.431 0.144

18 Busungbiu 4 67 6 3.0 4 7.547 7.199 0.348 0.087

19 Busungbiu 0 0 5 2.5 0 0.456 6.466 (6.010) 0

20 Banjar 0 0 5 2.5 0 0.456 6.466 (6.010) 0

Bottom 20

1 Grogak 0 0 7 2.3 1 0.639 9.073 (8.434) (8.434)

2 Grogak 0 0 14 7.0 3 1.277 13.063 (11.786) (3.929)

3 Grogak 0 0 4 1.3 2 0.365 6.874 (6.509) (3.254)

4 Busungbiu 2 33 6 3.0 1 4.047 7.199 (3.151) (3.152)

5 Busungbiu 0 0 5 2.5 2 0.456 6.466 (6.010) (3.005)

6 Grogak 0 0 4 2.0 2 0.365 5.733 (5.368) (2.684)

7 Banjar 0 0 7 3.5 3 0.639 7.932 (7.293) (2.431)

8 Grogak 0 0 7 3.5 3 0.639 7.932 (7.293) (2.431)

9 Grogak 0 0 3 1.5 2 0.274 5.000 (4.726) (2.363)

10 Busungbiu 0 0 9 9.0 4 0.821 8.258 (7.436) (1.859)

11 Grogak 0 0 8 8.0 4 0.730 7.525 (6.795) (1.699)

12 Busungbiu 4 36 11 5.5 2 7.504 10.864 (3.360) (1.680)

13 Grogak 0 0 10 3.3 5 3.312 11.272 (7.959) (1.592)

14 Banjar 4 33 12 6.0 3 7.095 11.597 (4.502) (1.501)

15 Grogak 0 0 12 12.0 5 3.495 10.457 (6.962) (1.392)

16 Grogak 0 0 19 9.5 9 6.054 16.728 (10.674) (1.186)

17 Banjar 2 13 16 8.0 8 8.800 14.529 (5.729) (0.716)

18 Banjar 6 25 24 12.0 8 15.530 20.393 (4.863) (0.608)

19 Banjar 4 27 15 7.5 6 10.249 13.796 (3.547) (0.591)

20 Busungbiu 4 50 8 4.0 2 7.730 8.665 (0.935) (0.468)



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Of the 20 bottom households for the GM/doe, 13 households (65%) sold no goats, two households

sold two goats each, four households sold four goats each and only one household sold six goats

although almost half of them had flocks of more than 10 goats per household. The reason for these

households to be the bottom 20 for GM/doe were most farmers had less than 50% turn off rate.

This has a positive perspective because they were waiting to sell their goats that would result in an

increased GM/doe, just prior to Eid Qurban. The bottom 20 households for GM/doe, also indicated

that some smallholder farmers in Buleleng Regency could increase their GM/doe by selling more

goats prior to Eid Qurban. Overall, some of the bottom 20-smallholder farmers for GM/doe, in

Buleleng Regency had an opportunity to generate higher GM/doe compared to some of the top 20

smallholder farmers.

Figure 6.3 Flock size, annual turn off rate (%), GM(A-B) (IDR million) and GM/doe (IDR million)

based on four flock sizes of goats reared in Banjar, Busungbiu and Grogak Districts, Buleleng

Regency.

Figure 6.3 and Table 12 in Appendix 1 show that regardless of the housing systems used, five

households who had a flock size of 22 ± 1 goats when they had a 30 ± 7% turn off rate generated

GM(A-B) of IDR 12.712 ± 5.409 million and GM/doe of IDR 1.584 ± 0.636 million. The average

turn off rate for the 44 flocks was 36 ± 6% recorded in March 2014 (Table 12 in Appendix 1).


106



prices (IDR million) of goats reared in Banjar, Busungbiu and Grogak Districts, Buleleng Regency.

It was estimated that the average number of goats sold/year per flock in 2014 was 5 ± 1 goats with a

total income per flock of IDR 12.130 ± 1.893 million. Of the 590 goats reared in Buleleng Regency

in March 2014, it was estimated that 232 goats in different physiological states were sold with an

estimated price of IDR 386 million (Table 7 in Appendix 1).

Therefore, sale of goats was IDR 166.380 million per 100 goats per year or IDR 981.640 million for

the 590 goats reared in Buleleng Regency (Figure 6.4). Turn off rate was only an estimate as the

data was only recorded once for the first three months of 2014. It was an estimate as the data taken

from households was extrapolated from the numbers of goats sold/year and assuming that the

kidding interval was about 8 months.

However, households that sold no goats in March 2014 were also counted zero per cent for their

turn off rate at the end of year 2014 although households with large flock sizes were probably

waiting to sell their goats in early October 2014 prior to Eid Qurban.

On average, the largest number of goats sold/year were male weaners of 3 ± 1 goats. The average

number of female weaners and dry females sold were 1.8 ± 0.6 and 0.1 ± 0.0 goats, respectively.

There were no pregnant or lactating females sold. This indicated that male and female yearlings

and bucks were being kept to be sold just prior to Eid Qurban in October 2014. Thus, turn off rate

is likely to have been increased, particularly in those households that had the larger flocks.

It was estimated that the average number of goats sold/year per flock in year 2014 was 5 ± 1 goats

with a total income per flock of IDR 12.130 ± 1.893 million. Of the 590 goats reared in Buleleng

Regency in March 2014, it was estimated that 232 goats were sold with an estimated price of IDR


107


386 million. Therefore, sale of goats was IDR 166.380 million per 100 goats per year or IDR

981.640 million for the 590 goats reared in Buleleng Regency (Figure 6.4).

Total annual gross margin was IDR 0.871 million for the 232 goats sold or IDR 0.375 million per

100 goats per year. The average gross margin estimated for the 232 goats sold in 2014, for the 44

flocks, was 0.02 ± 1.371 million ranging from a loss of IDR 11.790 million to a profit of IDR

33.710 million. The GM/doe estimated in 2014 was IDR (27.427) million for the 232 goats sold or

IDR (11.821) million for 100 does and the average GM/doe was IDR (0.623 ± 0.300) million

ranging from a loss of IDR 8.434 million to a profit of IDR 2.346 million (Tables 6.1 and 2 in

Appendix 1).

Buleleng Regency had opportunities to respond to high demand for goat meat. The prices for goats

sold in Banjar, Busungbiu and Grogak Districts, Buleleng Regency for different purposes were the

same as the prices of goats sold/year in Rendang District that are given in Table 13 (Appendix 1).

Goat marketing in Buleleng Regency was simple and direct, and most of the transactions between

goat farmers and buyers occurred on goat farms. However, goat brokers were common, and as

such, there was a longer supply chain and this potentially reduced the possibility of gaining better

selling prices for goat farmers. High demand for Boerawa goats existed among goat farmers in

Buleleng Regency. Smallholder farmers did not have any constraints to marketing their goats. In

contrast, they faced constraints to fulfil the opportunities as well as the challenges to supply demand

for goats within Bali Province, particularly at Eid Qurban.



The first objective for smallholder farmers interviewed in Grogak District, to keep goats was to

utilise the benefits from free access to grow a mixture of roughages in the conservation forest.

Rearing goats was their only income resource. Growing roughage in the conservation forest

provided sufficient quantity and quality of roughages throughout the year for their goats and Bali

cattle. In return, goat manure was utilised to fertilize their plots.

All (100%) households interviewed in Buleleng Regency kept goats as a source of fertilizer to

improve soil fertility in their crop plantations. Farmers could also utilise the fodders trees that were

purposefully planted as shade trees in their coffee plantations as feed for their goats. By using the

goat manure, households reduced the production cost of their crop plantations. Although

smallholder farmers in Busungbiu District only used the goat manure as fertilizer, they had the


108


largest coffee production of about 9,000 tonnes in 2014 in Bali Province (Tables 4.5 and 4.6) (BPS-

Bali 2015).

Only 16% of the farmers with flock sizes of 21≤30 goats and 31≤42 goats, using battery housing, in

Busungbiu and Banjar Districts were able to sell goat manure. Farmers with large flock sizes were

also able to sell live goats for Eid Qurban for higher prices. Unlike in Rendang District,

smallholder farmers in Banjar, Busungbiu and Grogak Districts did not raise goats for Mecaru

purposes. Farmers in Buleleng Regency who had the larger flocks produced milk for self-

consumption or sold fresh goat milk for IDR 40,000 per litre. A lactating female could produce 250

to 500 ml milk daily. The only university-graduated farmers in Busungbiu District collected goat

milk from farmers and 75% of fresh goats milk was distributed to a boxing club and Bali Hindu‘s

ashram, and the remaining 25% was processed into cosmetics or snacks.

The manure sold generated IDR 53.837 million or contributed 10% of the total income of IDR

558.9 million while 20% i.e. IDR 95.040 million was generated from selling milk and 70% i.e. IDR

386million from selling live goats. In Buleleng Regency, some smallholder farmers raised goats

solely for breeding or fattening with or without integrated with crop plantations but none raised

goats for selling hides or meat/meat products.


Cut and carry feeding systems were the only system used in Buleleng Regency. All farmers

interviewed in Busungbiu District fed their goats with Caliandra calothrysus, Sesbania sesban,

Erythrina variegata, and Pennisetum purpureum that were purposefully planted as living fences or

as shade trees in coffee plantations. They also provided fermented coffee pulp or cacao pods and

pollard. In contrast, all farmers in Banjar District preferred cutting the field grasses, Artocarpus

heterophyllus or other bushes or Caliandra calothrysus, Sesbania sesban, Erythrina variegata, and

Pennisetum purpureum that were purposefully planted along the riverbank to feed their goats.

Dagdag soup was provided to goats. All farmers interviewed in Grogak District fed their goats with

Caliandra calothrysus, Gliricidia sepium, Pennisetum purpureum and kikuyu grasses that were

purposefully planted in conservation forest plots that were 0.25, 0.50 or 1 ha for each household.

Farmers estimated the amount of mixture of fresh roughage fed to their goats was about 5

kg/goat/day regardless of their physiological state. All flocks studied in Busungbiu District were

fed with a mixture of fermented coffee pulp or cacao pods with Aspergillus niger and pollard about

150 g per goat per day that were fed twice or three times in a week. Dagdag soup was also provided


109


twice or three times in a week. Concentrate starter feeds or commercial concentrates were never

given purposefully to the goats. Total feed cost for 44 households was IDR 454 million or 81.2%

contributed to the total income of IDR 558.900 million. The average feed cost for the three districts

was not significantly different (Table 2 in Appendix 1).


Predators of goats in Busungbiu District contributed to low values for goat productivity in Buleleng

Regency. Wild dogs, particularly in Busungbiu District, were the major cause of kid‘s deaths,

particularly during their first week until they were four weeks old. The wild dogs killed the newly

born kids, particularly when does gave birth at night in the middle of huge coffee or cacao

plantations. Forty kids or 74% of kids died before weaning in Busungbiu District for various

reasons i.e. wild dogs, stillborn kids, or they were the weakest in multiple kid births. Health

problems i.e. metabolic disturbances, toxicity, bloat and scabies commonly occurred in preweaned

kids in Buleleng Regency.

Farmers in Buleleng Regency never injected their goats with Klosan200™

(an anthelmintic) or any

medications to control diseases or parasites and this resulted in an average FAMACHA©

score of

2.1 for their goats. The average FAMACHA©

scores of goats reared in colony housing were

significantly higher i.e. 2.5 ± 0.1 than of goats reared in battery housing i.e. 2 (P<0.01).

FAMACHA©

scores of goats reared in colony housing had significantly higher scores in the first

two smallest average flock sizes of 3 ± 0 and 3 ± 0 and they were categorized as a ―warning‖ to pay

more attention on the housing/pen cleanliness (Table 6.7).


Goats were confined almost all the times, with feed and water brought to battery and colony

housing systems that were constructed from locally available materials. Of all households

interviewed in Banjar, Busungbiu and Grogak Districts, 27% or 12 households in Grogak District

reared 129 goats in colony housing while 73% or 32 households in Busungbiu and Banjar Districts

reared 461 goats in battery housing. Most of the goat housings in both Banjar and Grogak Districts

were located in front of the farmers‘ houses so observing if the does‘ were in oestrus was not too

difficult and often resulted in manageable breeding. However, in Busungbiu District all goats were

housed in battery pens that were located quite far from the farmer‘s house in coffee or cacao

plantations so that farmers sometimes missed observing females in oestrus that meant they missed

the opportunity to bring a buck to mate them.


110


In the colony housing systems, goats regardless of their physiological state were penned in groups

on the ground. The ground was always dry as branches of Caliandra calothrysus, Pennisetum

purpureum, Artocarpus heterophyllus and Sesbania sesban were spread to create the floor in this

housing system. However, rearing goats in colony housing was not as easy to collect goat manure

as in battery housings.

Table 6.3 Effects of housing (battery and colony) systems on annual production parameters of goats

reared in Banjar, Busungbiu and Grogak Districts, Buleleng Regency. Production parameters Housing system

Battery Colony

Mean ± SEM, n=32 Mean ± SEM, n=12

No. of goats sold/year 6.4 ± 1.1 2.3 ± 1.8

Turn off rate (%) 46 ± 6a 11 ± 10b

Prices of goats sold (IDR million) 10.580 ± 1.847 3.958 ± 3.016

Prices of manure sold (IDR million) 1.315 ± 0.159 0.981 ± 0.170

Prices of milk sold (IDR million) 2.460 ± 0.557 1.360 ± 0.910

Total income (IDR million) 15.100 ± 2.338 6.299 ± 3.817

Drenching cost (IDR million) 0.043 ± 0.005 0.032 ± 0.008

Roughage cost (IDR million) 10.520 ± 1.175 7.847 ± 1.918

Dagdag cost (IDR million) 0.520* 0.520*

Labour cost (IDR million) 2.281 ± 0.106 2.471 ± 0.173

Total variable costs (IDR million) 13.360 ± 1.189 10.870 ± 1.940

Gross Margin (A-B) (IDR million) 1.742 ± 1.546 (4.572 ± 2.524)

Gross Margin/doe (IDR million) (0.048 ± 0.313)a (1.103 ± 0.300)b *. Could not be computed because at least one of the variables was constant. N=Number of households

Means in a row with different superscripts differed significantly at the .05 level. Figures in brackets mean their values were negative.

Housing systems significantly affected turn off rate and GM/doe of goats reared in Banjar,

Busungbiu and Grogak Districts (P<0.05) (Table 6.3). None of the flocks reared in colony housing

had positive values for both GM(A-B) and GM/doe as they only had a 11 ± 10% turn off rate from

an average flock size of 11 ± 3 goats. In contrast, both GM(A-B) and GM/doe of goats reared in

battery housing had positive values as they had a 46 ± 6% turn off rate from an average flock size of

14 ± 2 goats (Table 6.3). This indicated that goats reared in colony housing, with a 11 ± 10% turn

off rate, had an opportunity for their owners to sell more goats prior to Eid Qurban.

There were no significant differences (P>0.05) in the average number of goats in different classes

owned per household reared between battery and colony housings in Banjar, Busungbiu and Grogak

Districts (Table 6.4).


111


Table 6.4 Effects of housing (battery and colony) systems on average numbers of goats in different

classes owned per household in Banjar, Busungbiu and Grogak Districts, Buleleng Regency.

Flock size and composition

Mean ± SEM

Battery, n=32 Colony, n=12

F preweaned 2 ± 0 1 ± 0

F weaner 1 ± 0 1 ± 0

F yearling 1 ± 0 2 ± 1

F pregnant 3 ± 1 2 ± 1

F lactating 2 ± 0 1 ± 0

F dry 1 ± 0 1 ± 0

M preweaned 2 ± 0 1 ± 0

M weaner 1 ± 0 1 ± 0

M yearling 1 ± 0 1 ± 0

M buck 1 ± 0 0 ± 0

Flock size 14 ± 2 11 ± 3

As more goats were reared in battery housing systems, more goats were sold (P>0.05) and had a

higher turn off rate (P<0.01) and higher average bodyweight (P<0.01) (Table 6.7). Thus generated

a higher GM/doe (P<0.01) and a positive value of GM(A-B) (P>0.05) compared to those goats

reared in colony housing systems (Tables 6.3 and 6.4 and 12 in Appendix 1). Households that

reared goats in colony housing with an average flock of 21 ± 2.4 goats provided the highest GM(A-

B) of IDR 11.960 ± 8.080 million and GM/doe of IDR 1.994 ± 1.627 million when they had the

highest turn off rate of 76 ± 33% (Table 6.5).


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Table 6.5 Effects of housing (battery and colony) systems and flock sizes on labour ratio, number of

does owned per household (does), number of goats sold per household (goats), prices of goats sold

per household (IDR million) and prices of milk sold per household (IDR million) in Banjar,

Busungbiu and Grogak Districts, Buleleng Regency. Mean ± SEM

No. of households Labourer to goat ratio


1≤10 13 7 4 ± 1 3 ± 1a

11≤20 12 4 7 ± 1 10 ± 1b

21≤30 4 1 14 ± 1 7 ± 3c

31≤42 3 0 18 ± 2 .*d

1 - 42 32 12 11 ± 1a 7 ± 1b

No. of households No. of does owned per household (does)


1≤10 13 7 3 ± 1 3 ± 1a

11≤20 12 4 5 ± 1 6 ± 1be

21≤30 4 1 8 ± 1 6 ± 3ce

31≤42 3 0 34 ± 2 .*d

1 - 42 32 12 10 ± 1a 5 ± 1b

No. of households No. of goats sold per household (goats)


1≤10 13 7 3 ± 1 0 ± 2a

11≤20 12 4 6 ± 2 3 ± 3ad

21≤30 4 1 12 ± 3 16 ± 5be

31≤42 3 0 12 ± 3 .*cde

1 - 42 32 12 8 ± 1 6 ± 2

No. of households Prices of goats sold per household (IDR million)


1≤10 13 7 5.732 ± 2.482 0 ± 3.383a

11≤20 12 4 10.080 ± 2.584 5.250 ± 4.475ad

21≤30 4 1 21.380 ± 4.475 26.500 ± 8.950be

31≤42 3 0 19.170 ± 5.167 .*cde

1 - 42 32 12 14.090 ± 1.929 10.580 ± 3.521

Prices of milk sold per household (IDR million)


1≤10 13 7 0.628 ± 0.464 0.343 ± 0.632a

11≤20 12 4 1.720 ± 0.483 2.760 ± 0.836b

21≤30 4 1 3.960 ± 0.836 2.880 ± 1.673c

31≤42 3 0 11.360 ± 0.966 .*d

1 - 42 32 12 4.417 ± 0.361a 1.994 ± 0.658b

* no flock sizes reared in battery housings

The highest average flock size of 39 ± 1 goats in battery housing (P<0.01) generated a higher

GM(A-B) of IDR 10.100 ± 4.665 million (P<0.05) and GM/doe of IDR 0.446 ± 0.939 million

(P<0.01) when they had the lowest turn off rate of 29 ± 19% (P<0.05) (Tables 6.6 and 12 in

Appendix 1). Both GM(A-B) and GM/doe for the smallest flocks reared in battery (6.8 ± 0.5 goats)

or colony housing (6.1 ± 1 goats) were negative although the turn off rate for the battery housing

was 24 ± 6% (Table 6.6).


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GM(A-B) (IDR million) and GM/doe (IDR million) of goats reared in Banjar, Busungbiu and

Grogak Districts, Buleleng Regency.

Flock size (goats)

Mean ± SEM

No. of households Turn off rate (%)

Battery Colony Battery Colony

1≤10 13 7 48 ± 9 0

11≤20 12 4 45 ± 9 15 ± 16

21≤30 4 1 55 ± 16 76 ± 33

31≤42 3 0 29 ± 19 -

1 - 42 32 12 44 ± 7 30 ± 13

No. of households Gross Margin (A-B) (IDR million)


1≤10 13 7 (0.836 ± 2.241) (6.726 ± 3.054)

11≤20 12 4 0.285 ± 2.332 (4.934 ± 4.040)

21≤30 4 1 8.219 ± 4.040 11.960 ± 8.080

31≤42 3 0 10.100 ± 4.665 -

1 - 42 32 12 4.443 ± 1.742 0.100 ± 3.178

No. of households Gross Margin/doe (IDR million)


1≤10 13 7 (0.444 ± 0.451) (3.208 ± 0.615)

11≤20 12 4 (0.051 ± 0.470) (1.358 ± 0.813)

21≤30 4 1 0.881 ± 0.813 1.994 ± 1.627

31≤42 3 0 0.446 ± 0.939 -

1 - 42 32 12 0.208 ± 0.351 (0.857 ± 0.640)


Regardless of the housing systems used, the average flock size in Buleleng Regency was 13 ± 1

goats (Table 7 in Appendix 1). When goat rearing was categorized based on housing systems, 32

households reared 461 goats in battery housing with an average flock size of 21 ± 1 goats that had

an average 23 ± 3% turn off rate. Goat rearing was examined based on housing systems and flock

sizes (Table 6.3). This indicated that the highest positive values of GM(A-B) of IDR 14.841

million and GM/doe of IDR 2.474 million were from a household that reared goats in colony

housing with a flock size of 21 goats with a 38% turn off rate. Bigger flocks of 22.7 ± 0.7 or 39.3 ±

2.7 goats reared in battery housing generated smaller GM(A-B) of IDR 13.463 ± 17.604 million and

GM/doe of IDR 0.311 ± 0.795 million as they had a smaller i.e. 14 ± 12% turn off rate. In contrast,

the smallest GM(A-B) of IDR (6.384 ± 0.480) million and GM/doe of IDR (3.140 ± 0.920) million

were from the smallest flock size of 6 ± 1 goats with a 0% turn off rate.

In contrast, 12 households reared 129 goats in colony housing with an average flock size of 14 ± 0

goats that had a 6 ± 4% turn off rate which generated GM(A-B) of IDR (3.212 ± 2.443) million and

GM/doe of IDR (1.958 ± 0.797) million (Table 11 in Appendix 1).

Overall, the average bodyweight of goats reared in battery housing systems was significantly higher

than in colony housing systems (P<0.01) (Table 6.7). In each housing system, the larger the flock


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sizes, the bodyweights of goats were significantly lower (P<0.01) except for the 31<42 goat flock,

reared in battery housing, that had the highest bodyweights (Table 6.7).

Table 6.7 Effects of housing (battery and colony) systems and flock size on average bodyweights

and FAMACHA©

scores of 590 goats reared in Banjar, Busungbiu and Grogak Districts, Buleleng

Regency.

Flock size (goats)

No. of animals

Mean ± SEM

Battery Colony

Battery Colony Bodyweights of goats in Buleleng Regency

1≤10 89 32 27.3 ± 1.4 26.9 ± 2.3

11≤20 163 76 25.6 ± 1.0 22.4 ± 1.5

21≤30 91 21 25.1 ± 1.3 17.7 ± 2.8

31≤42 118 -- 32.4 ± 1.2 --

1 - 42 461 129 27.6 ± 0.6a 22.3 ± 1.3b

Flock size (goats)

No. of animals Battery Colony

Battery Colony FAMACHA© score of goats in Buleleng Regency

1≤10 89 32 1.9 ± 0.1 2.6 ± 0.1

11≤20 163 76 2.0 ± 0.1 2.7 ± 0.1

21≤30 91 21 2.1 ± 0.1 2.1 ± 0.2

31≤42 118 -- 2.0 ± 0.1 --

1 - 42 461 129 2.0 ± 0.0a 2.4 ± 0.1b

Means in a row with different superscripts differed significantly (P<0.01).

6.4 Discussion



smallholder production systems in Banjar, Busungbiu and Grogak Districts could be used to

improve their goat production (Table 1 in Appendix 1). Although every household studied in

Buleleng Regency cultivated an average of 1.2 ± 0.1 ha integrated with goat rearing of various flock

size, not all of them owned the land. In the three districts studied in Buleleng Regency, 41% of the

households did not own the land where they cultivated crops. They cultivated the shared land and

shared the crop production with their landowners but not the production of their goats. Those

farmers who shared land were 11 farmers (44%) from Busungbiu District and seven farmers (100%)

from Banjar District. In contrast, all 12 farmers (100%) cultivated their own land where they only

grew a mixture of roughage for their Bali cattle and goats.

The smallholder farmers planted Caliandra calothrysus, Sesbania sesban, Erythrina variegata, and

Pennisetum purpureum purposefully as shade trees or as living fences in their coffee or cacao

plantations to optimize their crops. Since goat production was not shared, the households limited

the size of their goat flocks based on the amount of the shade trees to provide sufficient feeds

required by their goats. Sometimes, the goats reared could not produce sufficient amounts of

manure required to fertilize their crops. However, the farmers had to be realistic about keeping

their flocks small due to the availability of roughages as well as the low number of household


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labourers available to rear an average flock of 13 ± 1 goats integrated with 1.2 ± 0.1 ha for crops.

Goat rearing integrated with shared land for crop plantations by smallholder farmers could be a

constraint to goat production, particularly in Busungbiu District.

The ratio of labourers to flock sizes had a strong positive effect (P<0.05) on GM/doe. This study

revealed 16% of the households had three labourers per household, and had a ratio between labourer

and flock size lower than 7 ± 1 goats per labourer which was considered inefficient in labour cost

and thus reduced the GM(A-B) and GM/doe per flock. The households who had three labourers

were inefficient although they had more than 33% turn off rate (Table 3 in Appendix 1).

Of the inefficient labourer ratios, 62.5% of them were in Busungbiu District who graduated from

Grade 6 and they had shared land. They did not have the authority to increase their flocks nor to

grow more roughage in coffee plantations. Even if they were given the authority by the

landowners, they did not have sufficient household labourers to cultivate the size of land as well as

to rear larger flocks. In contrast, the households with one labourer had a significantly higher

labourer ratio of 13.4 ± 2.1 goats reared per labourer (P<0.05), and they had made less than a 33%

turn off rate. This indicated that they had opportunities to gain more profits by selling more goats

prior to Eid Qurban (Table 3 in Appendix 1).

This study revealed that labourers who had the highest education level had the highest ratio of

labourers to goats with a sufficient proportion of does and bucks to produce more milk and more

kids (Tables 4 and 5 in Appendix 1). The farmer also had the ability to set a plan of selling the

highest milk production (P<0.05) to cover the production costs due to having the highest number of

does owned per flock (P<0.05), and the lowest labourer ratio to flock size (P<0.05) (Tables 4 and 5

in Appendix 1).

Furthermore, GM(A-B) and GM/doe were significantly higher although zero goats were sold but

they had significantly higher prices for milk sold (P<0.05). This result was confirmed by Patil et al.

(2009) who reported that dairy farmers in Nagpur District of Maharashtra State, with a medium

level of knowledge, were significantly and positively correlated with socio-economic variables such

as education (0.437), herd size (0.486), annual income (0.445), daily milk production (0.583), daily

milk sales (0.486), and social participation (0.500). This was also confirmed by Azizi and Moayedi

(2012) who reported that having a broader viewpoint as well as having a higher education level was

a prerequisite for having the ability to turn problems into opportunities. Having an educated

smallholder farmer i.e. one who had graduated from university who encouraged other farmers to


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milk their goats in Busungbiu District could be one of the development strategies that will help in

improving milk production thus improving their income by selling more kids as well as milk and

milk products.


Decisions to keep certain breeds or crossbred goats was related to the objectives of keeping goats

which significantly influenced improvements in productivity of goats reared in Buleleng Regency.

The smallholder farmers in Busungbiu District who upgraded their goats by crossing them with

Boer and Etawah bucks showed this. All average body dimensions i.e. bodyweight, chest

circumference, height at withers and rump height of Boerawa crossbred goats reared in Busungbiu

were significantly higher than of goats reared in Banjar and Grogak Districts (P<0.05) (Tables 5 and

6 in Appendix 1). Goats reared in Busungbiu were categorized as Large goat type while in Banjar

and Grogak Districts, they were Small goat type according to Devendra and Burns (1983) and none

were categorized as Dwarf goat type. The average height at withers of goats reared in Busungbiu

District i.e. 66.1 ± 0.6 cm was significantly higher (P<0.05) than those reared in Banjar District i.e.

62.0 ± 1.1 cm or in Grogak District i.e. 56.7 ± 1.0 cm. The height at withers of goats reared in

Busungbiu District indicated that they had higher productivity than those reared in Banjar and

Grogak Districts (Devendra 1985b; Abebe et al. 2010). This result was also confirmed by Singh et

al. (2011) who reported that improved breeds of goats had positive impacts on the income of goat

keepers.

The upgrading programmes by smallholder farmers in Busungbiu District enabled them to sell

heavier weaned kids thus providing higher GM(A-B) and GM/doe (Table 2 in Appendix 1). Except

for pregnant and lactating does, all bodyweights of all physiological classes of goats reared in

Busungbiu District were the heaviest among districts in Buleleng Regency (Table 7 in Appendix 1).

Lower bodyweights for pregnant and lactating does reared in Busungbiu compared to those reared

in Banjar District, was probably due to the fact that most of the does reared in Banjar were in their

late pregnancy and or early lactation.

All bodyweights of all physiological classes of goats reared in Busungbiu District (Table 7 in

Appendix 1) were within the range of the required physical standard of PE breeding stock by

Indonesia National Standard (SNI 2008). This indicates that it was a good time to expand the

number of goats in Busungbiu District as good breeding stocks were being farmed. Expanding

quality-breeding stock could be one of the development strategies that will help in improving their

goat production.


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Most Boerawa crossbred goats reared in Busungbiu District had large bodies and floppy medium

ears that are well known with high milk production. The farmer who had the highest education

level processed the goats‘ milk that was collected from smallholder farmers in Buleleng Regency

and then distributed the goat milk and milk products to consumers. Encouraging goat farmers to

milk their goats improved their goat production and thus improved their income. This was

supported by Arya (2014) and Arya et al. (2014) who stated that commodity plantations integrated

with goat rearing improved farmer‘s income in Busungbiu District. Abebe (2009) and Momani et

al. (2012) reported that crossbreeding goats improved their growth rates and milk production and

larger size goats usually produced more meat and milk than smaller ones.

This was also supported by Adhianto et al. (2013) who reported that Boerawa does had high

productivity to improve litter size, birth and weaning weights and reduce pre-weaning mortality and

thus improve efficiency of goats reared in Buleleng Regency. Suggestions by Morris et al. (2011)

that in future, genetic relationships among the bodyweights of does and their productivity for

growth traits as well as kidding interval, kidding and weaning rates or litter size traits and

particularly for the herd-test milk traits should be investigated in large herds of goats reared in

Busungbiu District. These factors can contribute to overall sustainability and long-term economic

profitability of animal production (Morris et al. 2011) in Buleleng Regency, particularly the

smallholder farmers in Busungbiu District for potentially gaining more income from selling goat

milk and milk products. This was possibly partly due to the farmer who had the highest education

level. This indicates that through goat rearing experiences, by smallholder goat farmers in

Busungbiu District, when farmers were educated and positive about trying new innovations, they

improve goat productivity (Huffman 2001; Huffman & Orazem 2007; Moayedi & Azizi 2011;

Azizi & Moayedi 2012).

Among districts in Buleleng Regency, goats owned by smallholder farmers in Grogak District had

the lowest bodyweights of all physiological classes (P<0.05) (Tables 6 and 7 in Appendix 1). The

farmers in this district also had the smallest land to cultivate roughage integrated with their goats as

well as the shortest experience in goat rearing (P<0.05). Although they were not significantly

different, the farmers in Grogak District tended to have the low ratio of labourers to the number of

goats, flock size, farmers education level and lower numbers of children (P>0.05) (Tables 1 and 2 in

Appendix 1). As they had the lowest turn off rate i.e. 11 ± 9% (P<0.05), they also had the lowest

GM/doe (P<0.05) and GM(A-B) (P>0.05). However, they had an opportunity to have higher

positive GM(A-B) and GM/doe when they sold more goats prior to Eid Qurban.


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Although the bodyweights of all physiological classes of goats reared in Grogak District were lower

than the range of the required physical standard of PE breeding stock by Indonesian National

Standard (SNI 2008), farmers in Grogak District did not face problems with marketing their goats.

All farmers studied in Grogak District were Muslims; they had good goat businesses with some

mosques located in Denpasar City to supply as many goats as possible prior to Eid Qurban.

The farmers in Grogak District had experience that this small body type goat with short floppy ears

survived and had good growth rates in high temperatures and the humid climate of Buleleng

Regency where there was low quantity and quality of roughage, particularly in dry seasons. Earlier

studies reported that the Kacang goat was the most common native breed of the Indonesian goat

adapted to the local environments of some regencies in Indonesia. Kacang goats have shown their

growth rates and potency under different smallholder production systems in Bali Province (Mantra

1991) as well as in Java (Sodiq et al. 2010). In Bogor Regency the reproductive performance of

Kacang goats were comparable to PE crossbreds maintained on low quality feed with and without

supplementation (Chaniago 1988). Kacang goats reared in East Kalimantan showed birth weights

of 2.2 kg with an average litter size of 2.7 kids; and a kidding interval of 7-8 months (Wiesner &

Hadinoto 1987). In West Timor mature Kacang goats had 20 to 28 kg bodyweights with high

fertility and generally less than 13% kid mortality (Fuah & Pattie 1992). This indicates that rearing

this small body type goat is an economically effective option as Kacang goats are well adapted

under smallholder production systems in Indonesia‘s humid tropics. In the last two decades,

however, Research Institute for Goat Production (Sungei Putih) has been conducting research on

improving Kacang goats by crossing them with Etawah and Boer bucks and this has resulted in

Boerka and Boerawa crossbreds that showed improved productivity (Mahmilia & Tarigan 2004;

Elieser et al. 2006; Mahmilia 2007; Mahmilia & Elieser 2008; Mahmilia et al. 2009; Mahmilia

2010; Mahmilia & Doloksaribu 2010; Mahmilia et al. 2010). In future, smallholder farmers in

Grogak District could rear Boerka and Boerawa goats as well. Rearing upgraded goat breeds that

have high productivity in Indonesia could be one of the development strategies that will help in

improving their goat production.

The average of 242 ± 4.7 days kidding interval in this study was significantly different (P<0.05)

between single and multiple type birth kids where does with multiple type birth kids had

significantly longer kidding intervals than those that had single birth kids. Average kidding

intervals of this study were shorter than in PE goats reared in Bali Province (Sandi et al. 1989) and

in Kejobong goats reared in Central Java Indonesia (Sodiq & Haryanto 2007). This kidding interval


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was also shorter than 301 ± 9.9 days in Boer goats (Elieser et al. 2012) and in Boerawa F1 i.e. 288.3

± 52.8 days, Boerawa BC1 i.e. 276.3 ± 59 days and Boerawa BC2 i.e. 271.8 ± 52.8 days (Sulastri

2010). The length of kidding interval in this study revealed that the breeding management used in

Buleleng Regency was a strength of the productivity of goats reared. This was supported by

Greyling and Vanniekerk (1991) who reported that of all the production parameters, kidding

interval was of major economic importance for optimal reproductive performance.

The average mortality rate of 17% observed in the present study was lower than the 25% mortality

rate of kids reared in Asian countries reported by Sherman (1998) or 17.6% to 23.5% in dairy kids

reared in Taiwan (Su et al. 2002). Mortality rate in the present study, however, was higher than in

PE kids i.e. 4.9% (Utomo et al. 2005) or Boerawa kids i.e. 6.5% Adhianto et al. (2013) or Angora

goats in Africa i.e. 11.5% (ranging from 8.6% to 16.5%) (Snyman 2010) or 8.6% in Rendang

District. High kid‘s mortality rate in this study was a major constraint of goats rearing in Buleleng

Regency.

The ratio between female and male kid‘s deaths in the present study was 30:24, i.e. 1.25:1 while the

highest rate of mortality was 50% for twin born kids followed by 20% for single born kids and the

remainder was about 17% for quadruplets and 13% for triplet born kids (Figure 6.4). However,

Snyman (2010) found that mortality rate in female kids was lower than that recorded for male kids

(11.1% vs. 11.9%) while single-born kids had the lowest mortality rate (10%), followed by twin

born (13%) and triplet born (22%) of Angora kids. The present study indicated that smallholder

farmers have to pay more attention to wild dogs as predators. Late pregnant females, particularly

prior to their parturitions, as well as remote goat‘s houses and nighttime parturition were easy

targets to these predators.

Pregnant females that had an average bodyweight of 37.8 ± 0.6 kg (Table 7 in Appendix 1) in this

study were higher than of Gwembe Valley does that had average bodyweights before kidding

between 24 to 27 kg (Aregheore et al. 1992). Reared in Zambia the Gwembe kid‘s birth weight

ranged from 1.0 to 1.6 kg (Aregheore et al. 1992). The bodyweights of does in this study was also

higher than of Black Bengal does during the month of conception i.e. 15.3 ± 0.5 kg; 17.1 ± 0.3 kg;

18.6 ± 0.7 kg and 21 ± 2 kg for bearing single, twin, triplet and quadruplet kids born to does reared

in India (Pan et al. 2015).

Of the 20 smallest flocks, only 30% of flocks had positive values of GM(A-B) and GM/doe. These

30% of flocks only had positive values of GM(A-B) and GM/doe when the farmers had at least


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33% turn off rate per year. Farmers received a total income of IDR 84.300 million for selling goats,

manure and milk production, and GM(A-B) was IDR 34.100 million and GM/doe was IDR 6.600

million when they sold 4.7 ± 1.1 goats per household per year. This indicated that having small

flock sizes did not necessarily mean always having a negative gross margin. This also indicated

that regardless of the flock size as long as the household made more than 33% turn off rate, they

achieved positive values both for GM(A-B) and GM/doe. As the sizes of flocks increased, the

positive values of GM(A-B) and GM/doe also increased; smallholder farmers in Buleleng Regency

had 50%, 80% and 67% turn off rates for the flock sizes of 11≤20, 21≤30, and 31≤42, respectively.

The benefits of rearing goats for milk production purposes also motivated households to improve

their flock sizes.

Number of does owned per flock had a strong correlation with prices of goats sold (IDR million)

(P<0.01). The largest flock size of 31≤42 goats per flock in this study had the largest number of 24

± 2 does owned per flock (P<0.05) and produced the highest prices of IDR 11.360 ± 0.100 million

milk production (Tables 6.2 and 11 in Appendix 1). The larger number of does owned per flock

also had increased opportunities to have more kids born and thus larger opportunities to have higher

GM(A-B) and GM/doe (Peacock 1996). This was in agreement with Singh et al. (2011) who stated

that having large flock size per household achieved high annual income per household than small

and medium flock sizes.

The average size of 13 ± 1 goats per household in this study was higher than goat flocks reared by

smallholder goat farmers in Java Island that ranged from 2 to 10 goats per household reported by

(Rusdiana et al. 2011). Smallholder goat farmers studied in Busungbiu District achieved an annual

total income of IDR 15.960 ± 2.661 million per household which was larger than IDR 2.691 million

reported by Rusdiana et al. (2011). Rearing an average large flock of 13 ± 1 goats per household as

well as owning at least 25% of does in flocks in Banjar, Busungbiu and Grogak Districts could be

one of the development strategies that will help in improving their income.

However, it was not easy for farmers who shared land in Busungbiu District to increase flock size

due to the ownership of the land thus the availability of livestock feeds. However, when the

households started to replace some of the coffee or cacao trees by growing Pennisetum purpureum

or king grass for goats feed and improving their flock sizes, or feeding fermented coffee pulp or

cacao pods as goats feed, as well as crossing goats with Boer and Etawah bucks – all improved

GM(A-B) and GM/doe. Change in land use and its impact on the productivity of goat rearing,


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particularly on the GM(A-B) and GM/doe in Busungbiu District could motivate other households in

Buleleng Regency to do the same.

The average flock size in this study was 13 ± 1 goats, and of the 20 smallest flocks with 1≤10 goats,

13 flocks did not have mature male goats and two households did not have does. Furthermore, of

the 16 flocks with 11≤20 goats, six flocks did not have male goats (Tables 6.2 and 11 in Appendix

1). One of the breeding programmes to ensure that oestrus females were mated in proper time was

that the farmers had an available buck (Devendra & McLeroy 1982; Devendra & Burns 1983;

Peacock 1996; Jainudeen et al. 2000). This indicated that the numbers of full-grown bucks in

Buleleng Regency should be at least 42 (1 X 20 Small + 1 X 16 Medium + 2 X 8 Large flock size)

instead of 35 during the observations (Table 12 in Appendix 1). From the point of view of practical

management, it was assumed each goat farmer should have one to two bucks for the larger flock

size to sire the 251 does that can improve the productivity of goats reared by smallholder farmers in

Bali Province. However, the relatively high average-kidding rate of 166% and turn off rate of 18 ±

3% observed in this study indicated that lack of access to a buck was not a widespread problem.

Preweaned male kids once they reached weaning period with an average bodyweight that ranged

from 19.4 ± 1.3 kg to 20.7 ± 1.2 kg were sold (Figures 6.2 and 6.4). Results of this study showed

that the proportion of females were similar at about 7-30% when they were I1 up to I4 dentition and

then decreased to be less than 4% when they were more than 6 years old. This indicated that

farmers were able to select productive females that had I0 dentition in proper portion of 20 to 25%

as replacements (Morand-Fehr et al. 2004).


Analysis of GM(A-B) and GM/doe from goat rearing by smallholder farmers in Buleleng Regency

were essential to determine the constraints to, challenges of and opportunities for rearing more

goats in more efficient management. Above all, the main reason to generate positive high values of

GM(A-B) and GM/doe in Buleleng Regency was having high kidding and weaning rates of kids.

The average kidding interval has been well managed, as had the kidding rate of 166% and weaning

rate of 107%. Although kidding intervals for does reared in battery and colony housing were not

significantly different, the kidding interval for does in colony housing tended to be shorter than in

does kept in battery housing. Having larger flock sizes in battery housing did not necessarily mean

having more opportunities to produce more kids in battery housing. This study revealed that from

323 kids born in Buleleng Regency in 2014, 10% were born from does, which were kept in colony

housing. This also enabled the flocks to have more kids born as well as more milk produced, these


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contributing to high positive values of GM(A-B) and GM/doe. The proportion of does in flocks

was highly important to positive high values of GM(A-B) and GM/doe.

This indicated that in Buleleng Regency, a farmer who sold a third of their flock each year or had

33% turn off rate always had positive GM(A-B) and GM/doe in 2014.

An average of IDR 14.316 ± 2.368 million total income gained by smallholder farmers in this study

was higher than of smallholder farmers with IDR 0.531 million per month in Batungsel Village

(Suciani et al. 2013), IDR 0.114 million per month in Semarang City, Central Java (Budiraharjo &

Setiadi 2004) or IDR 1.930/farmer/year for a flock of 13 goats per household in Lampung Province

(Priyanto 2008). The average GM(A-B) per household per year i.e. IDR 2.662 ± 1.743 million

generated by smallholder farmers in Busungbiu District was the only positive value and tended to

be higher than in Banjar and Grogak Districts being IDR (1.547 ± 3.294) million and IDR (4.572 ±

2.516) million, respectively (P>0.05) (Table 5 in Appendix 1). This GM(A-B) value generated

from the smallholder production systems was slightly higher than IDR 2.154 million and IDR 2.691

million for semi-intensive business and intensive business, respectively reported by Rusdiana et al.

(2011).

Among districts, smallholder farmers in Busungbiu District tended to have a higher average of 14.3

± 1.8 goats per flock with 6.5 ± 1.2 does per flock, and sold 6.7 ± 1.3 goats per flock, and thus made

significantly higher 51 ± 6% turn off rate (P<0.05). They generated significantly higher IDR

15.960 ± 2.661 million total income (P<0.05) that was generated from selling goats of IDR 11.140

± 2.106 million, selling manure of IDR 1.307 ± 0.017 million and selling milk of IDR 2.554 ± 0.064

million.

Overall, smallholder farmers in Buleleng Regency were significantly dependent on internal sources

that reduced the total variable costs of rearing goats. Turn off rate in Banjar and Grogak Districts

were lower than 33% that indicated the GM(A-B) and GM/doe could be increased by selling more

goats just prior to Eid Qurban. Total goats sold per year in Buleleng Regency was IDR 386 million

or 69% contributed to the total income of IDR 558.900 in this study was higher than 39% of goats

reared in traditional mixed farming systems reported by Legesse et al. (2010). Furthermore, the

milk sold contributed 21% to the total income that indicated an opportunity to improve milk

production by owning more does per flock. This is in agreement with Nemeth et al. (2004) who

reported that milk sold could contribute 75-80% to the total income of the farms by increasing the

number of doe per flock as well as upgrading the goats.


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In addition, owning and cultivating the second largest area i.e. 1.70 ± 0.50 ha by themselves,

smallholder farmers were able to replace some of their coffee trees with Pennisetum purpureum

grasses to produce sufficient amounts of feed for their goats. This indicated that they realized that 2

± 0.4 household labourers balanced with their area cultivated, and their flock size to optimize

GM(A-B) and GM/doe.

Three households in Buleleng Regency had the largest average flock size of 39 ± 1 goats that had

the largest average number of 24 ± 2 does, and the largest average number of 3 ± 0 bucks (P<0.05).

They sold the largest average of 12 ± 3 goats that generated the largest average total income of IDR

42.120 ± 4.991 million and the largest average IDR 10.100 ± 4.714 million for GM(A-B) and the

largest average IDR 0.446 ± 1.107 million for GM/doe. However, they had the lowest average 29 ±

21% turn off rate (P<0.05) (Tables 6.2 and 11 in Appendix 1). This indicated that by having the

lowest turn off rate, farmers still had an opportunity to make higher GM(A-B) and GM/doe by

selling more goats prior to Eid Qurban.

A positive value of GM(A-B) was made only by the flock sizes that had two labourers per

household and they had the highest turn off rate of 20 ± 3%. The positive values for both GM(A-B)

and GM/doe could only be made by having turn off rates >33% per flock. The average turn off rate

recorded in March 2014 was 36 ± 6%. Only female and male weaners and old dry females were

sold. It was likely that male yearling and bucks would be sold prior to Eid Qurban in October 2014.

Therefore, the turn off rate was likely to increase which would increase GM(A-B) and GM/doe,

particularly in the larger flocks.

This study revealed that for 75% or 33 households generated turn off rates less than 33% and had

negative values for GM(A-B) and GM/doe. Sixteen farmers or 36% of farmers sold no goats and

had 0% turn off rate in 2014. Forty-three or 98% farmers had a turn off rate <50% and only 1

farmer had a 75% turn off rate. This indicated that farmers could increase their income by selling

more goats at either the beginning of school in July or prior to Eid Qurban.

Turn off rate of goats reared in battery housing i.e. 46 ± 6% was significantly higher than of colony

housing i.e. 11 ± 10% (P<0.05) although the number of goats sold/year as well as the prices of goats

sold/year were not significantly different (P>0.05) (Table 6.3). Since the turn off rate of goats

reared in colony housings was lower than 33%, then there was opportunity to sell more goats prior


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to Eid Qurban for all flock sizes, particularly the larger flock sizes of 11≤20, 21≤30 and 31≤42

goats (Table 6.3).



interviewed in Banjar, Busungbiu and Grogak Districts were not sure how to predict the age of their

goats and had never weighed their goats even when they sold their goats. Furthermore, farmers had

never recorded the productive nor reproductive parameters of their goats. This is a constraint to

rearing goats in Buleleng Regency as it means farmers have no data on how well their animals are

performing.


Identifying the objectives of goat keeping by smallholder farmers in Banjar, Busungbiu and Grogak

Districts was a prerequisite in determining and evaluating the GM/doe that can be generated per

household. The three districts had various priorities for goat rearing based on the ownership and the

size of land cultivated. Considerations by shared land farmers, particularly in Busungbiu District,

on what the ideal flock size per household sould be, that provided sufficient goat manure for their

cultivated land, but the land provided sufficient roughage for goats? Or what the ideal number of

household labourers would be, that worked on that size of cultivated land for high coffee production

as well as high goat production?

The productivity of goat production integrated with the coffee and cacao plantations in Busungbiu

District increased from a minimum flock of 15 goats reared per household (Anonymous 2009; Arya

2014; Arya et al. 2014). Guntoro (2012) recommended 25 to 28 goats per ha would be enough to

produce goat manure as organic fertilizer to produce 2,450 kg coffee or 2,185 kg cacao annually.

Using goat manure composted by Rummino bacillus as organic fertilizer improved coffee

production from 500 kg/ha to 900 kg/ha in Busungbiu District (Guntoro et al. 2004).

However, the results of this study showed that 25 households had an average land size of 1.7 ± 0.1

ha per household and reared an average of 13 ± 2 goats per household. The total land size

cultivated for coffee plantations in this study was 42 ha with 358 goats reared. It was only a third of

the recommended number of goats by Guntoro (2012) i.e. 1,048 goats. Therefore, a suggestion to

smallholder farmers in Busungbiu District was to increase the number of goats by 690 goats to

provide sufficient quantity of organic fertilizer from goat manure. A major reason for farmers in

Buleleng Regency to raise goats was to provide an inexpensive bio fertilizer (manure).


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It was a problem, particularly for shared goat farmers, to balance between the size of shared area

cultivated and the number of household labourers to work on farming integrated with large flocks.

The highest average flock size of 39 ± 1 goats per household had an average of 2.3 ± 0.3 household

labourers. Meantime, the lowest flock size of 7 ± 1 goats per household had an average of 2 ± 0.1

household labourers. This indicated that smallholder farmers had insufficient numbers of

household labourers to cultivate one ha of coffee plantations along with rearing 25 goats. This

demand of labourer reached a peak from July to September when it was coffee harvesting.

It was calculated that the smallholder farmers gained IDR 1,290 kg/ha x IDR 22,000/kg = IDR

28.380 million/ha/year for wet processing coffee (Anonymous 2009) when the smallholder farmers

reared 25 to 28 goats per ha of coffee plantations (Guntoro 2012). This means that the households

who shared the area cultivated for the coffee plantations, they only received IDR 14.190

million/ha/year. However, this study showed that average total incomes were IDR 15.960 ± 2.661

million (Table 2 in Appendix 1) for rearing 14.3 ± 1.8 goats per household in Busungbiu District

(Table 1 in Appendix 1).

Although the 44% of households in Busungbiu District that reared larger flock sizes gained higher

total income than working in a hectare of coffee production, they were limited to the size of flocks

based on the availability of roughage grown as shade trees. They did not have the authority to grow

more roughage in coffee or cacao plantations. However, some of the 54% of the landowners who

also reared goats, started to improve the size of their flocks as well as to grow more roughage for

goats feed, and from fermented coffee pulp or cacao pods for goats. By utilizing the fermented

coffee pulp, farmers also gained extra income from selling the coffee pulp fermentation as well as it

assisted with environmental conservation (Arnawa et al. 2010).

For all households interviewed in Banjar District although rearing goats was to obtain goat manure

as fertilizer to improve soil fertility of their crop farms sized 0.9 ± 0.5 ha, they have a small size of

land to grow roughage for their goats. Therefore, they preferred cutting the field grasses,

Artocarpus heterophyllus or other bushes or Caliandra calothrysus, Sesbania sesban, Erythrina

variegata, and Pennisetum purpureum that were purposefully planted in empty space or public

areas along the riverbank to feed their goats. This situation limited them to rear certain size flocks

that they could manage based on roughage availability.


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Awareness of the objectives of goat keeping was important in leading farmers to generate high

GM(A-B) and GM/doe. As farmers expected extra income by selling goats milk as well as milk

products, farmers in Busungbiu District, particularly in Pucaksari Village upgraded their goats by

crossing them with Boer and Etawah Grade bucks to improve their milk production. This resulted

in Boerawa i.e. Boer X Etawah Grade crossbreds. Meantime, farmers in Sepang Kaja Village also

upgraded their goats by crossing them with Etawah Grade bucks. Results of this study indicated

that upgrading of goats reared in Busungbiu District improved the average bodyweight of goats

significantly more (P<0.05) i.e. 43.9 ± 2.2 kg than those goats reared in Banjar or Grogak Districts

i.e. 24.3 ± 1.4 kg and 21 ± 1.3 kg, respectively (Table 5 in Appendix 1). This was in agreement

with Momani et al. (2012) whom reported that upgrading goats resulted in better growth rates and

milk production which improved their productivity.

The contribution of 21% of income from milk sold in this study improved the productivity of goats

reared in Busungbiu District and thus increased the total income gained by smallholder farmers.

This was due to the number of does, 9.8 ± 0.7, owned per household in Busungbiu District, which

was significantly higher than in Banjar or Grogak Districts i.e. 5.2 ± 1.1 and 5.1 ± 1.2 does,

respectively (Table 12 in Appendix 1). This indicated that by having more does owned by

households in Busungbiu District having more kids thus having more milk-produced as well as

having better growth rates of goats. This was in agreement with Nemeth et al. (2004) and

Budiarsana (2011) who reported that increasing milk production and improvements in kidding rates

could improve profitability. Besides, milk production is a vital form of primary health care,

particularly for women and children in rural of Bali Province since rearing dairy cows was almost

impossible for smallholder farmers in Bali Province (Anonymous 2004b).

To achieve higher milk production, farmers in Busungbiu District should keep upgrading their goats

by obtaining breeding stock from the Indonesian Research Institute for Animal Production

(Balitnak-Ciawi). To support goats‘ milk as well as meat production, it was also suggested that

farmers in Buleleng Regency, particularly in Busungbiu District to keep upgrading their goats by

crossing them with Saanen or Anglo-Nubian goats. Smallholder farmers in Busungbiu District

reported that the average milk production of lactating does was about 500 to 750 ml per doe per day

in the peak of lactation, over average three-month lactation. Does never produced 1 litre of milk

per doe per day, although they were fed fermented coffee pulp and about 5 kg mixture of fresh

roughage per doe per day.


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As stated earlier farmers in Grogak District did not cultivate any crop or commodity plantations,

and their reason for keeping goats was to utilise the conservation forest where roughage was grown

as feed for their Bali cattle and goats (Surata et al. 2014). All households interviewed in this district

reared livestock as their main financial resource and they preferred rearing goats that had small

bodies with floppy short size ears. This type of goat breed, that had significantly lower average

bodyweights of 22.8 ± 1.2 kg (P<0.05) (Table 5 in Appendix 1), grew well and appeared to be

suited to the dry land of Grogak District that tends to have decreased availability of roughage in dry

seasons.

All farmers interviewed in Grogak District were Muslim, and they had good links to mosques in

Bali for marketing their goats prior to the Eid Qurban Celebration. This guaranteed for high prices

of goats sold. An objective of goat keeping was to sell live goats, and the bodyweight of the goat

was a determinant of prices of goats sold although other factors such as the goats‘ body condition,

coat colour, its age and timing of sale were important. The festive season could have an effect on

the market price of goats (Table 13 in Appendix 1).


Identifying the feed and feeding management used by smallholder farmers in Bali Province was

crucial to improving their goat productivity. Fresh Caliandra calothrysus, Gliricidia sepium,

Sesbania sesban, Erythrina variegata, Pennisetum purpureum kikuyu grasses, Artocarpus

heterophyllus fed to their goats was 5 kg/goat/day in this study as confirmed by Nitis (1997). Nitis

(1997) reported that smallholder farmers in Bali apart from growing crops as their main production,

they also practiced traditional silvipastoral systems by growing shrubs and trees and keeping

livestock as a sideline. The result was confirmed by Casasús et al. (2012) who reported that the

mixture of herbaceous plants fed to goats had beneficial effects on animal nutrition and health,

particularly their secondary compounds which had anti-parasitic properties (Tangendjaja & Wina

2000; Ørskov 2011; Pathak et al. 2017). Regarding livestock systems, smallholder farmers in

Buleleng Regency strategically optimised the productivity of crops and herbaceous forages i.e.

mainly improving water and soil management, and improved the ability of animals to cope with

environmental stress by using locally adapted cut and carry feeding management and upgrading

their goats with Boer and Etawah Grade bucks as confirmed by Nardone et al. (2010).

Sukanten et al. (1996) reported that feeding 100% Gliricidia sepium leaves to PE bucks during the

dry season in Bali, achieved average daily gains of 80 g/goat/day that was significantly higher than

those fed with ficus leaves i.e. 40 g/goat/day or fed with natural grass i.e. 9 g/goat/day. Feeding


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100% Gliricidia sepium leaves also increased bodyweights, improved carcass quality of PE bucks

as well as lower water consumption (Sukanten et al. 1996). In dry land farming areas Bali in

Indonesia, Gliricidia sepium leaves could become the sole diet for ruminants during the dry season;

while in the wet land farming areas, farmers did not lop such leaves, since ruminants do not eat

them, in the presence and absence of other feeds (Nitis 1999). Gliricidia sepium contributed as

nitrogen sources in compounded diet supplements without any detrimental effects on production in

lactating does as reported by Ondiek et al. (2000).

Sesbania sesban was one of the exotic multipurpose fodder trees introduced to Bali Province for

livestock feed, particularly in dry season and soil conservation (Nitis 2006; Oosting et al. 2011).

This was supported by Kaitho et al. (1998) who reported that long-term supplementation of

Sesbania sesban to male East African goats improved their growth and reproduction performance.

Utilization of leguminous fodder trees or shrubs has long been recognized to improve both the

supply and the quality of forage in smallholder production systems in Bali Province (Nitis 2006) as

well as to ameliorate feed constraints in developing countries and also to enhance soil fertility

(Topark-Ngarm & Gulteridge 1990).

All flocks studied in Busungbiu District were fed with a mixture of fermented coffee pulp or cacao

pods with Aspergillus niger and pollard about 150 g per goat per day that were fed twice or three

times a week. Feeding goats with coffee pulp fermented with Aspergillus niger as 30% substitution

for Gliricidia sepium and Caliandra calothrysus increased daily gain weight of goats to 100

g/goat/day (Londra & Sutami 2013). Fermented coffee pulp with Aspergillus niger improved the

protein content of the coffee pulp from 7.9% to 12.4% and was a quality substitute to pollard to feed

goats (Guntoro et al. 2004). It was assumed that feeding a mixture of roughage plus dagdag soup in

Buleleng Regency provided better growth rates as shown in Table 5 (Appendix 1). The average

bodyweight of goats reared in Busungbiu District i.e. 43.9 ± 2.2 kg was significantly higher than

goats reared in Banjar and Grogak Districts being i.e. 24.3 ± 1.4 kg and 21 ± 1.3 kg, respectively.

Prawirodigdo et al. (2005) suggested goats be fed a maximum amount of 100 g/goat/day of un-

processed cacao pods for increased daily weight gain of 70 g/goat/day due to the content of un-

processed cacao pods that were low in protein, and relatively high in lignocellulose and theobromin.

These contents limited the efficiency of these nutrients digestion (Suparjo et al. 2011; Riyanto &

Anam 2012; Wisri & Susana 2014). Farmers in Buleleng Regency never fed commercial

concentrate to their goats.


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Cut and carry feeding systems used by smallholder farmers in Buleleng Regency was fundamental

to their management, extent of use, conservation and enhancement for goat productivity (Nitis

1997). Feeding habits of grazing goats can lead to damage to soil and vegetation when uncontrolled

(Shrestha 2011), therefore it was avoidable in goat rearing management in Buleleng Regency. This

was in agreement with Wang et al. (2010) and Yang et al. (2010) who reported that feeding goats

with fresh un-treated roughage created healthy and cheaper organic goat production systems thus

improved goat productivity. This feeding management resulted in reasonable bodyweights for all

physiological states of goats reared in Buleleng Regency (Tables 6 and 7 in Appendix 1).

Although the average feed cost for goats reared in Buleleng Regency i.e. IDR 10.200 ± 1.156

million was not statistically different among the three districts (P>0.05), only goats reared in

Busungbiu District generated positive values both for GM(A-B) and GM/doe (Table 2 in Appendix

1). This was due to this district having the highest turn off rate i.e. 51 ± 6% (P<0.05) and tended to

generate a higher average IDR 15.960 ± 2.661 million total income (P>0.05).

The feed cost that contributed 81.3% to total costs in this study was lower than 72% reported by

Nemeth et al. (2004). Rearing goats by smallholder farmers in Buleleng Regency was significantly

dependent on internal resources that reduced the total variable costs. Smallholder farmers thought

that rearing goats provided profits, because they did not calculate the IDR 454 million and IDR

102.700 million for the total feed and labourer costs as expenses.


The cost in money and time to protect the kids, reduced productivity of goats reared in Busungbiu

District. One of the most utilised tools to reduce predation by wild dogs was fencing or better

housing. Wild dogs control could be used to improve the number of kids weaned, thus improve the

productivity of goat production in Busungbiu District.

The incidence of anaemia as measured by the FAMACHA©

technique was nil in kids born in

Buleleng Regency in 2014 (Table 6.6). A low parasite burden was due to the management of their

housing systems (Haenlein & Abdellatif 2004; Grosso et al. 2016) and the timing and height of

cutting herbaceous forages (Jones 1993) for better internal parasite control. Besides, Artocarpus

heterophyllus, Gliricidia sepium, and Caliandra calothrysus and herbaceous forages fed to goats in

this study contained tannin as anthelmintic (antiparasitic) properties against Haemonchus contortus

worms (Tangendjaja & Wina 2000; Kustantinah et al. 2014). Socio-economically health care and

sustainable eco-friendly disease control management substantially improved productivity of


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individual animals thus this resulted in economic gains for smallholder goat farmers in an organic

environment (Gunia et al. 2013; Pathak et al. 2017).

However, goats that were reared in the first two smallest flock sizes in colony housing systems had

significantly higher FAMACHA©

scores being 2.6 ± 0.1 and 2.7 ± 0.1 (P<0.05) indicating a

―warning‖. This might be due to the rainfall, which was still high in February-March 2014 i.e. 333-

192 mm. Papadopoulos et al. (2013) reported that using the FAMACHA©

system for identifying

infection by Haemonchus contortus was not always useful, particularly in areas where prevalence of

Haemonchus contortus is low. Instead, they suggested using classical parasitological techniques or

other selection criteria. Therefore, a green method was applied by feeding herbaceous forage

containing tannins have anthelmintic (antiparasitic) properties against Haemonchus contortus.

Nevertheless, using the FAMACHA©

technique could be useful as it was a practical on-farm

method, to identify small ruminants in need of anthelmintic treatment by showing their level of

anaemia.


Determining how smallholder farmers in Buleleng Regency housed their goats was important to see

if housing had any effect on productivity. Seventy-five per cent of goats were reared in battery

housing. All average turn off rates (P<0.05), total incomes (P<0.05), total variable costs (P<0.05),

gross margins (P<0.05) and GM/doe (P<0.05) of goats reared in battery housing were significantly

higher than of goats reared in colony housing (Tables 6.3 and 12 in Appendix 1).

In this study, the goats reared in colony housings regardless of their physiological state were free to

walk around and bucks were usually free to mate with mature does. This indicated that free access

of bucks to mate does made them also easier to detect as well as to mate those does that had their

first postpartum oestrus. Therefore, it may shorten their kidding intervals. Furthermore, the results

of this study indicate that feeding a mixture of fresh roughage 5 kg per goat per day as well as the

quality of feed provided to goats were sufficient to support their growth rates based on their

physiological state (Tables 5 and 6 in Appendix 1). Furthermore, three out of the five households

who had the highest education levels reared the largest size flocks in colony housing (Table 12 in

Appendix 1).

However, having dominant bucks in a flock reared in colony housings may lead to inbreeding,

particularly when the number of bucks was limited and bucks were used for a long time (Peacock

1996). Putting goats together into heterogeneous sizes or ages may also affect the weaker goats to


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gain access to feeds, particularly when feeds provided were of insufficient quantity for all goats.

Colony housing system was more recommendable in rearing goats that were homogenous in ages or

sizes for better results.

The highest average flock size of 39 ± 1 goats in battery housing (P<0.01) generated a higher

GM(A-B) of IDR 10.100 ± 4.665 million (P<0.05) and GM/doe of IDR 0.446 ± 0.939 million

(P<0.01) when they had the lowest turn off rate of 29 ± 19% (P<0.05) (Tables 6.6 and 12 in

Appendix 1). This indicated that more goats could be sold and were estimated to have more than

2.5 times larger GM(A-B) and GM/doe prior to Eid Qurban. This study revealed that high positive

GM(A-B) and GM/doe occurred when households had more than 33% turn off rate regardless of

what housing system was used. Larger flock sizes and reasonable labourer to goat ratios with

sufficient proportions of does and bucks in the flock played important roles in dictating high

positive GM(A-B) and GM/doe (Tables 6.3 and 12 in Appendix 1).

Both GM(A-B) and GM/doe for the smallest flocks reared in battery (6.8 ± 0.5 goats) or colony

housing (6.1 ± 1 goats) were negative although the turn off rate for the battery housing was 24 ± 6%

(Table 6.6). However, when flock sizes were bigger (battery 14 ± 1, colony 16 ± 2 goats), only

GM(A-B) and GM/doe for goats in battery housing were positive although they had a similar value

of turn off rate i.e. 22 ± 3%. This study revealed that positive values for GM(A-B) and GM/doe of

goats reared in the two housing systems were dictated primarily by flock size rather than the

decision to sell goats for larger turn off rate.

6.5 Constraints to improving goat production in Banjar, Busungbiu and Grogak Districts, Buleleng

Regency

In summary, the constraints to improving goat production in Banjar, Busungbiu and Grogak

Districts, Buleleng Regency were:

The absence of does and bucks in the flocks;

Farmers having a high mortality rate of kids;

A low ratio of household labourers to flock size particularly the farmers who shared land;

Keeping old does too long on farms;

A lack of awareness on the objectives of goat keeping;

Farmers having no or small sizes of land owned to grow roughage; and

Farmers having no records of their goats.


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6.6 Challenges of improving goat production in Banjar, Busungbiu and Grogak Districts, Buleleng

Regency

In summary, the challenges of improving goat production in Banjar, Busungbiu and Grogak

Districts, Buleleng Regency are:

To improve genetic performance of dairy goats i.e. introduction to Saanen goats;

To maintain the average bodyweight of goats in Busungbiu District were significantly higher

due to upgrading;

To rear more Boerka or Boerawa crossbreds for high production;

Improving smallholder‘s skills in selecting goats, particularly milk production; and

To utilise Aspergillus niger to ferment coffee pulps or cacao pods as feed for goat.

6.7 Opportunities for improving goat production in Banjar, Busungbiu and Grogak Districts,

Buleleng Regency

In summary, the opportunities for improving goat production in Banjar, Busungbiu and Grogak

Districts, Buleleng Regency were:

Average bodyweights of goats in Busungbiu District were high due to the farmers having crossed

their goats with Boer and Etawah bucks;

Maintain the high bodyweights of goats by keeping and selecting heavier does, bucks and kids;

Rear more Boerka or Boerawa goats for high meat and milk production; and

Strategies for having an additional source of income by selling milk and milk products.

6.8 Conclusion

Goats in Banjar, Busungbiu and Grogak Districts in Buleleng Regency have an important socio-

economic role using low internal inputs such as household labour, cheap feed and rearing

management costs to improve their GM(A-B) and GM/doe, creating food self-reliance thus

improving the welfare of smallholder farmers.

Overall, the efficiency of goat production was surprisingly high (weaning rate of 107%), in spite of

constraints such as lack of feed and competition from other agricultural enterprises for farmers time.

Upgrading for improvement of milk production was successfully shown by the significantly higher

average bodyweight, circumference of chest, height at withers and rump height of goats in

Busungbiu District due to crossing with Boer and Etawah bucks. Gross margin analysis per doe

indicated a wide range of economic performance; the major factors associated with high

performance were large flock size and high turn off rate. The fact that some farmers returned a

negative GM/doe indicated that they were waiting to sell more goats prior to Eid Qurban as they


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had low turn off rates, particularly for smallholder goats in Grogak District. Goats were sometimes

raised for non-economic reasons such as cultural, as a ―living bank‖ and tradition. In most cases,

rearing goats is a sideline for most farmers. Horticultural crops and cattle rearing have a higher

priority in most cases. Nevertheless, goat rearing has the potential to fill an important role in

alleviating rural poverty in rural area.

6.9 Suggestions

The main suggestion was to improve the quality of breeding stock. This may be accomplished by:

Introduce Saanen goats to improve milk production;


Improving smallholder‘s skills in selecting goats, particularly for milk production;

Rear more Boeraka and Boerawa goats;

Restructuring the flock profiles with an optimum age structure and buck to doe ratio;

Ensuring adequate access to bucks so that does are able to get pregnant immediately after

postpartum oestrus;

Reduce kid mortality;

Keep does only up to their fourth or fifth kidding;

Encourage smallholder goat farmers to practice simple recordings to be able to identify elite

animals and poor quality animals; and

Build networks to ensure quality of breeds, feed and rearing management systems.

Chapter 7 Mendoyo District, Jembrana Regency

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Chapter 7

Current and future goat production in Jembrana Regency, Bali Province, Indonesia:

A case study in Mendoyo District.

7.1 Introduction

Using the layout used in Chapter 5 as a template, factors influencing the efficiency of goat

production by smallholder farmers in Mendoyo District of Jembrana Regency were assessed and

discussed in this chapter. Mendoyo District was selected as the sampling area as it had the largest

goat population among the districts in Jembrana Regency (BPS-Bali 2015). However, this district

has had a large reduction in the number of goat farmers as well as goats, over the last 25 years.

Jembrana Regency previously had 42,751 goats as the largest goat population among regencies in

Bali Province or about 45% of the total 95,430 goat population in Bali Province in 1990

(Anonymous 1990). In 1990, this was about double the current number of goats in Buleleng

Regency i.e. 24,905 goats or triple that of Karangasem Regency i.e. 13,861 goats. Other villages in

Jembrana Regency that previously had large numbers of goats and goat farmers (Anonymous 1990)

had been visited. However, these villages at the time of this study had none or very few goats and

goat farmers. Available literature presented little information on the reasons some smallholder

farmers had stopped farming goats years ago or they had just re-started farming goats recently, as

well as the current situation of their goat rearing under smallholder production systems in Mendoyo

District. The objective of this chapter was to establish a database of the reproductive and

productive efficiency of goat farming under smallholder production systems in Mendoyo District in

Jembrana Regency, as well as a socio-economic analysis of these systems. The database was used

for establishing their future development strategies through identifying their constraints to,

challenges of and opportunities for improving goat production in Bali Province.

Most of the smallholder farmers studied in Mendoyo District apparently re-started rearing goats as

they had received Simantri Programmes in October 2013 and April 2014 (Tunas, W. 2014, pers.

comm. 9 June) that motivated them to resume or improve their goat rearing management (Elisabeth

2012). The smallholder goat farmers mostly had small flocks; therefore, they were increasing the

number of goats in their flocks and apparently would not sell goats prior to Eid Qurban. A case

study was conducted between 3rd

to 30th

June 2014 to establish a database of current reproductive

and productive efficiency of goat farming in Mendoyo District as they contributed about 2.4% of

the total 841.8 km² size of Jembrana Regency, and as well they contributed about 11% of the total

of 68,457 goats in Bali Province (BPS-Bali 2015). This district was a designation regency for


135


improvement of goat farming that was officially promulgated by the Indonesian Minister of

Agriculture (Anonymous 2015d).



adjustments. The goat farming studied in Jembrana Regency encompassed a village in Mendoyo

District. Mendoyo District is located in West Bali National Park, the conservation forest of

Jembrana Regency that is located in the western part of Bali (Plate 3.1). Most of the people lived in

agricultural sectors and their income was derived primarily from soybean, coconut, cacao, coffee,

and cloves plantations (BPS-Bali 2015) (Tables 4.5 and 4.6).

All 68 goat-owning families were interviewed, based on structured questionnaires, and 258 goats

were observed to obtain data i.e. breed-type, sex, age, dentition status (I0, I1, I2, I3, I4, toothless),

FAMACHA©

score, bodyweight, body measurements, birth type (single and multiple), and parity

were recorded over a month of direct animal observations. From the 258 goats, 67 kids were born

during the data collection. Data was only collected in June 2014; therefore, data on goat

reproductive performance was taken from the previous year. The average daily gain of goats reared

in Mendoyo District was not available as the goats were only weighed once (Table 3.1).

Furthermore, most of the smallholder goat farmers had just re-started rearing goats and housed their

goats only in battery housing systems; therefore, kidding intervals as well as the effects of housing

systems were not presented. The inputs included feeds, veterinary services, drugs, and labour cost

i.e. labourers (from the family). The outputs obtained included sales of live animals, manure or

goat products consumed at home which were then converted into cash (IDR million). IDR 1

million was equivalent to AUD$100.00.

7.3 Results




confirmed additional family members who were involved in goat rearing. All 68 households

interviewed in Mendoyo District were Bali Hindus whose ratio of labourers to the number of goats

managed was 1.9 ± 0.6 goats. One household (1.5%) that had the largest flock had 53 goats

including 37 pregnant and 2 dry does and 4 bucks. Sixty-four households (94%) had one to nine

goats per flock and the remaining three households (4.5%) had 11 or 12 goats per flock. The

households reared goats and occasionally Bali cattle as part of mixed farming.


136


All (100%) of the households owned their land where the average land area cultivated was 0.9 ± 0.1

ha per household ranging from 0.1 to 2.5 ha per household. The land was cultivated with coconut

(Cocos nucifera), cacao (Theobroma cacao), coffee (Coffea spp.), clove (Syzygium aromaticum)

and forest trees, integrated with Bali cattle or goat rearing. Jembrana Regency had 40%, 25% and

21% as the largest contributions to the total of 8,187 tonnes of soybean, 80,458 tonnes of coconut

and 14,468 tonnes of cacao production, respectively, for Bali Province in 2014 (BPS-Bali 2015)

(Tables 4.5 and 4.6). This indicated that with the availability of agricultural and industrial by-

products there was an opportunity for these to be utilised in promoting the goat industry in

Jembrana Regency.

Households interviewed in Mendoyo District had an average of two labourers that looked after an

average of 4 ± 1 goats per household and each labourer managed on average 1.9 ± 0.6 goats. This

indicated that household labourers consisted of the head of the household and his wife and an

average of 0.2 household members who were 15 years old or older. The average household had 0.2

± 0.1 children, which were considered low (Table 1 in Appendix 1).

Husbands had slightly higher education levels (1.6 ± 0.1) than wives did (1.5 ± 0.1). Of the wives,

25% and 12% graduated from Grade 9 (score 2) and Grade 12 (score 3), respectively, while 22%

and 21% of husbands graduated from Grade 9 and Grade 12, respectively. The average farmer age

was 47.3 ± 1.4 years and over three quarters of farmers, (84%) were aged from 23 to 64 years while

16% were aged between 65 and 73 years (Table 1 in Appendix 1).

The effects of the number, as well as the productivity of family labourers on turn off rate, GM (A-

B) and GM/doe of goats reared in Mendoyo District, are further investigated in a later section of

this thesis. The production parameters of the 258 goats reared in Jembrana Regency is shown in

Table 2 (Appendix 1). Overall goat rearing in Mendoyo District had average GM(A-B) and

GM/doe of IDR (4.376 ± 0.565) million and IDR (2.518 ± 0.174) million, respectively.

Assumptions for cost of inputs used for raising goats included the average drenching cost of IDR

0.011 ± 0.002 million and roughage cost of IDR 2.770 ± 0.589 million, and labour cost of IDR

2.264 ± 0.051 million. The assumptions for price of outputs used were the average prices of goats

sold of IDR 0.323 ± 0.173 million and prices of manure sold of IDR 0.436 ± 0.074 million.

Total GM(A-B) studied in Mendoyo District was calculated to be a loss of IDR 297.556 million

while the total GM/doe was a loss of IDR 138.491 million for the 14 goats as well as the goat


137


manure sold. They had low i.e. 5 ± 3% average annual turn off rates that generated almost no i.e.

0.2 ± 0.1 goats sold per household per year (Table 2 in Appendix 1). The average gross margin

calculated was a loss of 4.376 ± 0.565 million ranging from a loss of IDR 37.435 million to a profit

of IDR 6.792 million. The GM/doe was a loss of IDR 2.518 ± 0.174 million, ranging from a loss of

IDR 6.275 million to a profit IDR 3.396 million (Table 2 in Appendix 1).

Goat rearing by smallholder farmers in Mendoyo District had IDR 343.100 million of total variable

costs that was seven times larger than the IDR 45.540 million of total income when they had a 5 ±

3% of annual turn off rate. The total income generated was approximately half from selling manure

and goats per year i.e. IDR 23.540 million and IDR 22 million, respectively. Both feed and

labourer costs contributed about 50% to the total variable costs (Table 2 in Appendix 1).

Sixty-eight households had flocks from 1 to 53 goats and annual working hours per household

ranged from 182.5 to 547.5 hours (Table 3 in Appendix 1). The average labourer to goat ratio in

Mendoyo District was 1.9 ± 0.6 goats per labourer. Eighty-seven per cent or 59 flocks had average

annual working hours of 362.3 ± 14.1 hours while 7% and 6% had the least and the largest number

of labourers, respectively. They generated an average of IDR (6.798 ± 0.872) million GM(A-B)

and IDR (2.215 ± 0.292) million GM/doe from an average 15 ± 4% annual turn off rate (Table 3 in

Appendix 1).

The number as well as the productivity of family labourers significantly influenced the turn off rate

and GM (A-B) (P<0.05) but did not significantly affect the GM/doe (P>0.05) of goats reared in

Mendoyo District. The largest number of annual equivalent working hours per household had a

significantly higher labourer ratio of 6 ± 1.1 goats per labourer (P<0.05) and had a significantly

higher number i.e. 5 ± 0.9 of does owned per flock (P<0.05) but the lowest number of goats sold i.e.

6 ± 1.1 (P>0.05) (Tables 3 and 4 in Appendix 1).

Irrespective of the number of labourers per flock, all flocks had negative GM(A-B) and GM/doe

regardless of their turn off rate (Tables 3 and 4 in Appendix 1). This indicated that households sold

small numbers of goats in 2014. It was also presumed that most of the households would not sell

goats even prior to Eid Qurban in October 2014 as they had just re-started rearing goats again and

were focused on improving their flock sizes.

The level of farmers‘ education per se, would be expected to improve the efficiency of goat

production, as it was hypothesised that farmers with a better education would implement improved


138


management practices. However, this study revealed that the level of education of the household

did not significantly affect the turn off rate, GM(A-B) or GM/doe (P>0.05) although there was a

tendency that the farmers with the highest level of education had the lowest loss of GM/doe (Table

4 in Appendix 1).

The level of farmers‘ education also did not significantly affect the labourer to goat ratio, number of

does owned and number of goats sold per household (P>0.05) (Tables 7.5 and 7.6). Farmers that

had the highest education level tended to have the lowest labourer to goat ratio, and the smallest

turn off rate and generated loss in both GM(A-B) and GM/doe.

All households interviewed were not sure how to predict the age of their goats and had never

weighed their goats even when their goats were sold. The farmers had never recorded the

productive or reproductive parameters of their goats. This was a constraint to rearing goats in

Mendoyo District as it meant farmers had no data on how well their animals were performing.


Smallholder farmers in Mendoyo District reared goats that were a mixture of Gembrong, Benggala,

Kacang, Etawah Grade, PE and their crossbreds or backcrosses (Plate 2.1). The bodyweight, chest

circumference, body length, height at withers and rump height of the goats are given in Tables 6

and 7 (Appendix 1).

Overall, the number of females (192, mostly adult females) were significantly more than the 66

male goats recorded (P<0.05) (Tables 6 and 7 in Appendix 1). However, when goats of the same

physiological state were compared, all the body dimension measurements of preweaned, weaner

and yearling males were significantly higher than those of preweaned, weaner and yearling females

(P<0.05) (Tables 6 and 7 in Appendix 1).

There were 75 pregnant does or 54% of the 139 does recorded in the 68 flocks in 2014. The ratio of

does to bucks was 139:24 or 6:1. Of 68 flocks in Mendoyo District, 76% or 52 flocks had no

mature bucks and 19% i.e. 13 flocks had no does. Furthermore, 40 flocks or 59% had no pregnant

females in June 2014. In contrast, the largest flock of 53 goats had 37 pregnant does and 4 mature

bucks. Only one flock studied in Mendoyo District had a flock of 53 goats, which included 39 does

and 4 bucks. Of the 64 smallest flock sizes with ≤10 goats, 80% i.e. 51 flocks had no bucks and

20% i.e. 13 flocks had no does and 18% i.e. 12 flocks neither had no bucks nor does (Table 7.1).


139


Table 7.1 Average number of goats of different classes, owned by households in Mendoyo District,

Jembrana Regency. Class of goat No. of farms No. of goats Mean ± SEM Range Minimum Maximum Mode

F preweaned 7 13 1.9 ± 0.7 5 1 6 1

F weaner 12 18 1.5 ± 0.1 1 1 2 1

F yearling 17 22 1.3 ± 0.1 2 1 3 1

F pregnant 28 75 2.7 ± 1.3 36 1 37 1

F lactating 13 16 1.2 ± 0.1 1 1 2 1

F dry 32 48 1.5 ± 0.2 4 1 5 1

M preweaned 14 18 1.3 ± 0.1 1 1 2 1

M weaned kids 9 13 1.4 ± 0.2 2 1 3 1

M yearling 6 11 1.8 ± 0.4 2 1 3 1

M buck 16 24 1.5 ± 0.2 3 1 4 1

Flock size 68 258 3.8 ± 0.8 52 1 53 1

The average flock size of 4 ± 1 goats from 68 farms ranged between 1 and 53 goats (Table 1 in

Appendix 1) where 64 farmers had the smallest flock size of 1≤10 goats and 4 farmers had a larger

flock size of greater than 10 goats (Figure 7.1 and Table 12 in Appendix 1). Fifty-two flocks (76%)

had no bucks, 13 flocks (19%) had no does, 12 flocks had neither bucks nor does, and another 40

flocks had no pregnant females in June 2014. This combination of flocks was a constraint to goat

production in Mendoyo District (Figure 7.1 and Table 12 in Appendix 1).

FS= Flock size, F=Female, M=Male, All prewean=aged 0 – 4.5 months; All wean=4.5 month – I0; All yearling=I1; F pregnant, F

lactating, F dry, and buck had I1 – toothless.


households in Mendoyo District, Jembrana Regency.

The number of kids born, that died, reared and were sold affected the production parameters of

goats that were farmed in Mendoyo District. In 2014, there were only 67 kids born from 49

parturitions from 49 productive females that had I0/I1/I2/I3 dentition (Figure 7.2). The ratio between

female and male kids born was 34:33. Of the 49 parturitions, 67% were single (33 kids), followed


140


by 29% twin born (28 kids) and 4% for triplets (6 kids). Kid mortality was 24% and occurred in

their first weeks of life when six kids died; they were born as twins and triplets.

Figure 7.2 Numbers of kids‘ born, that died, survived, were sold or reared of the 67 kids born in the

first six months in 2014 in Mendoyo District in Jembrana Regency.

Kidding rate (67 kids born per 49 does of reproductive age/year) was 137% for kids born in the first

half of 2014 in Mendoyo District. There were 139 mature does of the total 258 goats in Mendoyo

District and 65% of the does did not kid during the first 6 months in 2014. There were 31 kiddings

in the 1st parity, the 2

nd parity was 10 kiddings, the 3

rd parity was 4 kiddings and the 4

th, 5

th and 6

th

parity were 2, 1, and 1 does kidding, respectively. Having a larger number of does that did not kid

in the first six months of 2014 was a constraint to goat production in Mendoyo District.

Weaning rate (51 kids weaned per 49 does of reproductive age/year) was 104% for kids born from

the start of January to the end of June 2014 in Mendoyo District. The average bodyweights of

female preweaned kids i.e. 10.5 ± 1.9 kg was not significantly different (P>0.05) to the average

bodyweights of male preweaned kids 13.6 ± 1.6 kg although the average bodyweights of female

weaners 22.9 ± 1.6 kg were significantly lower (P<0.01) than of male weaners 29.8 ± 1.9 kg (Tables

6 and 7 in Appendix 1).


Overall, total GM/doe of IDR (138.500) million with an average IDR (2.518 ± 0.174) million

ranged from a loss of IDR 6.275 million to a profit of IDR 3.396 million. Of the 258 goats studied,

14 goats were sold in 2014 for the total price of IDR 22 million that contributed 48% to the total

income of IDR 45.540 (Figure 7.3). Comparison of the GM/doe between the top 20 and bottom 20

across the 68 households studied in Mendoyo District is shown in Table 7.2.


141



Total variable costs (IDR million), GM(A-B) (IDR million) and GM/doe (IDR million) of goats

reared by smallholder goat farmers in Mendoyo District, Jembrana Regency.

Farmer

No. of

goats

sold/year

Turn off

rate (%)

Flock

size

(goats)

Labourer

to goat

ratio

No. of

does

owned

(IDR million)

Total

income

Total

variable


Top 20

1 Gonyok 6 150 4 4 2 10.865 4.073 6.792 3.396

2 Sudewa 0 0 1 0.5 0 0.091 3.014 (2.923) 0

3 Mahardika 0 0 1 0.5 0 0.091 3.014 (2.923) 0

4 Adnyana 0 0 1 0.5 0 0.091 3.014 (2.923) 0

5 GA Rai 0 0 1 0.5 0 0.091 3.014 (2.923) 0

6 Arnawa 0 0 1 0.5 0 0.091 3.014 (2.923) 0

7 Sudarsa 0 0 1 0.5 0 0.091 3.014 (2.923) 0

8 Yasa 0 0 1 0.5 0 0.091 3.014 (2.923) 0

9 Dharma 0 0 1 0.5 0 0.091 3.014 (2.923) 0

10 Wiyana 0 0 1 0.5 0 0.091 3.014 (2.923) 0

11 I Bagus 0 0 2 1 0 0.183 3.747 (3.565) 0

12 Suarta 0 0 2 1 0 0.183 3.747 (3.565) 0

13 Daging 0 0 1 0.5 0 0.091 3.014 (2.923) 0

14 Rahayu 0 0 4 2 0 0.365 5.213 (4.848) 0

15 Nadri 2 67 3 3 1 3.274 3.340 (0.066) (0.066)

16 Krutuk 2 67 3 1.5 3 3.274 4.480 (1.207) (0.402)

17 Karindya 2 40 5 2.5 3 3.456 5.946 (2.490) (0.830)

18 GKPB 0 0 53 17.7 39 4.836 42.271 (37.435) (0.960)

19 Sudania 0 0 11 5.5 7 1.004 10.344 (9.341) (1.334)

20 Restu 0 0 7 3.5 5 0.639 7.412 (6.774) (1.355)

Bottom 20

1 Kuncir 0 0 8 8 1 0.730 7.005 (6.275) (6.275)

2 Narta 0 0 3 1.5 1 0.274 4.480 (4.207) (4.207)

3 Arwita 0 0 3 1.5 1 0.274 4.480 (4.207) (4.207)

4 Ridia 0 0 9 4.5 2 0.821 8.878 (8.057) (4.029)

5 Wiarti 0 0 4 4 1 0.365 4.073 (3.708) (3.708)

6 Nanda 0 0 2 1 1 0.183 3.747 (3.565) (3.565)

7 Dentra 0 0 2 1 1 0.183 3.747 (3.565) (3.565)

8 Ember 0 0 2 1 1 0.183 3.747 (3.565) (3.565)

9 Wicaya 0 0 7 3.5 2 0.639 7.412 (6.774) (3.387)

10 Nuriada 0 0 6 3 2 0.548 6.679 (6.132) (3.066)

11 Sunyata 0 0 1 0.5 1 0.091 3.014 (2.923) (2.923)

12 Widnyana 0 0 1 0.5 1 0.091 3.014 (2.923) (2.923)

13 Sanur 0 0 1 0.5 1 0.091 3.014 (2.923) (2.923)

14 Adnyana 0 0 1 0.5 1 0.091 3.014 (2.923) (2.923)

15 Pusmawan 0 0 1 0.5 1 0.091 3.014 (2.923) (2.923)

16 Lanus 0 0 1 0.5 1 0.091 3.014 (2.923) (2.923)

17 Ariawan 0 0 1 0.5 1 0.091 3.014 (2.923) (2.923)

18 Budiasih 0 0 1 0.5 1 0.091 3.014 (2.923) (2.923)

19 Nirta 0 0 1 0.5 1 0.091 3.014 (2.923) (2.923)

20 Santika 0 0 1 0.5 1 0.091 3.014 (2.923) (2.923)


It was estimated that the average number of goats sold/year per flock in 2014 was 0.2 ± 0.1 goats

(Table 7.3) with a total income per flock of IDR 0.670 ± 1.468 million. Therefore, sale of goats

was IDR 314.286 million per 100 goats per year or IDR 810.850 million for the 258 goats reared in

Mendoyo District (Figure 7.3).


142


Table 7.3 Average number of different classes of goats sold per household in Mendoyo District,

Jembrana Regency. Class of goat n Mean ± SEM Range Minimum Maximum Mode

Flock size (goats) 68 3.8 ± 0.8 52 1 53 1

F preweaned 1 2.0 ± 0.0 0 2 2 2

F weaner 1 2.0 ± 0.0 0 2 2 2

M preweaned 2 2.0 ± 0.0 0 2 2 2

M weaner 1 6.0 ± 0.0 0 6 6 6

Total number of goats sold 68 0.2 ± 0.1 6 0 6 0

Each household sold an average of 0.2 ± 0.1 goats in 2014 (Table 7.3 and Figure 7.3). Of the 258

goats reared in Mendoyo District in 2014, only five farmers sold 14 goats i.e. 2 preweaned female

kids, 2 weaned female kids, 4 preweaned male kids and 6 weaned male kids in 2014. There were

no pregnant or lactating females sold. The prices for goats sold in Mendoyo District for different

purposes were the same as the prices of goats sold in 2014 in Rendang District as well as in Banjar,

Busungbiu and Grogak Districts that are given in Table 13 (Appendix 1).

0

2

4

6

8

10

12

14

No. of goat sold Total prices (IDR million)

N

o

.

o

f

g

o

a

t

s

F preweaned F weaned M preweaned M weaned sold

F=Female, M=Male, All preweaned=aged 0 – 4.5 months; All weaned=4.5 month – I0;


prices (IDR million) of goats reared in Mendoyo District.

The average flock size was 4 ± 1 goats and this ranged between 1 and 53 goats (Table 1 in

Appendix 1) where 64 farmers had the smallest flock size of 1≤10 goats and 4 farmers had larger

flock sizes of 11≤53 goats (Tables 7.11 and 7.12; and Figure 7.4). This indicated that flocks of

1≤10 and 11≤53 goats generated negative GM(A-B) of IDR (3.599 ± 0.435) million and IDR

(16.810 ± 1.740) million, respectively when they made 5 ± 3% and 0 ± 11% turn off rate,

respectively. These two flocks also generated negative GM/doe of IDR (2.570 ± 0.181) million and

IDR (1.852 ± 0.645) million (Figure 7.4).


143



four different flock sizes.

The average turn off rate for the 68 flocks was 5 ± 3% which generated a loss GM(A-B) of IDR

4.376 ± 0.565 million as well as a GM/doe loss of IDR 2.518 ± 0.174 million (Table 2 in Appendix

1). Turn off rate was not significantly different (P>0.05) between the two groups of flock sizes,

although the flock size, number of does and bucks owned per household were significantly different

(P<0.05) (Tables 7.11 and 7.12; and Figure 7.4). This was due to the fact that the number of goats

sold/year, by smallholder farmers with the two different size flocks, were not significantly different

(P>0.05). Of the 258 goats, only 14 goats in different physiological states were sold with the total

price of IDR 22 million or approximately AUD$2,200/68 smallholder farmers in 2014. It was

predicted that the total price of goats sold would be remain stable, as the farmers were increasing

the number of goats in their flocks and apparently would not sell goats prior to Eid Qurban.



All (100%) households interviewed in Mendoyo District kept goats as a source of fertilizer along

with the Simantri Programmes that they had received in October 2013 and April 2014. All the

smallholder farmers interviewed used only goat manure produced to fertilize their crop plantations.

The manure sold contributed IDR 23.542 million or 52% to the IDR 45.542 million of the total

income, while IDR 22 million or 48% was generated from goats sold. Although all (100%) farmers

housed their goats in battery housings, the average flocks of 4 ± 1 goats produced insufficient

quantity of goat manure to fertilize their 0.9 ± 0.1 ha of cultivated land (Table 1 in Appendix 1).


144


Other benefits of rearing goats were the farmers utilised their cacao waste for goats feed. They also

utilised the roughage that was purposefully planted as shade trees in their coffee or cacao

plantations as well as to utilise the cacao pods waste as feed for their goats. The third objective for

keeping goats was to increase income as their ―living bank‖ with goats sold when cash was needed.

No farmers studied in Mendoyo District milked, consumed or sold goat milk.


Cut and carry feeding systems were used to feed their goats with Caliandra calothrysus, Sesbania

sesban, Erythrina variegata, Artocarpus heterophyllus and Pennisetum purpureum twice a day at

noon and in the evening at 5:00 pm. The amount of fresh roughage fed to their goats was about 5

kg/goat/day regardless of their physiological state. The mixture of roughage that were purposefully

planted as living fences or shade trees in coffee or cacao plantations were never measured for their

quality. The farmers also fed their goats with unfermented chopped cacao pods about 100

g/goat/day. This feeding management resulted in reasonable bodyweights for all physiological

states of goats reared in Mendoyo District (Tables 6 and 7 in Appendix 1).


Kid mortality was 24% that occurred in their first weeks of life when six kids died as they were

born as twins and triplets. Metabolic disturbances, toxicity, bloat and scabies commonly occurred

in preweaned kids in Mendoyo District. Although all goats were kept in battery housing in cacao

plantations, dogs were not predators to kids reared in Mendoyo District. However, the goat housing

was quite far from the farmer‘s houses. As a result, farmers paid less attention to health status as

well as breeding management of their goats.

Farmers in Mendoyo District never injected their goats with Klosan200™

(an anthelmintic) or any

other medications to control diseases or parasites. The average FAMACHA©

score for all goats

during the study was 1.5 and ranged between 1.1 ± 0.2 for male weaners and 1.9 ± 0.2 for lactating

does (P<0.05). As the incidence of anaemia was low, farmers did not inject their goats with any

medication to treat for internal parasites.


The 68 households interviewed in Mendoyo District housed all their goats in individual pens in

elevated slatted battery housings. The poles and floor in this housing system were usually made

from bamboo or wood. The floor of the battery house was about 1 to 1.5 meters above the ground.

The floor slats had gaps that were between 15 to 25 mm wide that ensured faeces fell through and


145


together with urine accumulated under the floor to be used as manure for crops. With this housing

system, it was easier for farmers to clean pens and to collect the manure used for fertilizer.

However, the goat housings that were located in crop plantations were quite far from the farmer‘s

house. This sometimes caused the farmers to miss observing female goats in oestrus, which meant

they missed the opportunity to bring a buck to mate them. The average weaning period was 135

days and does were usually re-mated as soon as the does had their oestrus postpartum. Farmers had

never used artificial insemination with their does.

7.4 Discussion



smallholder production systems in Mendoyo District could be used to improve their goat production

(Table 1 in Appendix 1). Ceasing goat rearing for quite some time, for various reasons, smallholder

farmers in Mendoyo District re-started rearing goats again in October 2013 and April 2014 when

they received Simantri Programmes (Tunas, W. 2014, pers. comm. 9 June). Smallholder farmers

faced problems such as having traumatic experiences where their goats got sick and had low

performance and/or died due to mouth and foot diseases; lack of capital to restart rearing goats

again; low numbers of household labourers; and not being young anymore (47.3 ± 1.4 years) to

manage their crops along with rearing goats at the same time. This indicated that the farmers were

old and did not have much physical energy necessary to contribute to farming as would be expected

from them. On the other hand, farmers who reared small flock sizes produced insufficient goat

manure to fertilize the 0.9 ± 0.1 ha of their crops (Table 1 in Appendix 1). Strangely farmers that

had the highest education level tended to have the lowest labourer ratio, the smallest turn off rate

and generated loss in both GM(A-B) and GM/doe (Tables 7.5 and 7.6)

One reason for the reduction in the number of goats in Mendoyo District was possibly that this

district had the lowest number of children per household (P<0.05) (Table 1 in Appendix 1).

Farmers‘ children did not stay on the farm – they went to study in Denpasar City or to work on

cruise ships overseas. Artini et al. (2011) and Nilan and Artini (2013) reported that cruise ship

work was an increasingly popular career choice for senior high school graduates in Bali Province,

where the main industry was tourism. The low number of children per household, along with the

old age of the farmers, limited the number of household labourers to rear more goats integrated with

the crop plantation, as hiring labourers outside the household was rare and relatively expensive.

Limitations of the availability of family labourers resulted in a new critical threshold for farm


146


growth strategies in Mendoyo District. Based on its low profitability and the amount of labour

required, it is unlikely that the younger generations would be interested in taking up goat

husbandry, so it is a trend that is bound to continue.

The average age of the smallholder farmers in this study, 47.3 ± 1.4 years, was in agreement with

the Act of the Republic of Indonesia number 13 year 2003 concerning manpower that categorized

ages as productive between 15 years and 64 years. However, 16% of the households were aged

between 65 and 73 years with 9.2 ± 1.1 years of goat rearing experience. This indicated that some

of the smallholder farmers had to maintain crop farms integrated with goat rearing although they

were not young anymore. Smallholder goat farmers in Malang Regency, East Java, besides

cultivating an average of 1.35 ha for crop farms, 32% respondents reared about 8 to 20 goats per

household involving more family members as labourers i.e. 5-7 household labourers whose ages

were younger than Indonesian manpower age standard i.e. 10 to above 65 years old (Hartono et al.

2006). This indicated that the higher the levels of education of children of the households studied in

Mendoyo District, the less interested in goat rearing they were (Table 5 in Appendix 1). They

preferred studying or working in Denpasar City or abroad to rearing goats. Having a low number of

household labourers that would maintain goat rearing, integrated with crops, seemed to be a

constraint to improving goat rearing in Mendoyo District.

This study revealed that the level of education of the household played an important role in

dictating the best production parameters. The level of farmer education per se, could be expected to

improve the efficiency of goat production, but it is hypothesised that farmers with a better education

would implement improved husbandry practices. Although farmers‘ education level did not

significantly affect their GM/doe, the farmers with the highest education level tended to have higher

GM/doe (Table 4 in Appendix 1). This indicated that the higher education level of the farmers, the

better the decisions they make for efficient goat production such as having larger numbers of does

per household, and having a larger ratio of household labourers to their goats. It may be assumed

that increased education leads to a better understanding on how to have more efficient goat

production (Netting 1993; Shindina et al. 2015).

Of the smallholder farmers studied in Mendoyo District, 81%, 11% and 8% of them had completed

Grade 1, 2 and 3, respectively. These levels of education were lower than those of smallholder

farmers in Malang District, East Java i.e. 41%, 28% and 16% for Grade 1, 2 and 3, respectively

(Hidayati et al. 2012). However, smallholder farmers studied in Mendoyo District (16% of them

were aged 65≤73 years and 84% of them aged 15 to 64 years) were older than smallholder farmers


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in Malang Regency (20% of them aged between 49-61 years and 80% of them aged 20 to 48 years).

Being old with the low numbers of household labourers, they faced the challenge to improve their

goat flock size when the current flock size i.e. 4 ± 1 goats provided insufficient goat manure to

fertilize their 0.9 ± 0.1 ha of crop farms. Education and governance have major impacts on

agricultural efficiency, therefore, farmers should have higher levels of education (Bayyurt &

Yılmaz 2012).

The ratio of labourers to flock sizes had a strong positive effect (P<0.05) on GM/doe. The larger

the ratio of labourers to flock size, the larger GM/doe would be generated by the household. The

labourer cost inputs in this study i.e. based on regional Bali minimum wage labourer rate, were

higher than reported by Budisatria et al. (2008) who calculated it as 33-38% below the minimum

wage labour rate. This study revealed that the households with the largest number of labourers

were efficient in terms of labourer cost paid per household (Tables 7.3 and 7.4). These households

had the highest flock size, the highest labourer ratio, the highest number of does owned and yet still

sold the lowest number of goats i.e. 0 ± 0.4 and only had a low i.e. 3 ± 10% annual turn off rate.

The only farmer in Mendoyo who had a 150% turn off rate, had GM (A-B) of IDR 6.792 million

and GM/doe of IDR 3.396 million which were higher than IDR 1.747 million reported by Hartono

et al. (2006). This indicates that more goats could be sold and there was an opportunity to improve

the GM(A-B) and GM/doe. However, farmers in Mendoyo District involved in this study preferred

increasing their flock sizes to selling their goats.


Determining the flock size of goats and the reasons that smallholder farmers in Bali Province kept

goats were crucial to determine GM(A-B) and GM/doe. Flock size, more importantly the number

of does owned by households, was one of the factors that influenced the GM(A-B) or GM/doe

gained by smallholder farmers in Bali Province. All the body dimension measurements of

preweaned, weaner and yearling males were significantly higher than of preweaned, weaner and

yearling females (P<0.05). The average of 29.8 ± 1.9 kg bodyweights of male weaners in this study

were significantly higher (P<0.01) than the 22.9 ± 1.6 kg of female weaners (Tables 6 and 7 in

Appendix 1). This was in agreement with Souza et al. (2010) and Dias Medeiros et al. (2012) who

reported that male kids grew faster and heavier than female kids. The reasonable growth rates of

preweaned and weaned kids indicated that smallholder farmers in Mendoyo applied good kid

rearing management, thus improving goat production.


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Average height at withers of goats reared in Mendoyo District i.e. 66.0 ± 0.7 cm was categorized as

a Large type goat (Devendra & Burns 1983; Devendra & Haenlein 2011) (Tables 6 and 7 in

Appendix 1). Based on the body dimension measurements, it appeared that goats were PE goats

with longer ears. This indicated that larger size goats usually produced more milk and meat than

smaller ones (Abebe et al. 2010; Devendra & Haenlein 2011). Female yearlings aged 0.5 – 1 year

studied in Mendoyo District had an average of 26.2 ± 1.4 kg bodyweight, 66.1 ± 1.5 cm chest

circumferences and 64.8 ± 1.3 cm height at withers. These body dimensions were within the range

of the required physical standard of PE breeding stock by Indonesian National Standard (SNI 2008).

This indicated that it was a good time to expand the number of goats in Mendoyo District as good

breeding stock was being farmed. Expanding quality-breeding stock could be one of the

development strategies that will help in improving their goat production.

Assuming that of the 258 goats, the 139 does produced single birth kids in three kiddings in two

years and had 10% mortality of these kids, the 139 does could produce 187 kids with a ratio of 93

female and 94 male kids. Thus kid replacement = 25% X 139 does = 35 female kids would be kept

while the remaining 58 female kids plus 94 male kids and 35 culled does equals 187 goats to be

sold which makes 187 goats sold/258 goats in total = 82% annual turn off rate in 2014.

In the same manner, assuming of the 258 goats, when 139 does produced twin birth kids in three

kiddings in two years and had 10% mortality of these kids, the 139 does could produce 375 kids

with a ratio of 187 female and 188 male kids. Therefore kid replacement = 25% X 139 does = 35

female kids would be kept while the remaining 152 female kids plus 188 male kids and 35 culled

does equals 375 goats were sold which makes 375 goats sold/258 goats in total = 145% annual turn

off rate in 2014. This indicates that with the 139 does out of 258 total goats reared in Mendoyo

District, smallholder farmers could produce or sell 187 to 375 kids annually or make an 82% to

145% annual turn off rate. Selecting kid replacements from large numbers of kids produced could

be better in improving breeding stock thus improving their goat production from the small number

of kids produced on the farms.

Overall, 49 parturitions produced 67 kids that were born in the first six months of 2014 in Mendoyo

District. There were 75 pregnant does or 54% of the 139 does recorded in the 68 flocks in 2014 in

Mendoyo District. This figure was larger than 25% of flock sizes recommended by Morand-Fehr et

al. (2004). This indicated that flock size could be expanded in two or three years to achieve a larger

proportion of does, and bucks owned per household in Mendoyo District. Expanding flock size by


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households could be one of the development strategies that will help in improving their goat

production with no goats sold in 2014.

The largest flock of 53 goats that included four bucks and 39 does, six female preweaned kids, a

female weaner, two female yearlings and a male preweaned kid, had 37 pregnant does and was

making a big effort to expand flock size in Mendoyo District. This was shown by selling zero goats

and thus they had zero per cent annual turn off rate in 2014. Furthermore, the smallholder farmer

had four bucks to mate the 39 does to ensure a high pregnancy rate i.e. 95% had been achieved, thus

a high kidding rate. The smallholder farmer also paid attention to the body dimensions of his goats.

The average bodyweights, chest circumferences and height at withers of 39 does aged 1-2 years

reared on this farm were 33 ± 1 kg, 73 ± 1 cm and 69 ± 1 cm, respectively while for the four bucks

aged 1-2 years these were 38 ± 4 kg, 79 ± 3 cm and 78 ± 3 cm, respectively for the three

measurements. These body dimensions were within the range of the required physical standard of

PE breeding stock by Indonesian National Standard (SNI 2008). SNI (2008) required 34 ± 6 kg, 76

± 7 cm and 71 ± 5 cm for breeding stock PE does aged 1-2 years while 49 ± 9 kg, 80 ± 8 cm and 67

± 5 cm for breeding stock PE bucks aged 1-2 years for the three measurements, respectively. This

indicates that having a large flock size with the correct proportion of does and bucks as well as

having three household labourers per household and a high standard of breeding stock could be one

of the development strategies that will help in improving their goat production.


Total sale of manure i.e. IDR 23.542 million and sale of goats i.e. IDR 22 million contributed 52%

and 48% to the total income of IDR 45.542 million for the flocks studied in Mendoyo District.

Although goat rearing contributed a high income i.e. GM (A-B) IDR 6.792 million and GM/doe

IDR 3.396 million to the farmers as shown in Table 7.2, farmers in Mendoyo District preferred

increasing the number of goats in their flocks. Their goats were quality-breeding stock as they

achieved the required physical standard of SNI (2008). However, other farmers including the one

who had the largest flock of 53 goats had an opportunity to sell goats and thus had a higher turn off

rate, GM(A-B) and GM/doe. This household was expanding their flocks and apparently would not

sell goats prior to Eid Qurban (Tables 7.10 and 7.11). Expanding flocks by smallholder farmers

studied in Mendoyo District almost made a zero per cent of turn off rate and thus generated

negative GM(A-B) and GM/doe. This indicated that in future, Mendoyo District could have more

goats to produce organic fertilizer for their crops and to sell both fertilizer and live animals.


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The average turn off rate recorded in 2014 was 5 ± 3% where only preweaned female and male kids

and weaners female and male kids were sold in 2014 (Table 12 in Appendix 1). It was likely that

smallholder farmers in Mendoyo District were not able to sell more goats prior to Eid Qurban in

October 2014. Therefore, the turn off rate was likely to be stable and would not significantly affect

GM(A-B) and GM/doe in all flock sizes. As members of the smallholder goat farmers association

who received the Simantri programme, they had an agreement with the Bali Government that they

would not sell their goats until they kidded.

Overall, goat rearing in Mendoyo District, had average GM(A-B) and GM/doe of IDR (4.376 ±

0.565) million and IDR (2.518 ± 0.174) million, respectively, when they had a low turn off rate of 5

± 3% (Table 2 in Appendix 1). When all flocks were ranked based on GM/doe, only one flock had

a positive GM/doe of IDR 3.396 million and this flocks consisted of four goats that included two

does, and six goats were sold and had a 150% turn off rate (Table 7.2). However, an assumption

was made that owning the four goats with one buck, one female yearling and two does, in 2014,

produced three female and three male kids (i.e. 2 does X 3 kids X 2 as twins per 2 years with 0%

mortality). Therefore, when a female kid was kept for replacement, two female and three male kids

and a culled doe could be sold with a 150% turn off rate.

The bottom 20 households of GM/doe generated the largest loss of IDR 6.275 million when the

farmer who had eight goats including one doe and sold no goats. Although this farmer did not

generate the largest loss of GM(A-B), the farmer generated the largest loss of GM/doe as the

GM(A-B) was divided by one doe. In contrast, the household that had the largest flock of 53 goats

including 39 does had the largest ratio of household labourers to goats i.e. 17.7 goats per household

had the largest total variable cost of IDR 42.271 million as well as the largest loss of GM(A-B) of

IDR 37.435 million. However, this household was the 18th

of the top 20 for GM/doe. This

indicated that the number of does owned per household largely dictated the efficiency of goat

production. The larger the number of does owned by the household, the greater opportunity they

had efficient goat production and thus generated higher GM/doe.

Although the number of does per household significantly affected the GM(A-B) and GM/doe

(P<0.05), other factors that also contributed to these two production parameters had to be

considered. Annual equivalent working hours, the labourer to goat ratio or farmer education level

of flock size did not significantly (P>0.05) affect the GM/doe (Tables 7.3, 7.5 and 7.11). This

indicated that as long as the number of does owned per household did not generate positive values

of GM(A-B) and GM/doe, other factors contributed to generate higher positive or negative values


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for GM(A-B) and GM/doe. That was as long as the number of does owned per household covered

labourer, feed and health control costs, farmers generated positive GM(A-B) and GM/doe (Tables

7.9).

Goat marketing in Mendoyo District was not well managed by goat farmer associations as they had

just re-started rearing goats again and had only sold a few goats. Goat brokers were common in

Mendoyo District, and as such, there was a longer supply chain and this potentially reduced the

possibility of gaining better selling prices for goat farmers in Mendoyo District. Most of the

transactions between goat farmers and buyers occurred on goat farms. Goat buyers were

categorised as four types: breeder, meat retailers, satay sellers and occasional buyers. As the goat

population reduced in Jembrana Regency, farmers as well as larger satay sellers preferred buying

goats from East Java Province that provided stable and lower prices. Smallholder farmers did not

have any constraints to marketing their goats. In contrast, they faced constraints to fulfil the

opportunities as well as the challenges to supply demand for goats within Bali Province, particularly

for Eid Qurban.



interviewed in Mendoyo District were not sure how to predict the age of their goats and had never

weighed their goats even when they sold them. Furthermore, farmers had never recorded the

productive nor reproductive parameters of their goats. This is a constraint to rearing goats in

Mendoyo District as it means farmers have no data on how well their animals are performing.


All households interviewed in Mendoyo District had just re-started rearing goats again after they

had experienced low goat production and great losses due to mouth and foot diseases in their goats.

Therefore, their main priority of keeping goats was to increase the size of their flocks, as the

amount of goat manure produced per household was insufficient to supply their organic fertilizer

(Table 1 in Appendix 1). This was in agreement with Guntoro (2012) who reported that to have

high cacao production, one ha of cacao plantations needed goat manure produced by 25 to 28 goats.

This indicated that the smallholder farmers in Mendoyo District have the opportunity to increase

crop productivity with more goats; but expansion of their flocks may be constrained by their age

and low numbers of children.


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Identifying the feed and feeding management used by smallholder goat farmers in Bali Province

was crucial to improving their goat productivity. Goats in this study were fed with fresh Caliandra

calothrysus, Gliricidia sepium, Sesbania sesban, Erythrina variegata, Artocarpus heterophyllus or

other bushes or field grasses at about 5 kg/goat/day regardless of their physiological state. This

result was supported by Nitis (1997) who reported that smallholder farmers in Bali, apart from

growing crops as their main production, also practiced traditional silvipastoral systems by growing

shrubs and trees and keeping livestock as a sideline. Devendra (1985a) stated that goats were great

economic value ruminants for their efficient converters of low-quality forages into quality meat and

milk products. This was supported by Surai (2002) who reported that feeding goats with various

herbaceous roughages provided balanced proportions of nutrients in the goat‘s diet as they

contained natural antioxidant rich diets that have become especially important for their growth,

survival, maintenance and health status. This feeding management resulted in comparable

bodyweights for all physiological states of goats reared in Mendoyo District (Tables 6 and 7 in

Appendix 1).

Smallholder farmers in this study also fed their goats with unfermented chopped cacao pods of

about 100 g/goat/day. This was in agreement with Prawirodigdo et al. (2005) who suggested that

goats be fed with un-processed cacao pods at a maximum amount of 100 g/goat/day, that increased

daily weight gain of 70 g/goat/day. This was due to the un-processed cacao pods containing low

protein, relatively anti nutritional compounds such as lignin, tannin and theobromine that limited

the efficiency of its digestion (Suparjo et al. 2011; Riyanto & Anam 2012; Wisri & Susana 2014).

Utilizing treated cacao pods or coffee pulp from their agriculture wastes, as goats feed that was

mixed with cut and carry feeding, might be the best choice because of their limited number of

household labourers or their old age. Hartono et al. (2006) reported that cut and carry feeding

systems, such as looking for roughage/grass, smallholder farmers in Malang Regency, East Java

needed 36% of their daily labourer, while transporting the roughage, mixing the roughage with

other feedstuffs and feeding the goats required about 12%, 5% and 21%, respectively. Cleaning

goat housing and rearing kids, the farmers needed about 1% and 25% of daily labourer hour,

respectively. Since feeding management was the most time consuming and costly for goat farming

(FAOSTAT 2015), by treating the cacao pods and coffee pulp, the farmers could minimise

problems. Cacao pod contains crude protein from 6.8 to 13.8%; NDF from 55.3 to 73.9% and ADF

from 38.31 to 58.98% was a good fibre source and could replace grass for goats (Wisri & Susana

2014). However, cacao pods also contains anti nutritional compounds such as lignin, tannin and


153


theobromine (Suparjo et al. 2011; Riyanto & Anam 2012; Wisri & Susana 2014). Suparjo et al.

(2011) reported that by using P. chrysosporium increased crude protein up to 13.8% from 8.7% of

untreated cacao pods thus increased daily gain of goats from 102 g/goat/day (Suparjo et al. 2011)

and 100 to 125 g/goat/day as well as milk production from 1.00 to 1.25 litre/goat/day (Riyanto &

Anam 2012). Utilizing these agricultural wastes as goats feed rather than leaving them as mulch

also helped to conserve the environment of Mendoyo District.


Although the farmers studied in Mendoyo District never injected their goats with Klosan200™

(an

anthelmintic) or any other medications to control diseases or parasites, the incidence of anaemia as

measured by the FAMACHA©

technique in all classes of goats was nil. This was probably due to

the housing management system being well maintained. Furthermore, the smallholder farmers in

Mendoyo District had just received the package of Simantri Programme including the goat housings

that apparently new.


Goat farmers studied in Mendoyo District actually had implemented a recommendation by

Martawidjaja (1992) who suggested to house goats in individual battery housing systems for

hygienic reasons as it was easy to clean the houses as well as to collect the goat manure. In

addition, smallholder farmers had paid attention to the cutting height as well as the cutting time of

roughages fed to their goats.

However, the mortality rate in this study i.e. 24% of newly born kids was considered high as six

kids died when they were born as twins and triplets. This was probably due to the kids born having

low birth weights. Furthermore, most of the goats were housed quite a distance from farmers‘

houses, so the goat farmers paid less attention when the low birth weights newly born kids needed

help to ensure they received sufficient quantities of colostrum as well as does‘ milk. This result was

confirmed by Snyman (2010) who reported that low birth weights; unthrifty kids who needed help

with suckling, does having little or no milk, and does abandoning their kids were the major

contributors to high mortality of newly born kids. Birth weight and the sex of the kid had a

significant influence on pre-weaning mortality rates where triplet-born kids had the highest

mortality rate (22%), followed by twinborn (13%) and single-born kids (10%) kids (Snyman 2010).

The distance to the goat housing also increased the occurrence of metabolic disturbances, toxicity,

bloat and scabies in preweaned kids. High kid mortality as well as the distance to the goat housing

were constraints to improving goat rearing in Mendoyo District.


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7.5 Constraints to improving goat production in Mendoyo District in Jembrana Regency

In summary, the constraints to improving goat production in Mendoyo District in Jembrana

Regency were:

Farmers having small flock sizes thus the likely absence of does and bucks in the flocks;

A low ratio of household labourers to flock size;

Farmers having a large number of does that did not kid in the first six months of 2014;

A lack of awareness on the objectives of goat keeping;

Farmers having no records of their goats;

Farmers did not purposefully grow roughage for their goats;

Farmers having the goat housing too far away from farmers house; and

Farmers having a high mortality rate of kids.

7.6 Challenges of improving goat production in Mendoyo District in Jembrana Regency

The challenges of improving goat production in Mendoyo District in Jembrana Regency were:

To increase their flock sizes through efficient goat production; and

To utilise Phanerochaete chrysosporium to ferment cacao pods as feed for goat.

7.7 Opportunities for improving goat production in Mendoyo District in Jembrana Regency

The opportunities for improving goat production in Mendoyo District in Jembrana Regency were:

Average bodyweights of goats in Mendoyo District were high due the farmers had just received

Simantri programmes. Bali Government provided good does and bucks as breeding stock as a

package of Simantri programme;


and

A higher reproduction rate produces more animals for entry into the growing phase of production.

This growth rate may be improved by genetics, nutrition, and disease control.

7.8 Conclusion

In conclusion, smallholder farmers in Mendoyo District reared goats in small flocks as the

farmers had just re-started rearing goats again resulting in inefficient goat production, particularly

when labour costs were included.


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7.9 Suggestions

Suggestions include:

The main suggestion was to improve the size of breeding flocks. This may be accomplished by:

Restructuring the flock profiles with optimum age structure and buck to doe ratio;

Ensuring adequate access to bucks so that does are able to get pregnant immediately after

postpartum oestrus;

Reduce kid mortality;

Keep does only up to their fourth or fifth kidding;

Encourage smallholder goat farmers to practice simple recordings to be able to identify elite

animals and poor quality animals; and

Build networks to ensure quality of breeds, feed and rearing management systems.

Chapter 8 Assessing current goat rearing in Bali Province through a hybrid method of SWOT and AHP analyses

156


Chapter 8

Assessing current goat rearing towards improving productivity in Bali Province, Indonesia through

a hybrid method of Strengths, Weaknesses, Opportunities and Threats (SWOT) and Analytic

Hierarchy Process (AHP) analyses.

8.1 Introduction

Information collected in this thesis on goat rearing, aimed at improving goat productivity in Bali

Province, was assessed with a hybrid method that was composed of SWOT and AHP analyses to

achieve optimal use of the opportunities and control of threats (Kurttila et al. 2000; Ho 2008;

Bayram & Üçüncü 2016; Santopuoli et al. 2016). The primary and secondary data on goat rearing

under smallholder production systems in Bali Province was summarized from various data

resources. The combined data were analysed by using descriptive statistics, correlate bivariate and

general linear model multivariate analyses using SPSS version 24 (Figure 8.1). The roles of

Indonesian Government policies and practices were also reviewed and these were used in this study.

The database of household labourers and their profiles, goats and their profiles as well as the

environmental resources assessments, market assessments, managerial practices of the 175

smallholder farmers with their 2,017 goats in this study were presented. The data from the

overview of goat production systems in Bali Province presented in Chapter 4 is also analysed using

this hybrid method. The proposed SWOT and AHP analyses research framework is summarised in

Figure 8.1.

The strengths and weaknesses of the current reproductive and productive efficiency of goat farming

under smallholder production systems in Banjar, Busungbiu, Grogak, Mendoyo and Rendang

Districts in Bali Province, as well as their socio-economic analysis and their opportunities and

threats originating from each district, were determined using the SWOT matrix. The information

obtained from the SWOT matrix was integrated into the AHP hierarchy to identify the most

important factors in each district as well as the optimum strategies for improving goat production

(Kurttila et al. 2000; Ho 2008; Bayram & Üçüncü 2016; Santopuoli et al. 2016).


157


Figure 8.1 Proposed SWOT analysis and Analytic Hierarchy Process research framework.

Adopted from Ho (2008), Umeta et al. (2011), Lai and Hitchcock (2015), Zare et al. (2015) and

Bayram and Üçüncü (2016).

The objectives of this chapter are to (1) summarise current goat production under smallholder

production systems in Banjar, Busungbiu, Grogak, Mendoyo and Rendang Districts in Bali

Province that have been fully described and discussed in the previous three chapters and (2) to

discuss strategies to improve goat production.

The database of the current goat production in Bali Province was mapped using a hybrid method

composed of SWOT and AHP analyses. The identification of mechanisms, actions, innovations

developed by 175 smallholder farmers with their 2,017 goats, for reducing their constraints and

responding to their challenges, as well as the opportunities for improving their goat production are

Primary and secondary data collection

The Department of Husbandry and

Agriculture in Bali Province

Statistics Bali

Statistics Indonesia

The Department of Meteorology and

Geophysics Indonesia

Case studies

Direct observations

Environmental resources assessments

Market assessments

Managerial practices

Structured formal household interviews

Meetings

Key informant interviews

Focus group discussions and

Structured questionnaires

Determine the constraints, challenges and

opportunities to improve goat rearing in Bali

Province

Established current data:

Household labourers and their profiles

Goats and their profiles

Socio-economic analysis

Effects of managerial and environmental

factors on production parameters in five

districts namely:

Banjar District

Busungbiu District

Grogak District

Mendoyo District and

Rendang District

SWOT analysis & Analytic Hierarchy Process

Determine the strengths, weaknesses, opportunities and threats of rearing goats in Bali Province

and find out the best strategies to improve goat rearing in Bali Province.

Research design and data collection

Research direction

Establish database of current goat rearing in

Bali Province

Identify the constraints, challenges and

opportunities to improve rearing goats in Bali

Province

Find out the best strategies to improve rearing

goats in Bali Province.

Data analysis

Descriptive statistics

Correlate bivariate

General linear model multivariate

Reliability and validity

Pearson Correlation

Measure the level of importance

SWOT analysis & Analytic Hierarchy Process

Pearson Correlation


158


also discussed. Finally, this study provided suggestions for further research and government policy

intervention to improve the efficiency of goat rearing in Bali Province.

8.2 SWOT and AHP analyses

The information and data used were from the structured questionnaires collected in Banjar,

Busungbiu, Grogak, Mendoyo and Rendang Districts in Bali Province. All the data, presented in

Chapters 4, 5, 6, and 7, were used to determine the SWOT factors and are summarised in Table 8.5

while the hierarchic structure of the SWOT analysis for AHP is summarised in Figure 8.2.

Figure 8.2 Hierarchic structure of the SWOT analysis for AHP

Goat production practices in all districts studied were constrained by a variety of factors. A

pairwise ranking method was employed to assess the detail of these problems that were associated

with specific parameters of goat production in particular districts. The result of this pairwise

ranking analysis showed that, in most cases, the Pearson correlation ranked the factors influencing

goat production in each districts differently as shown in Tables 8.1 to 8.4.

External

Strategy

evaluating

Internal

Strengths

Weaknesses

Opportunities

Threats

S1

S2

Sn

W1

W2

Wn

O1

O2

On

T1

T2

Tn

SWOT groups SWOT factors


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Size of land cultivated per household (ha)

Among the 175 smallholder goat farmers studied, the smallholder goat farmers in Rendang District

had the largest average size of 2 ± 0.1 ha land cultivated per household (Tables 8.1 and 1 in

Appendix 1) along with free access to grow roughage in conservation forest. There were no

significant differences (P>0.05) within the households in Rendang District on the size of the land

cultivated nor with other parameters of goat production. However, the average size of 1.2 ha land

cultivated by smallholder goat farmers in Bali Province was the most important parameter of goat

production. The results of the pairwise analysis showed that it had strong positive correlations with

the flock size per household, labourer ratio to flock size per household, number of bucks owned or

goats sold or does owned per household, and the number of household labourers per household

(P<0.01) (Tables 8.1 and 1 in Appendix 1). However, the average size of 0.6 ± 0.1 ha land

cultivated in Grogak District or 1.7 ± 0.1 ha of land cultivated in Busungbiu District had no

significant correlation with other parameters of goat production (P>0.05). The size of land

cultivated by smallholder goat farmers in Banjar District i.e. 0.9 ± 0.2 ha and Mendoyo District i.e.

0.9 ± 0.1 ha had strong positive correlations with four other parameters of goat production (P<0.01)

but the Pearson correlation ranked the factors influencing goat production in each district differently

(Tables 8.1 and 1 in Appendix 1).

Table 8.1 Rank in order of importance of pairwise Pearson correlations, between the size of land

cultivated (ha) and other parameters of goat production, in Banjar, Busungbiu, Grogak, Mendoyo

and Rendang Districts, Bali Province. Size of land cultivated per household (ha)

correlated with parameters of goat production

Regency Province

Buleleng Jembrana Karangasem

Banjar Busungbiu Grogak Mendoyo Rendang Bali

Flock size per household 2* - - 3** a 1**

Labourer ratio to flock size per household 2* - - 2** a 2**

No. of bucks owned per household - - - 1** a 3**

No. of goats sold per household 1** - - - a 4**

No. of does owned per household 3* - - 4** a 5**

No. of household labourers per household - - - - a 6**

Education level of households - - - - - -

Total 4 0 0 4 a 6

The rank of (1) had the highest value of R2 while (6) had the lowest of R2 that its correlation was significant at the 0.01 level or the

0.05 level (2-tailed). The (-) indicated that there was no significant correlation between the two parameters of goat production

(P>0.005). The a indicated that it could not be computed because at least one of the variables was constant.

The average size of 1.2 ha land cultivated in this study was bigger than the average size of land

cultivated per household in Asia countries i.e. less than 2 ha with the smallest sizes of 0.3 to 0.6 ha

reported by Devendra (2007). It was also bigger than 0.3 to 0.5 ha cultivated per household by

smallholder farmers in Central Java (Suranindyah et al. 2009a; Suranindyah et al. 2009b) or 0.17 ±

0.03 ha, 0.31 ± 0.04 ha and 0.59 ± 0.08 ha owned by small ruminant farmers in lowlands, middle

zone, uplands of agro-ecological zones in Central Java, Indonesia, respectively (Budisatria et al.

2007). Unlike the typical smallholder farmers in Java Island that had limited land or were landless


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(Budisatria et al. 2007; Suranindyah et al. 2009a; Suranindyah et al. 2009b), smallholder farmers in

Bali owned and cultivated their own land (Nitis 1997; Nitis et al. 2004). The ownership as well as

the size of land cultivated per household i.e. 1.2 ha, for growing crops using goat manure as organic

fertilizer by the smallholder farmers in Bali Province were a major strength to improving goat

production as well as their crops. This result was confirmed by Hidayat (2007) who reported that

the land size and flock size were significant components that contributed to the profits of IDR 6.219

million gained from integrated paddy, fish and goat farming in Banyumas Regency in Central Java

Province. The average GM(A-B) loss of IDR 0.357 ± 1.067 million per household from goat

farming studied in Bali Province was lower than in Banyumas Regency reported by Hidayat (2007)

due to goat farmers only having an average of 28 ± 3% annual turn off rate. This indicated that

when goat farmers had higher than 33.3% annual turn off rate, they were able to increase both

GM(A-B) and GM/doe. Nevertheless, cultivating 1.2 ha land per smallholder household in Bali

Province could be one of the development strategies that will help in improving their income by

fertilizing the land with organic fertilizer and selling more vegetable crops along with more goats.

Number of household labourers (labourer)

The smallholder goat farmers in Rendang District also had the largest average number of 2.7 ± 0.1

labourers per household (Tables 8.2 and 1 in Appendix 1) along with the equivalent working hours

i.e. 492.5 ± 14.7 hours/number of household labourers per year. There were no significant

differences (P>0.05) within the households in Rendang District on the number of household

labourers nor with other parameters of goat production.

Table 8.2 Rank in order of importance of pairwise Pearson correlations, between the number of

household labourers and other parameters of goat production, in Banjar, Busungbiu, Grogak,

Mendoyo and Rendang Districts, Bali Province. No. of household labourers correlated with

parameters of goat production

Regency Province



Size of land cultivated (ha) a - - - - 1**

Flock size per household a - - 2** - 2**

No. of goats sold a - - 3** - 3**

No. of bucks owned per household a - - - - 4*

No. of does owned per household a - - 1** - 5*

Labourer ratio to flock size per household a 1* 1* - 1 -

Education level of households a - - - - -

Total a 1 1 3 1 5




However, the number of household labourers used by smallholder goat farmers in Bali Province

was the most important parameter of goat production. The results of the pairwise analysis showed

that it had strong positive correlations with the size of land cultivated per household, flock size per


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household, the number of goats sold, the number of bucks owned and the number of does owned

per household (P<0.01). This parameter had strong high correlations with the labourer ratio to flock

size found in Busungbiu, Grogak and Rendang Districts (P<0.01) but not in Banjar District or in

Bali Province (P>0.05) (Tables 8.2 and 1 in Appendix 1).

Education level of the smallholder goat farmers

The smallholder goat farmers in Busungbiu District on the other hand, had the largest average

education level per household i.e. 1.9 ± 0.1 (Tables 8.3 and 1 in Appendix 1) along with the highest

education level i.e. 1.9 ± 0.1 of homemakers. There were significant differences (P<0.01) within

the households in Rendang District on the education level of the farmers with the flock size and the

number of does owned per household (P<0.01). The education level of goat farmers in Banjar

District also had strong high correlations with the number of does owned per household, the flock

size and the number of goats sold per household (P<0.01). However, the education level of goat

farmers was not an important parameter of goat production in Grogak, Mendoyo and Karangasem

Districts or in Bali Province. The results of the pairwise analysis showed that there were no

significant correlations of the education level of Balinese goat farmers to other parameters of goat

production (P>0.05) (Tables 8.3 and 1 in Appendix 1).

Table 8.3 Rank in order of importance of pairwise Pearson correlations, between the education level

of farmers to other parameters of goat production, in Banjar, Busungbiu, Grogak, Mendoyo and

Rendang Districts, Bali Province. Education level of farmer correlated with

parameters of goat production

Regency Province



Flock size per household 2* 1* - - - -

No. of goats sold 2* - - - - -

No. of does owned per household 1** 2* - - - -

No. of bucks owned per household - - - - - -

No. of household labourers per household a - - - - -

Labourer ratio to flock size per household - - - - - -

Size of land cultivated (ha) - - - - - -

Total 3 2 - - - -

The rank of (1) had the highest value of R2 while (3 had the lowest of R2 that its correlation was significant at the 0.01 level or the



Gross margin per doe per household (IDR million)

The smallholder goat farmers in Rendang District had the largest positive average of IDR 6.330 ±

1.226 million for GM(A-B) per household and IDR 0.350 ± 0.228 million for GM/doe per

household when they had an average 44 ± 4% annual turn off rate (Tables 8.4 and 2 in Appendix 1).

While those in Busungbiu District also had high positive values for both GM(A-B) and GM/doe i.e.

IDR 2.662 ± 1.946 million and IDR 0.079 ± 0.362 million, respectively when they had an average

51 ± 6% annual turn off rate (Tables 8.4 and 2 in Appendix 1). In contrast, smallholder goat


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farmers in Banjar, Grogak and Mendoyo Districts and Bali Province generated loss both for GM(A-

B) and GM/doe when they had 26 ± 11%, 11 ± 9% and 6 ± 4% average annual turn off rates,

respectively (Table 2 in Appendix 1). This indicated that the GM/doe in these three districts could

be improved if they sold more goats prior to Eid Qurban or had higher annual turn off rates. The

GM/doe was the most important parameter of goat production in Bali Province. The results of the

pairwise analysis showed that it had strong positive correlations with the number of goats sold,

flock size, the labourer ratio to flock size, number of does owned, size of land cultivated and the

number of bucks owned per household (P<0.01) (Tables 8.4 and 2 in Appendix 1). The GM/doe

that was generated by smallholder goat farmers in all districts had strong positive correlations with

one to four other parameters of goat production (P<0.01) but Pearson correlations ranked the factors

influencing goat production in each districts differently (Tables 8.4 and 2 in Appendix 1).

Table 8.4 Rank in order of importance of pairwise Pearson correlations, between the GM/doe and

other parameters of goat production, in Banjar, Busungbiu, Grogak, Mendoyo and Rendang

Districts, Bali Province. GM/doe per household (IDR million) correlated

with parameters of goat production

Regency Province



No. of goats sold per household 2* 1** 2* 1** 1** 1**

Flock size per household - - 3* - 4** 2**

Labourer ratio to flock size per household - - - - 2** 3**

No. of does owned per household - - 1** - 3** 4**

Size of land cultivated per household (ha) 1* - - - 5**

No. of bucks owned per household - - - - - 6**

No. of household labourers per household a - - - - -

Education level per household - - - - - -

Age of farmers per household (year) - - - - - -

Total 2 1 3 1 4 6




The Tables 8.1 to 8.4 above showed that the welfare and socio-economic activity of Bali

smallholder goat farmers were inextricably linked to the productivity of their goats.


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Table 8.5 SWOT factors considered for improving goat production in Bali Province, Indonesia

Strengths:

The ownership and size of land cultivated were

relatively large.

The number of household labourers was relatively

large for the number of goats cared for, except for

Mendoyo District that just re-started rearing goats

recently.

The number of does owned per household was

proportional to the total number of goats in each

flock.

The availability of feed resources, particularly

leguminous fodder trees or shrubs have been used to

ameliorate feed constraints and to enhance soil

fertility in Bali Province, particularly in conservation

forests as well as natural anti-parasitic properties.

Balinese culture - desires to own and raise livestock.

High kidding and weaning rates and relatively low

kid mortality, particularly in Banjar and Rendang

improved the efficiency of goat production in Bali

Province.

Goats are relatively low cost and easy to care for.

Goats are easy to transport.

High education level of goat farmers, particularly in

Busungbiu District associated with upgrading goats

with Boer and Etawah Grade bucks improved the

bodyweights and milk production of goats.

Smallholder goat farmers associations managed

―One gate marketing system‖ as well as forming a

cooperative that helped the members in finances,

particularly in Rendang District.

The length of goat rearing experience of Bali goat

farmers was more than 10 years.

Weaknesses:

Age profile and sex balance of goat flocks may

not be optimised for maximum production.

Keeping does until their 10th parity in Rendang

District.

Feed supply may not be optimised for

maximum production.

High kid mortality rate was due to predator

risks (wild dogs) in Busungbiu District.

Lack of a ―business approach" to raising goats.

Goats kept for cultural reasons or as a "living

bank".

Price received by farmers may not be based on

quality and weight - but bargaining power of

traders.

Smallholder goat farmers were not sure on how

to predict the age of their goats and they had

never weighed their goats even when they sold

their goats.

Smallholder goat farmers had never recorded

the productive nor reproductive parameters of

their goats and it means farmers have no data on

how well their animals were performing.

Limitation of the availability of family

labourers resulted in a new critical threshold for

farm growth strategies, particularly in Mendoyo

District.

Opportunities:

Huge unmet demand for goat meat and milk - this

demand is predicted to increase.

Roles of goats for Bali smallholder farmers included

their inclusion in social/religious ceremonies,

particularly Eid Qurban and Mecaru ceremonies.

Policy of Indonesian Government for meat self-

sufficiency.

Bali Government encouraged Bali smallholder goat

farmers in improving their goat productivity.

Bali Government assist smallholder farmers to build

networks with the Indonesia Research Institute for

Animal Production to ensure quality breeds, feeds

and rearing goat management systems were used in

Bali Province i.e. having simple goat recording as

well as skills in selecting goats, particularly for high

milk production.

Maximise efficient use of agricultural by products.

To supply organic fertilizer for cropping.

Increase income and nutrition of poor rural families.

Threats:

Exotic diseases such as Foot and Mouth

Disease and endemic diseases such as scabies in

Mendoyo District, and haemonchosis and

scabies in Banjar District.

Loss of feed supply due to encroaching urban

development.

Cultural shift as more rural people move to

urban areas to gain employment in business and

tourist associated trade.

Lack of capital and competition with other

demands for farmer‘s attention (goats are a

sideline enterprise), particularly in Mendoyo

District.

There were no clear goat breed strategies for

development of rearing goats in particular

districts recommended by government.


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8.3 Strategies for improvement of goat production in Bali Province

Of the Balinese smallholder goat farmers studied, 40% had a flock size higher than the average of

12 ± 0.8 goats per household. They generated high positive GM(A-B) and GM/doe when they had

at least 33.3% annual turn off rate. The remaining 60% of Bali goat farmers had flocks smaller than

the average of 12 ± 0.8 goats per household. As long as they had at least 25% does in a flock that

kidded three times in two years, when they had at least 33.3% of annual turn off rate, they also

generated positive GM(A-B) and GM/doe (Tables 11 and 12 in Appendix 1). This result was

supported by Pinos-Rodríguez et al. (2015) who stated that management of goat farming was the

most important aspect for profitability. This means that a small flock with a good management can

be profitable. In contrast, it can be unprofitable with improper management.

However, of the 60% of Bali goat farmers‘ having a low ratio of household labourers to the flock

size, an absence of does or bucks in a flock was a constraint to the improvement of goat production

in Bali Province. For example, about 39% of flocks in Mendoyo District had an average flock size

of 3.8 ± 1.2 goats, and 66% of them had no does in their flocks. Furthermore, 9% of Bali goat

farmers did not own any does and half of them did not own any bucks. They were major constraints

to goat production in Bali Province. All of these parameters generated negative GM(A-B) and

GM/doe (Figure 2 in Appendix 1). To overcome these constraints, the inclusion of does and bucks

in their flocks, particularly in Mendoyo District, would automatically improve the ratio of

household labourers to their flock size. The size of flocks per household influenced the number of

goat sold per-year per household and thus influenced their GM/doe. These were confirmed by the

results of correlations in this study where the correlation of R2 = 0.753 (P<0.01) for flock size and

number of goats sold per household per year, while R2

= 0.731 (P<0.01) for the number of goats

sold per household per year and GM/doe per household per year. Similarly Singh et al. (2011)

reported that large flocks of goats achieved higher profits than small and medium flock sizes.

Strategies for improvement of goat production in Bali Province therefore could be achieved by:

The proportional number of does and bucks in a flock.

The availability of does and bucks in a flock that were well managed for their reproductive

performance could be one of the development strategies that will help in improving their goat

production. This was supported by Peacock (1996) who stated that reproduction dictated the rate of

expansion of the flock, and the numbers of excess stock for sale, and thus milk available for home

consumption and sale. By increasing the number of goats in their flocks and producing milk for

sale could improve the production of goats in Bali Province (Knipscheer et al. 1984; James &

Carles 1996).


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The presence of sufficient does and bucks in larger flocks generated more offspring that was then

available for breeding stock for selection programmes (Peacock 1996; Abebe 2009). Bali farmers

who had larger flock sizes with sufficient does and bucks in their flocks had an opportunity to select

replacement kids from the larger number of kids in their flocks. With increased flock sizes, Bali

farmers will be able to select kids with heavier birth weights, heavier bodyweights at first puberty,

or at first kidding, and does with shorter postpartum intervals, higher fertility, higher annual

reproductive rate and higher milk production. This would also enable smallholder farmers to select

twin born kids to increase the number of kids sold. The twin born kids in this study could be

increased from 37% to 50% or 75% through selection of does for more efficient goat production.

Devendra and Burns (1983) stated, that selection of does, which had multiple births at their first or

first two kiddings was a practical method to increase prolificacy in goat flocks.

The proportion of labourers to flock size

The number of household labourers to the number of goats managed per household that were well

managed for their reproductive performance could be one of the development strategies that will

help in improving their goat production. The inclusion of high costs for labourers in goat farming

in Bali Province showed that this was not beneficial to those farmers who had small flocks as well

as a small labourer to goat ratio when they had less than 33.3% annual turn off rate (Tables 3 and 11

in Appendix 1). Bali smallholder farmers in this study reported that goat rearing was only a sideline

of their farming activities. Goat production was mostly not a profitable activity since most of its

profits only compensated the labourer employed as the biggest costs were feedstuffs and labour

(Nemeth et al. 2004). Nevertheless, the small scale of goat rearing, integrated with crop farms in

Bali Province, was considered as utilization of spare time of farmers after working for their food

crop farming, with goats providing organic fertilizer from their manure. Furthermore, by selling

their goats helped households to overcome financial problems and enabled them to purchase goods

for household consumption. It meant that their income could be increased and thus reduced their

poverty. This condition also gave an advantage to develop the sustainability of livestock farming in

villages. This result was supported by Ayalew et al. (2003) who reported that as a subsistence

animal goats were a low-cost and inflation-proof alternative of saving, their value provided asset

(financing) and security (insurance) benefits at times of difficulty. Encouraging the smallholder

farmers in Bali Province to improve their flock sizes or the labourer to goat ratio and flock sizes

could be one of the development strategies that will help in improving their income by selling more

or heavier goats.


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Education level/knowledge/skill/experience of goats rearing management of smallholder goat

farmers

The present study showed that increasing the litter size of breeding does in Bali Province was a

major factor to increase flock sizes and thus the productivity of their goat production. The larger

number of kids born, the larger possibility for Bali smallholder farmers to sell more (male) goats

thus to make a larger turn off rate and generate higher GM(A-B) and GM/doe.

There were 958 kids born from 657 kiddings of 606 productive females and the ratio between

female and male kids born was 494:464 or 1.1:1. Of the 657 kidding, the number of single born

kids was the largest i.e. 387 or 59%; followed by 243 or 37% of twin born kids and then triplet and

quadruplet kids born were 23 or 3.5% and 4 or 0.5%, respectively. There were 786 does of the total

2,017 goats reared in Bali Province and 77% of does kidded during the first nine months in 2014

(Table 9 in Appendix 1). This study revealed that smallholder farmers in Bali Province applied

good breeding management as well as good goat rearing management as their goats achieved the

bodyweights appropriate for each age of physiological state (Table 7 in Appendix 1).

Selection programmes would enable Bali farmers to cull their does after their 6th

parity when does

were about 7 years of age to achieve maximum litter size and efficient goat production as suggested

by Devendra and Burns (1983), and Peacock (1996) as reproductive performance of does gradually

decreases after their 6th

parity (Peacock 1996). Therefore, Bali goat farmers, particularly in

Rendang District, should no longer keep their does until their 10th

parity. They should replace them

with the younger does. All of these suggestions should lead to increases in production of goats in

Bali Province.

Growth rates for preweaned male kids i.e. 143 ± 4.7 g/d and female kids i.e. 113 ± 4.6 g/d in the

present study, were higher than preweaned male and female Kacang kids reported by Sodiq et al.

(2010). The growth rates in the present study were also higher than average daily gains of Boer, PE

x Kacang, Boer x Kacang, Kacang x Kacang, and PE x PE preweaned kids observed in the RIAP

(Balitnak-Ciawi) (Setiadi et al. 2000; Setiadi et al. 2001; Romjali et al. 2002; Sutama et al. 2003).

This indicated that smallholder farmers in Bali Province had good kid rearing management as

indicated by the high weaning rate of 143% and low mortality of 8.6%. In the present study, the

weaning weights of kids were higher than those reared elsewhere in Indonesia. The average

weaning weights of 19 ± 0.4 kg for females and 22 ± 0.4 kg for males, were higher than 17.1 kg and

16.2 kg respectively for male and female Boerawa weaners reared in Lampung Province (Adhianto

et al. 2013). These results were also higher than 14 ± 2 kg for Etawah weaners (Astuti et al. 2000)


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and 17.7 ± 0.5 kg for Etawah Grade weaners and 21 ± 1.3 kg for Boerawa F1 weaners reared in

Lampung Province (Sulastri 2010). This signified that farmers in Bali Province had also good

weaner management and thus generate high GM(A-B) and GM/doe as indicated by selling more

kids with heavier bodyweights.

The average bodyweights of does and bucks in this study were higher than previous studies. These

were 37 ± 0.2 kg and 41 ± 0.5 kg, respectively, which were higher than 21 ± 6.6 kg and 19 ± 5.3kg

for Marica does and bucks, and 22 ± 5.9 kg and 25 ± 6.1 kg for Kacang does and bucks reared

elsewhere in Indonesia (Batubara et al. 2011). The bodyweights of Balinese adult goats were also

higher than Jawarandu does and bucks i.e. 23 ± 7.9 kg and 16 ± 4.8 kg, Benggala does and bucks

i.e. 25 ± 8.7 kg and 16 ± 3.9 kg, and for Samosir does and bucks i.e. 25 ± 5.4 kg and 22 ± 8.1 kg,

respectively (Batubara et al. 2011). However, the present results were similar to Muara does and

Bali bucks which were slightly lighter than Muara bucks reared in other regencies of Indonesia i.e.

37 ± 11 kg and 49 ± 26.9 kg, respectively (Batubara et al. 2011).

Improving the knowledge, experience and skill of the Bali smallholder goat farmers is critical in

improving the efficiency of rearing goats. One of the ways to achieve those improvements is to

improve their awareness of the particular goat breeds that have adapted well to their environment

i.e. climate, rainfall and the availability of feed. Bali smallholder goat farmers in Busungbiu

upgraded their goats by crossing them with Boer and Etawah bucks, which resulted in extra income

by selling extra milk and milk products. Similarly, the farmers in Grogak District reared small body

type goats with short ears that are well known for their ability to adjust to the humid tropical

environment.

8.4 Suggestions for improvement of goat production in Bali Province

This study had generated new, important and detailed information on goat production by

smallholder farmers in Karangasem, Buleleng and Jembrana Regencies in Bali Province. This

study makes the following observations and recommendations about improving goat production by

smallholder farmers in Bali Province, and elsewhere in Indonesia:

High performance (as indicated by GM/doe) was associated with a higher turn off rate

(underpinned by a higher reproductive rate);

Organic goat rearing management in Rendang District was a model for Bali Province;

The ideal labourer to goat flock size ratio was 20 goats per labourer where at least 25% of the

flock was does, had 75% annual turn off rate and 8 month kidding interval;

Does should only be kept up to their fourth or fifth kidding;


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Farmers need to keep records of their goats;

A ―One gate marketing system‖ should be used to maintain profitable market prices;

Smallholder farmers need assistance in making decisions for setting up better breeding, feeding

and rearing management for efficient goat production; and

Smallholder farmers need assistance to build networks with the Indonesia Research Institute for

Animal Production to ensure quality breeds, feeds and rearing goat management systems are used

in Bali Province.

This information could be used to reduce the constraints to, and improve the opportunities for

improving goat production in these three and the other regencies in Bali in particular, and to

improve goat production elsewhere in Indonesia.

8.5 Concluding remarks

8.5.1 An outcome of this study is a tape measure that has been validated for predicting the

bodyweights of goats in the districts studied.

Type appraisal is important in goat breeding, and data on relationships between body conformation

and goat production of goats reared by smallholder farmers in Bali Province were important to help

them in selection of their goats, hence improving in their productivity. This was confirmed by

Peacock (1996) who reported that applying simple records were necessary for efficient management

and it was an affordable activity applied by smallholder goat farmers in Bali Province since most of

them were literate, although they had the lowest level of education, i.e. Primary School or Grade 1-

6 (Table 1 in Appendix 1) (BPS-Bali 2015). However, smallholder goat farmers in the present

study as well as from the available references reported that Bali smallholder farmers did not record

the productive or reproductive performance of their goats nor did they weigh their goats even when

they sold them.

Some of smallholder goat farmers, particularly those who were members of smallholder goat

farmers association, in the present study, had learnt how to do simple recordings as part of the

conditions for receiving Bali Simantri Programme. However, since they did not fully understand

the importance of using the records, they stopped recording data on their goats. Bali smallholder

farmers stated that recording data on their goats was not easy due to goat rearing being only a

sideline to their farming activities. Furthermore, smallholder farmers required sufficient skills and

time to maintain the simple recording system. The most important issue, however, was that

smallholder goat farmers in Bali Province required an understanding of the importance of recording

data on their goats and as well as they needed to build their confidence in keeping and using their


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records. This result was confirmed by Bayyurt and Yılmaz (2012) who reported that governance

and education were interwoven in shaping smallholder farmers and they required longer time in

learning processes for improving their skills and confidence in management efficiency as they were

typically unskilled and had low education levels.

Although weighing goats regularly is important to improve goat productivity, smallholder farmers

in Bali Province did not weigh their goats due to various reasons that included lack of weighing

scales. The best method of weighing animals without a scale was to use a tape measure. The tape

measure was based on a mathematical model to predict bodyweights in different ages of goats.

Using tape measures for convenient prediction of bodyweight of goats for smallholder goat farmers

in villages could be used for better rearing management as well as to predict goat sale prices for

higher profits (Villaquiran et al. 2005). Using a tape measure is practical, faster, easier, and cheaper

in rural areas where weigh scale are expensive or not available for smallholder farmers.

Of all 4,193 recordings generated from a total of 2,017 goats reared by smallholder farmers in Bali

Province in the present study, there were significant differences (P<0.01) between age and sex of

goat for their bodyweight, chest circumferences, height at withers, rump height and body length in

the same physiological of goats (Tables 6 and 7 in Appendix 1). Average measurements of body

dimensions of goats in the present study were determined as bodyweight 26.4 ± 0.2 kg, chest

circumference 67.4 ± 0.1 cm, height at withers 63.3 ± 0.1 cm, rump height 65.6 ± 0.1 cm and body

length 73.6 ± 0.3 cm (Tables 6 and 7 in Appendix 1). There were positive and significant (P<0.01)

correlations between bodyweight and body dimensions of goats reared in Bali Province. The

highest correlations were between bodyweight and chest circumference (R2=0.9077) followed by

height at withers (R2=0.8705), rump height (R

2=0.8611) and body length (R

2=0.8532). Two

hundred tape measures for predicting the bodyweights of goats reared in Bali Province were created

based on the equation where bodyweight = 23.527*CC0.3275

, R² = 0.9077. This was based on the

chest circumference of the 2,017 goats measured during the data collection in 2014 (Plate 8.1).


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Plate 8.1 Two hundred tape measures were produced for predicting bodyweights of goats reared in

Bali Province, based on the 2,017 goats measured during the data collection in 2014.

Estimation of the bodyweight of goats reared in Bali Province was more accurate when prediction

was based on chest circumference and this was confirmed by Olatunji-Akioye and Adeyemo

(2009), Natsir et al. (2010), Chitra et al. (2012) and McGregor (2017). Encouraging smallholder

farmers in Bali Province to use the tape measures could be one of the development strategies that

will help in improving goat production, for example, by allowing farmers to determine the growth

rate of their goats thus improving their income by selling heavier goats.

8.5.2 Strengths and limitations of this study

This study summarised important data about the goats reared by smallholder farmers in Banjar,

Busungbiu, Grogak, Mendoyo and Rendang Districts, Bali Province. Data of the 2,017 goats that

were recorded one to four times during the data collection generated important information on the

goats and their profiles, households and their profiles, the impacts of different rearing management

i.e. housing system, feeding and breeding systems as well as their socio-economics. This database

is the first and includes the bodyweights and body dimensions of all physiological states of goats in

those districts. This created the opportunities to supply the measuring tapes that have been

distributed to all smallholder goat farmers involved in this study.

This study, however, has limitations. The data on smallholder goat farmers only originated from

five districts. Therefore, not all information and recommendations from this study is applicable to

other goat farmers and locations, particularly to those that have different characteristic from the five

districts studied.

8.5.3 Recommendations for future research

In future researchers need to conduct more research on the socio-economics, particularly on the

labourer to goat ratio in relation to flock sizes, and the composition of goats in a flock that would

generate optimal GM/doe per household.

Research on the returns i.e. GM(A-B) and GM/doe per household gained by farmers, roles and the

strengths of goat farmers‘ associations and cooperatives in dictating selling goat prices, the power

of bargaining by traders, and the niche market for religious festivals, also need to be conducted.

This would provide clear information on when and how many goats should be sold per household

annually to achieve the optimal profits but at the same time maintaining the ideal number of

breeding goats in Bali Province.


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Research on breeding, particularly the introduction of Saanen goats to Bali Province, also needs to

be conducted. The productive and reproductive performance of Saanen goats, particularly for their

milk production could be compared between the mixture of Boer and Etawah breeds and their

offspring. This would provide clear information on the GM(A-B) and GM/doe gained by goat

farmers when they rear Saanen, Boer, Etawah goats and their crossbreds or their backcrosses.

Selection of heavier and larger body dimensions of goats as well as modified feeding management

or utilization of agriculture industry by-products as feed, could improve the bodyweight of goats for

optimum selling prices. This would provide clear information on utilization of agriculture industry

by-products for optimum growth rate of goats.

Research with these focuses will provide further improvement of goat production in Bali Province.

All this will lead to strategies to help to ameliorate poverty, provide goat meat, milk and their

products and thus increase smallholder goat famers‘ income in Bali Province.

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Appendix 1

200


Appendix 1

Analysis data from 175 smallholder goat farmers in Banjar, Busungbiu, Grogak, Mendoyo and

Rendang Districts, Bali Province, Indonesia who reared 2,017 goats that was recorded once to four

times during data collection in 2014 is presented in Figures 1 and 2 as well as in Tables 1 to 14.

The 2,017 goats that were a mixture of Gembrong, Benggala, Kacang, Etawah Grade, PE, Boer,

Boerawa and their crossbreds or backcrosses reared in battery or and colony housing systems. This

data is used for assessing the current goat rearing towards improving productivity in Bali Province,

Indonesia through a hybrid method of SWOT and AHP analyses in Chapter 8.

Figures 1

Figure 1 The average number of goats, of different physiological states, owned per household in

Banjar, Busungbiu, Grogak Mendoyo and Rendang Districts in Bali Province.

Appendix 1

201


Figures 2

Figure 2 Flock sizes and total number of goats of different physiological states, owned per

household in Bali Province.

Table 1

Table 1 Information about the household labourers in Banjar, Busungbiu, Grogak, Mendoyo and

Rendang Districts, Bali Province.

Description

Regency Province



Mean ± SEM Mean ± SEM Mean ± SEM Mean ± SEM Mean ± SEM Mean ± SEM

n=7 n=25 n=12 n=68 n=63 n=175

No. of household labourers per

household

2 ± 0.2a 2 ± 0.1a 2.2 ± 0.2a 2 ± 0.1a 2.7 ± 0.1b 2.3 ± 0.0

Equivalent working hours

(hours/no. of household

labourers/year)

365 ± 44.2a 365 ± 23.4a 395.4 ± 33.8a 362.3 ± 14.2a 492.5 ± 14.7b

412 ± 9.9

No. of children per household 2 ± 0.3a 1.6 ± 0.1ae 1.2 ± 0.2bef 0.2 ± 0.1c 1.2 ± 0.1df 1.2 ± 0.1

Age of farmer (years) 38.6 ± 4.5ac 39.5 ± 2.4a 42.2 ± 3.4ad 47.3 ± 1.4bcd 40.5 ± 1.5a 41.6 ± 1.3

Homemaker‘s education level * 1.6 ± 0.2af 1.7 ± 0.1a 1.1 ± 0.1be 1.5 ± 0.1df 1.0 ± 0.1ce 1.4 ± 0.0

Husband‘s education level * 1.6 ± 0.3ad 1.9 ± 0.1a 1.5 ± 0.2ac 1.6 ± 0.1a 1.3 ± 0.1bcd 1.6 ± 0.1

Flock size (goats) 15 ± 4ad 14 ± 2ae 11 ± 3a 4 ± 1b 19 ± 1cde 12 ± 1

Ratio of labourers to the

number of goats managed

7.4 ± 1.7a 7.7 ± 0.9a 5.6 ± 1.3a 1.9 ± 0.6b 7.5 ± 0.6a 6.0 ± 0.5

Housing (battery or colony)

systems used**

1 ± 0.1a 1 ± 0.1a 2 ± 0.1b 1 ± 0.0a 1.5 ± 0.0c 1.3 ± 0.0

Farming period (years) 12.4 ± 3.4aeh 16.4 ± 1.8a 5.2 ± 2.6befg 9.2 ± 1.1cfhi 10.8 ± 1.1dgi 10.8 ± 1

Size of land cultivated (ha) 0.9 ± 0.2ae 1.7 ± 0.1b 0.6 ± 0.1a 0.9 ± 0.1de 2 ± 0.1c 1.2 ± 0.0 *1=Primary School (Grade 1 to 6); 2=Secondary School (Grade 7 to 9); 3=High School (Grade 10 to12); 4=University **1=Battery housing system; 2=Colony housing system

Means in a row with different superscripts differed significantly at the .05 level.

Appendix 1

202


Table 2

Table 2 Production parameters of 2,017 goats reared by 175 households in Banjar, Busungbiu,

Grogak, Mendoyo and Rendang Districts, Bali Province.

Description

Regency Province




n=7 n=25 n=12 n=68 n=63 n=175

Turn off rate (%) 26 ± 11ad 51 ± 6bc 11 ± 9a 6 ± 4a 44 ± 4cd 28 ± 3

No. of goats sold/year 5.1 ± 2.6aef 6.7 ± 1.4ag 2.3 ± 2.0ac 0.2 ± 0.9bce 9.3 ± 0.9dfg 4.8 ± 0.8

Prices of goats sold 8.571 ± 4.238aef 11.14 ± 2.242ag 3.958 ± 3.237ac 0.4 ± 1.512bce 15.06 ± 1.413dfg 7.827 ± 1.229

Prices of manure sold 1.343 ± 0.365ae 1.307 ± 0.193af 0.981 ± 0.279ac 0.398 ± 0.130bc 1.693 ± 0.122def 1.144 ± 0.106

Prices of milk sold 2.126 ± 0.592ae 2.554 ± 0.313a 1.360 ± 0.452de 0 ± 0.190bf 0 ± 0.197cf 1.208 ± 0.171

Total income 12.04 ± 4.717adf 15.96 ± 2.496ag 6.299 ± 3.602cde 0.798 ± 1.683be 16.76 ± 1.572afg 10.37 ± 1.368

Drenching cost 0.044 ± 0.012ae 0.043 ± 0.006af 0.032 ± 0.009ac 0.013 ± 0.004bc 0.056 ± 0.004def 0.038 ± 0.003

Feed cost 11.26 ± 2.106ae 10.97 ± 1.114a 8.368 ± 1.609ad 3.185 ± 0.751b 7.293 ± 0.702cde 8.216 ± 0.611

Labour cost 2.281 ± 0.288a 2.281 ± 0.152a 2.471 ± 0.220a 2.261 ± 0.103a 3.078 ± 0.096b 2.474 ± 0.083

Total variable costs 13.59 ± 2.156ae 13.30 ± 1.141a 10.87 ± 1.647ad 5.459 ± 0.769b 10.43 ± 0.719cde 10.73 ± 0.625

Gross Margin (A-B) (1.547 ± 3.678)afh 2.662 ± 1.946ae (4.572 ± 2.809)cfg (4.661 ± 1.312)dgh 6.330 ± 1.226be (0.357 ± 1.067)

Gross Margin/doe (0.5 ± 0.684)ad 0.079 ± 0.362a (2.158 ± 0.522)cde (2.518 ± 0.244)be 0.350 ± 0.228a (0.949 ± 0.198)

All prices and cost and GM(A-B) and GM/doe were in IDR million. Labourers were paid IDR 6,250 per hour.

Means in a row with different superscripts differed significantly at the .05 level. Figures in brackets mean their values were negative

Appendix 1

203


Table 3

Table 3 Effects of annual equivalent working hours on annual turn off rate (%), GM(A-B) (IDR

million) and GM/doe (IDR million) in Banjar, Busungbiu, Grogak, Mendoyo and Rendang

Districts, Bali Province. Annual equivalent

working hours

(hours/no. of

household

labourers/year)

Turn off rate (%)

Buleleng Jembrana Karangasem Province



n=7 n=25 n=12 n=68 n=63 n=175

182.5 * 26 ± 17 0 ± 21 43 ± 13

* 23 ± 10

365 26 ± 11 55 ± 67 10 ± 12 3 ± 4 45 ± 5 28 ± 4

547.5 * 54 ± 17 19 ± 15 0 ± 15 41 ± 6 29 ± 7

730 *

*

*

* 56 ± 17 56 ± 17

912.5 *

*

*

* 61 ± 17 61 ± 17

1095 *

*

*

* 18 ± 29 18 ± 29

182.5 - 1095 26 ± 11afh

45 ± 8be

10 ± 9cfg

15 ± 7dgh

44 ± 8ae

30 ± 4

Annual equivalent

working hours

(hours/no. of

household

labourers/year)

GM(A-B) (IDR million)




n=7 n=25 n=12 n=68 n=63 n=175

182.5 * (1.635 ± 5.635) (6.878 ± 6.902) (1.521 ± 4.365)

* (3.345 ± 3.307)

365 (1.547 ± 3.689) 2.918 ± 2.239 (5.027 ± 3.985) (4.105 ± 1.439) 7.528 ± 1.753 (0.047 ± 1.259)

547.5 * 5.340 ± 5.635 (2.735 ± 4.880) (14.97 ± 4.880) 5.422 ± 1.952 (1.737 ± 2.280)

730 *

*

*

* 8.972 ± 5.635 8.972 ± 5.635

912.5 *

*

*

* 3.055 ± 5.635 3.055 ± 5.635

1095 *

*

*

* (6.182 ± 9.760) (6.182 ± 9.760)

182.5 - 1095 (1.547 ± 3.689)afh

2.208 ± 2.759ae

(4.880 ± 3.115)cfg

(6.867 ± 2.235)dgh

3.759 ± 2.574be

(0.758 ± 1.300)

Annual equivalent

working hours

(hours/no. of

household

labourers/year)

GM/doe (IDR million)




n=7 n=25 n=12 n=68 n=63 n=175

182.5 * (0.464 ± 1.019) (1.545 ± 1.248) (1.620 ± 0.79)

* (1.210 ± 0.598)

a

365 (0.5 ± 0.667) 0.057 ± 0.405 (1.920 ± 0.721) (2.652 ± 0.260) 0.590 ± 0.317 (0.885 ± 0.228)a

547.5 * 0.756 ± 1.019 (2.822 ± 0.883) (2.103 ± 0.883) 0.319 ± 0.353 (0.962 ± 0.412)

a

730 *

*

*

* (0.087 ± 1.019) (0.087 ± 1.019)

a

912.5 *

*

*

* 0.745 ± 1.019 0.745 ± 1.019

a

1095 *

*

*

* (6.182 ± 1.766) (6.182 ± 1.766)

b

182.5 - 1095 (0.5 ± 0.667)a 0.117 ± 0.499

a (2.096 ± 0.563)

bd (2.125 ± 0.404)

cd (0.923 ± 0.466)

a (1.162 ± 0.235)

Annual equivalent

working hours

(hours/no. of

household

labourers/year)

Number of goats sold per household (goats)




n=7 n=25 n=12 n=68 n=63 n=175

182.5 * 5 ± 4 0 2 ± 3 * 2

± 2

365 5 ± 3 7 ± 2 2 ± 3 0

± 1 9

± 1 5

± 1

547.5 * 5 ± 4 4 ± 3 0 9

± 1 5

± 2

730 * * * * 11 ± 4 11

± 4

912.5 * * * * 10 ± 4 10

± 4

1095 * * * * 3 ± 7 3

± 7

182.5 - 1095 5 ± 3

adf 6

± 2

ag 2

± 2

ae 1

± 1

bde 8

± 2

cfg 5

a ± 1

Annual equivalent

working hours

(hours/no. of

household

labourers/year

Prices of milk sold per household (IDR million)




n=7 n=25 n=12 n=68 n=63 n=175

182.5 a 2.080 ± 1.920 1.200 ± 2.352 * * 1.640 ± 1.518

365 2.126 ± 1.257 2.400 ± 0.763 1.440 ± 1.358 * * 1.989 ± 0.667

547.5 a 4.000 ± 1.920 1.320 ± 1.663 * * 2.660 ± 1.270

730 * * * * * *

912.5 * * * * * *

1095 * * * * * *

182.5 - 1095 2.126 ± 1.257 2.827 ± 0.940 1.320 ± 1.061 * * 2.081 ± 0.634

Means in a row with different superscripts differed significantly at the .05 level. Figures in brackets mean their values were negative. *This level combination of factors was not observed, thus the corresponding population marginal mean was not estimable.

Appendix 1

204


Table 4

Table 4 Effects of education level of household labourers on annual turn off rate (%), GM(A-B)

(IDR million) and GM/doe (IDR million) in Banjar, Busungbiu, Grogak, Mendoyo and Rendang

Districts, Bali Province.

Level of

education

Turn off rate (%)




n=7 n=25 n=12 n=68 n=63 n=175

1 11 ± 17 55 ± 9 0 ± 10 11 ± 5 44 ± 4 24 ± 4

2 37 ± 14 67 ± 10 38 ± 20 0 ± 8 35 ± 11 35 ± 6

3 * 33 ± 12 30 ± 20 0 ± 9 65 ± 13 32 ± 7

4 * 0 ± 29 * * * 0 ± 29

1 - 4 24 ± 11ad 39 ± 8be 23 ± 10a 4 ± 4a 48 ± 6cde 28 ± 4

Level of

education





1 (5.935 ± 5.637) 2.662 ± 3.087 (7.981 ± 3.452) (4.194 ± 1.726) 5.550 ± 1.367 (1.981 ± 1.525)a

2 1.744 ± 4.881 1.877 ± 3.452 3.297 ± 6.903 (6.375 ± 2.818) 5.747 ± 3.690 1.259 ± 2.05ac

3 * 3.408 ± 3.986 1.195 ± 6.903 (4.148 ± 2.944) 15.11 ± 4.366 3.891 ± 2.389bcd

4 * 4.479 ± 9.763 * * * 4.48 ± 9.764ad

1 - 4 (2.096 ± 3.728)aeg 3.106 ± 2.879ah (1.163 ± 3.452)cef (4.906 ± 1.475)dfg 8.801 ± 1.959bh 1.095 ± 1.247

Level of

education





1 (1.311 ± 1.037) 0.293 ± 0.568 (2.981 ± 0.635) (2.550 ± 0.318) 0.399 ± 0.252 (1.231 ± 0.280)

2 0.108 ± 0.898 0.436 ± 0.635 (0.345 ± 1.271) (2.523 ± 0.519) (0.891 ± 0.679) (0.722 ± 0.377)

3 * (0.276 ± 0.734) (0.678 ± 1.271) (2.419 ± 0.542) 1.584 ± 0.804 (0.447 ± 0.440)

4 * 0.344 ± 1.797 * * * 0.344 ± 1.797

1 - 4 (0.601 ± 0.686)ad 0.101 ± 0.530a (1.335 ± 0.635)cde (2.497 ± 0.271)be 0.364 ± 0.361a (0.747 ± 0.229)

Means in a row with different superscripts differed significantly at the .05 level. Figures in brackets mean their values were negative.

*This level combination of factors was not observed, thus the corresponding population marginal mean was not estimable.

Appendix 1

205


Table 5

Table 5 Effects of education level of household labourers on labourer ratio, number of does owned

per household (does), and number of goat sold per household (goats) in Banjar, Busungbiu, Grogak

Mendoyo and Rendang Districts, Bali Province.

Level of

education

Labourer to goat ratio




n=7 n=25 n=12 n=68 n=63 n=175

1 4 ± 2.5 7.3 ± 1.4 5.6 ± 1.6 2.0 ± 0.7 7.1 ± 0.6 5.2 ± 0.7a

2 9.9 ± 2.2 3.5 ± 1.6 4.5 ± 3.1 2.0 ± 1.1 7.7 ± 1.7 5.5 ± 0.9ac

3 * 13.5 ± 1.8 6.7 ± 3.1 1.4 ± 1.2 10.7 ± 2 8.1 ± 1.1bcd

4 * 11.3 ± 4.4 * * * 11.3 ± 4.4ad

1 - 4 6.9 ± 1.7a 8.9 ± 1.3a 5.6 ± 1.6a 1.8 ± 0.6b 8.5 ± 0.9a 6.5 ± 0.6

Level of

education

Number of does owned per household (does)




1 2 ± 3 4 ± 2 4 ± 2 2 ± 1 6 ± 1 4 ± 1a

2 8 ± 2 3 ± 2 4 ± 3 4 ± 1 6 ± 2 5 ± 1ac

3 * 13 ± 2 6 ± 3 2 ± 1 8 ± 2 7 ± 1bcd

4 * 13 ± 5 * * * 13 ± 5ad

1 - 4 5 ± 2ad 8 ± 1a 5 ± 2ac 2 ± 1bcd 7 ± 1a 6 ± 1

Level of

education





1 1 ± 4 7 ± 2 0 ± 2 0 ± 1 9 ± 1 3 ± 1a

2 8 ± 3 5 ± 2 8 ± 5 0 ± 2 9 ± 2 6 ± 1acd

3 * 9 ± 3 6 ± 5 0 ± 2 16 ± 3 8 ± 2bce

4 * 0 ± 7 * * * 0 ± 7ade

1 - 4 5 ± 2adf 5 ± 2ag 5 ± 2ae 0 ± 1bde 11 ± 1cfg 5 ± 1


Appendix 1

206


Table 6

Table 6 Average body dimensions of different physiological state from 4,193 recordings from a

total of 2,017 goats reared in Banjar, Busungbiu, Grogak Mendoyo and Rendang Districts Bali Class of goat Chest circumference (cm), Mean ± SEM


No. of

goat

3 Districts No. of

goat

Mendoyo No. of

goat

Rendang No. of

goat

Bali

F preweaned 93 50.3 ± 1a 13 48.9 ± 2.0a 447 47.8 ± 0.3a 553 48.3 ± 0.3a

F weaner 29 64.5 ± 1.8bjk 18 61.1 ± 1.7b 245 60.5 ± 0.5b 292 60.9 ± 0.4b

F yearling 57 65.8 ± 1.2cjl 22 66.1 ± 1.5cjk 369 69.0 ± 0.4cj 448 68.5 ± 0.4cj

F pregnant 130 80.2 ± 0.8dm 75 75.3 ± 0.8dlmn 263 79.3 ± 0.4dk 464 78.9 ± 0.4d

F lactating 68 78.5 ± 1.2emn 16 78.2 ± 1.8elop 473 76.6 ± 0.3e 556 76.9 ± 0.3ek

F dry 53 76.3 ± 1.3fn 48 74.4 ± 1.0fmoq 567 77.9 ± 0.3f 665 77.5 ± 0.3fk

M preweaned 66 51.2 ± 1.2a 18 48.3 ± 1.7a 411 48.6 ± 0.4a 491 48.9 ± 0.3a

M weaner 32 64.7 ± 1.7gkl 13 68.9 ± 2.0gjr 188 62.6 ± 0.5g 233 63.2 ± 0.5g

M yearling 28 71.4 ± 1.9h 11 69.8 ± 2.1hkqr 206 69.2 ± 0.5hj 242 69.5 ± 0.5hj

M buck 34 86.8 ± 1.7i 24 78.1 ± 1.5inp 196 80.4 ± 0.5ik 249 81.0 ± 0.5ii

All goats 590 69.0 ± 0.4 258 66.9 ± 0.5 3126 67.2 ± 0.1 4,193 67.4 ± 0.1

Class of goat Chest circumference (cm), Mean ± SEM


No. of

goat

3 Districts No. of

goat

Mendoyo No. of

goat

Rendang No. of

goat

Bali

All females 430 69.9 ± 0.7a 192 71.1 ± 0.8a 2,364 68.9 ± 0.3a 2,978 69.2 ± 0.3a

All males 160 64.7 ± 1.3b 66 66.6 ± 1.4b 1,001 61.7 ± 0.4b 1,215 62.3 ± 0.4b

All goats 590 67.3 ± 0.7 258 68.8 ± 0.8 3,365 65.3 ± 0.3 4,193 65.8 ± 0.2

Class of goat Body length (cm), Mean ± SEM


No. of

goat

3 Districts No. of

goat

Mendoyo No. of

goat

Rendang No. of

goat

Bali

F preweaned 93 62.4 ± 1.2a 13 59.0 ± 2.8a 447 56.5 ± 1a 553 57.6 ± 0.9a

F weaner 29 75.7 ± 2.2bjk 18 72.6 ± 2.3b 245 69.9 ± 1.4bj 292 70.6 ± 1.2bjk

F yearling 57 80.3 ± 1.6cjl 22 80.4 ± 2.1cjk 369 79.7 ± 1.1cklmn 448 79.8 ± 1.0clmn

F pregnant 130 96.7 ± 1dmn 75 91.5 ± 1.2dlmnov 263 77.7 ± 1.3dkopq 464 85.1 ± 1.0d

F lactating 68 97.6 ± 1.4emo 16 94.3 ± 2.5elqr 473 77.4 ± 1elors 556 80.3 ± 0.9elop

F dry 53 95.9 ± 1.6fno 48 91.6 ± 1.5fmqst 567 79.5 ± 0.9fmprt 665 81.6 ± 0.8fmoq

M preweaned 66 61.4 ± 1.5a 18 58.7 ± 2.3a 411 57.0 ± 1a 491 57.6 ± 0.9a

M weaner 32 76.0 ± 2.1gkl 13 80.4 ± 2.8gju 188 72.0 ± 1.5gj 233 73.0 ± 1.3gjr

M yearling 28 86.3 ± 2.3h 11 85.4 ± 3.0hknsu 206 78.3 ± 1.5hnqst 242 79.5 ± 1.3hnpq

M buck 34 105.6 ± 2.1i 24 93.7 ± 2.1iprtv 196 63.0 ± 1.5i 249 71.0 ± 1.3ikr

All goats 590 83.8 ± 0.6 258 80.8 ± 0.7 3126 71.1 ± 0.4 4,193 73.6 ± 0.3

Class of goat Body length (cm), Mean ± SEM


No. of

goat

3 Districts No. of

goat

Mendoyo No. of

goat

Rendang No. of

goat

Bali

All females 430 85.6 ± 0.9a 192 86.4 ± 1.1a 2,364 73.6 ± 0.5a 2,978 76.1 ± 0.4a

All males 160 77.6 ± 1.5b 66 79.9 ± 1.8b 1,001 65.4 ± 0.7b 1,215 67.7 ± 0.6b

All goats 590 81.6 ± 0.9 258 83.2 ± 1.1 3,365 69.5 ± 0.4 4,193 71.9 ± 0.4

Class of goat Height at withers(cm), Mean ± SEM


No. of

goat

3 Districts No. of

goat

Mendoyo No. of

goat

Rendang No. of

goat

Bali

F preweaned 93 49.5 ± 0.8a 13 49.1 ± 1.7a 447 47.5 ± 0.3a 553 47.9 ± 0.2a

F weaner 29 60.1 ± 1.4bjk 18 59.0 ± 1.4b 245 58.0 ± 0.3b 292 58.3 ± 0.3b

F yearling 57 61.3 ± 1cjk 22 64.8 ± 1.3cjk 369 65.2 ± 0.3ck 448 64.7 ± 0.3cj

F pregnant 130 71.1 ± 0.6dmno 75 69.3 ± 0.7dlmn 263 70.3 ± 0.3dlmn 464 70.3 ± 0.3dkl

F lactating 68 72 ± 0.9emop 16 72.9 ± 1.5eo 473 70.3 ± 0.2elmo 556 70.6 ± 0.2ekm

F dry 53 70.6 ± 1fnp 48 68.8 ± 0.9flpq 567 70.8 ± 0.2fno 665 70.7 ± 0.2flm

M preweaned 66 48.3 ± 0.9a 18 49.3 ± 1.4a 411 48.6 ± 0.3g 491 48.6 ± 0.3a

M weaner 32 60.9 ± 1.3gkl 13 65.8 ± 1.7gjmpr 188 59.6 ± 0.4h 233 60.1 ± 0.4g

M yearling 28 66.9 ± 1.5h 11 64.4 ± 1.8hknqr 206 64.8 ± 0.4ik 242 65.0 ± 0.4hj

M buck 34 78.9 ± 1.3i 24 75.1 ± 1.3io 196 76.8 ± 0.4j 249 76.9 ± 0.4i

All goats 590 64 ± 0.3 258 64.0 ± 0.4 3126 63.2 ± 0.1 4,193 63.3 ± 0.1

Appendix 1

207

Class of goat Height at withers(cm), Mean ± SEM


No. of

goat

3 Districts No. of

goat

Mendoyo No. of

goat

Rendang No. of

goat

Bali

All females 430 64.4 ± 0.6a 192 66.6 ± 0.7a 2,364 64.1 ± 0.2a 2,978 64.3 ± 0.2a

All males 160 60.3 ± 1b 66 64.5 ± 1.2a 1,001 59.5 ± 0.3b 1,215 59.9 ± 0.3b

All goats 590 62.3 ± 0.6 258 65.5 ± 0.7 3,365 61.8 ± 0.2 4,193 62.1 ± 0.2

Class of goat Rump height(cm), Mean ± SEM


No. of

goat

3 Districts No. of

goat

Mendoyo No. of

goat

Rendang No. of

goat

Bali

F preweaned 93 52.6 ± 0.8a 13 51.5 ± 1.7a 447 49.8 ± 0.3a 553 50.3 ± 0.2a

F weaner 29 63.4 ± 1.4bjk 18 61.3 ± 1.5b 245 60.2 ± 0.3b 292 60.6 ± 0.3b

F yearling 57 65.1 ± 1.0cjl 22 68.1 ± 1.3cjk 369 67.3 ± 0.3ck 448 67.1 ± 0.3cj

F pregnant 130 75.2 ± 0.7dmn 75 73.4 ± 0.7dlm 263 71.9 ± 0.3dlm 464 73.0 ± 0.3dkl

F lactating 68 75.8 ± 0.9emo 16 75.6 ± 1.6eln 473 72.1 ± 0.2eln 556 72.7 ± 0.2ekm

F dry 53 74.2 ± 1fnop 48 71.9 ± 0.9fmop 567 72.7 ± 0.2fmn 665 72.8 ± 0.2flm

M preweaned 66 51.7 ± 0.9a 18 51.8 ± 1.5a 411 50.7 ± 0.3g 491 50.9 ± 0.3a

M weaner 32 63.6 ± 1.3gkl 13 68.1 ± 1.7gjoq 188 61.6 ± 0.4h 233 62.2 ± 0.4g

M yearling 28 71 ± 1.5hp 11 69.2 ± 1.9hkpq 206 66.9 ± 0.4ik 242 67.4 ± 0.4hj

M buck 34 81.6 ± 1.4i 24 77.2 ± 1.3in 196 78.8 ± 0.4j 249 79.0 ± 0.4i

All goats 590 67.4 ± 0.3 258 66.8 ± 0.5 3126 65.2 ± 0.1 4,193 65.6 ± 0.1

Class of goat Rump height(cm), Mean ± SEM


No. of

goat

3 Districts No. of

goat

Mendoyo No. of

goat

Rendang No. of

goat

Bali

All females 430 68.0 ± 0.6a 192 69.9 ± 0.7a 2,364 66.0 ± 0.2a 2,978 66.6 ± 0.2a

All males 160 63.5 ± 1b 66 67.0 ± 1.2b 1,001 61.6 ± 0.3b 1,215 62.1 ± 0.3b

All goats 590 65.8 ± 0.6 258 68.5 ± 0.7 3,365 63.8 ± 0.2 4,193 64.3 ± 0.2

F=Female, M=Male. All preweaned=aged 0 – 4.5 months; All weaner=4.5 month – I0; All yearling=I1; F pregnant, F lactating, F

dry, and buck had I1 – toothless.


Appendix 1

208


Table 7

Table 7 Average bodyweights of different classes of goats reared in Banjar, Busungbiu, Grogak, Mendoyo and Rendang Districts, Bali Province. Class of goat Bodyweight of goats (kg), Mean ± SEM


No. of goat Banjar No. of goat Busungbiu No. of goat Grogak No. of goat Mendoyo No. of goat Rendang No. of goat Bali

F preweaned 22 10.2 ± 1.4 56 11.9 ± 1 15 6.4 ± 1.7 13 10.5 ± 1.9 446 10.1 ± 0.3 552 9.8 ± 0.6a

F weaner 7 18.4 ± 2.5 15 21.1 ± 1.7 7 16.6 ± 2.5 18 22.9 ± 1.6 245 18.9 ± 0.4 292 19.6 ± 0.9b

F yearling 8 26.5 ± 2.4 25 27.9 ± 1.3 24 19.9 ± 1.4 22 26.2 ± 1.4 343 27.0 ± 0.4 422 25.5 ± 0.7c

F pregnant 23 43.6 ± 1.4 80 37.3 ± 0.7 27 34.3 ± 1.3 75 35.6 ± 0.8 211 41.5 ± 0.5 416 38.5 ± 0.4d

F lactating 8 43.1 ± 2.4 48 32.9 ± 1 12 34.3 ± 1.9 16 38.0 ± 1.7 460 36.8 ± 0.3 544 37.0 ± 0.7ej

F dry 6 33.8 ± 2.7 35 35.9 ± 1.1 12 29.2 ± 1.9 48 33.4 ± 1 454 37.3 ± 0.3 555 33.9 ± 0.7fj

M preweaned 13 10.5 ± 1.9 42 11.8 ± 1.0 11 7.3 ± 2.0 18 13.6 ± 1.6 411 10.8 ± 0.3 495 10.8 ± 0.7a

M weaner 5 20.6 ± 3.0 19 23.0 ± 1.5 8 15.4 ± 2.4 13 29.8 ± 1.9 187 21.4 ± 0.5 232 22.0 ± 0.9g

M yearling 6 28.8 ± 2.7 14 29.8 ± 1.8 8 23.1 ± 2.4 11 28.7 ± 2.0 204 28.1 ± 0.5 243 27.7 ± 0.9h

M buck 5 33.2 ± 3.0 24 48.8 ± 1.4 5 34.0 ± 3.0 24 36.2 ± 1.4 165 41.3 ± 0.5 223 38.7 ± 0.9i

All goats 103 26.9 ± 0.8a 358 28.0 ± 0.4b 129 22.0 ± 0.7c 258 27.5 ± 0.5d 3126 27.3 ± 0.1a 3974 26.4 ± 0.2

Class of goat Bodyweight of goats (kg), Mean ± SEM



All females 74 28.6 ± 1.5 259 29 ± 0.8 97 24.5 ± 1.3 192 31.3 ± 0.9 2159 28.3 ± 0.3 2781 28.3 ± 0.5a

All males 29 19.9 ± 2.4 99 25.5 ± 1.3 32 17.4 ± 2.3 66 27.5 ± 1.6 967 21.7 ± 0.4 1193 22.4 ± 0.8b

All goats 103 24.3 ± 1.4ae 358 27.2 ± 0.8a 129 21 ± 1.3b 258 29.4 ± 0.9c 3126 25 ± 0.2de 3974 25.4 ± 0.5

F=Female, M=Male. All preweaned=aged 0 – 4.5 months; All weaner=4.5 month – I0; All yearling=I1; F pregnant, F lactating, F dry, and buck had I1 – toothless.


Appendix 1

209


Table 8

Table 8 Average FAMACHA©

scores of different classes of goats reared in Banjar, Busungbiu, Grogak, Mendoyo and Rendang Districts, Bali

Province. Class of goat FAMACHA© scores, Mean ± SEM



F preweaned 22 2.4 ± 0.2 56 1.8 ± 0.1 15 2.1 ± 0.2 13 1.2 ± 0.2 446 1.8 ± 0.0 552 1.9 ± 0.1a

F weaner 7 2.3 ± 0.3 15 1.9 ± 0.2 7 2.0 ± 0.3 18 1.5 ± 0.2 245 1.6 ± 0.0 292 1.9 ± 0.1bijkl

F yearling 8 2.2 ± 0.3 25 1.7 ± 0.1 24 2.6 ± 0.1 22 1.3 ± 0.2 343 1.7 ± 0.0 422 1.9 ± 0.1aimn

F pregnant 23 2.7 ± 0.1 80 1.9 ± 0.1 27 2.9 ± 0.1 75 1.3 ± 0.1 211 2.1 ± 0.0 416 2.2 ± 0.0cop

F lactating 8 2.6 ± 0.3 48 2.2 ± 0.1 12 2.8 ± 0.2 16 1.9 ± 0.2 460 2.0 ± 0.0 544 2.3 ± 0.1do

F dry 6 2.7 ± 0.3 35 2.1 ± 0.1 12 2.4 ± 0.2 48 1.6 ± 0.1 454 2.0 ± 0.0 555 2.1 ± 0.1ep

M preweaned 13 2.2 ± 0.2 42 1.8 ± 0.1 11 2.5 ± 0.2 18 1.7 ± 0.2 411 1.8 ± 0.0 495 2.0 ± 0.1a

M weaner 5 2.6 ± 0.3 19 1.7 ± 0.2 8 2.4 ± 0.3 13 1.1 ± 0.2 187 1.6 ± 0.0 232 1.9 ± 0.1fjm

M yearling 6 2.3 ± 0.3 14 1.8 ± 0.2 8 2.4 ± 0.3 11 1.3 ± 0.2 204 1.6 ± 0.0 243 1.9 ± 0.1gk

M buck 5 2.4 ± 0.3 24 2.0 ± 0.1 5 2.6 ± 0.3 24 1.7 ± 0.1 165 1.5 ± 0.1 223 2.1 ± 0.1hln

All goats 103 2.4 ± 0.1a 358 1.9 ± 0.0b 129 2.5 ± 0.1a 258 1.5 ± 0.0c 3126 1.8 ± 0.0d 3974 2.0 ± 0.0

Class of goat FAMACHA© scores, Mean ± SEM



All females 74 2.5 ± 0.1 259 1.9 ± 0.0 97 2.6 ± 0.1 192 1.4 ± 0.0 2159 1.9 ± 0.0 2781 2.1 ± 0.0

All males 29 2.3 ± 0.1 99 1.8 ± 0.1 32 2.5 ± 0.1 66 1.5 ± 0.1 967 1.7 ± 0.0 1193 2.0 ± 0.0

All goats 103 2.4 ± 0.1a 358 1.9 ± 0.0b 129 2.5 ± 0.1a 258 1.5 ± 0.0c 3126 1.8 ± 0.0d 3974 2.0 ± 0.0

F=Female, M=Male. All preweaned=aged 0 – 4.5 months; All weaner=4.5 month – I0; All yearling=I1; F pregnant, F lactating, F dry, and buck had I1 – toothless. Means in a column with different

superscripts differed significantly at the .05 level.

Appendix 1

210


Table 9

Table 9 Number of kiddings, does kidded and their productivities and kids dynamics in Karangasem, Buleleng and Jembrana Regencies, Bali Province. Regency Number of kiddings, does kidded, and their productivities

No. of kids born No. of does Kidding rate (%)

Female Male Total No. of kidding Kidded Percentage Total

Karangasem 289 279 568 413 362 91 396 157

Buleleng 171 152 323 195 195 78 251 166

Jembrana 34 33 67 49 49 35 139 137

Total 494 464 958 657 606 77 786 158

Regency Type of birth and number of kids born in Bali Province

Single Twin Triplet Quadruplet

Occurrence kids Occurrence kids Occurrence kids Occurrence kids

Karangasem 268 268 136 272 8 24 1 4

Buleleng 86 86 93 186 13 39 3 12

Jembrana 33 34 14 28 2 6 0 0

Total 387 387 243 468 23 69 4 16

Appendix 1

211


Table 10

Table 10 Comparison between the top 20 and bottom 20 for annual Total income (IDR million),


farms under smallholder production systems in Banjar, Busungbiu, Grogak, Mendoyo and Rendang


District

No. of

goats

sold/year

Turn

off

rate

(%)

Flock

size

(goats)

Labourer

to goat

ratio

No. of

does

owned

(IDR million)

Total

income

Total

variable


Top 20

1 Rendang 37 96 39 19.5 10 64.225 17.153 47.072 4.707

2 Rendang 13 111 12 3 4 25.762 9.498 16.263 4.066

3 Rendang 11 76 14 7 3 19.944 7.953 11.991 3.997

4 Rendang 35 102 34 11.3 12 59.769 16.454 43.315 3.610

5 Mendoyo 6 150 4 4 2 10.865 4.073 6.792 3.396

6 Rendang 32 100 32 10.7 11 52.253 15.718 36.535 3.321

7 Rendang 16 76 21 10.5 7 29.916 10.529 19.387 2.770

8 Rendang 13 83 16 8 5 22.127 8.689 13.437 2.687

9 Rendang 21 93 23 11.5 9 34.765 11.265 23.500 2.611

10 Rendang 19 75 25 8.3 8 32.281 13.142 19.139 2.392

11 Banjar 20 83 24 12 9 41.510 20.393 21.117 2.346

12 Rendang 11 89 12 6 6 20.428 72.170 13.211 2.202

13 Busungbiu 12 150 8 4 6 21.610 8.665 12.945 2.157

14 Rendang 19 57 33 8.2 8 34.345 17.226 17.118 2.140

15 Rendang 16 84 19 3.8 6 25.734 13.215 12.519 2.086

16 Rendang 8 89 9 3 3 13.488 7.254 6.234 2.078

17 Busungbiu 18 86 21 10.5 9 36.736 18.194 18.542 2.060

18 Rendang 19 85 22 11 8 27.341 10.897 16.444 2.055

19 Grogak 16 76 21 7 6 31.296 19.335 11.961 1.994

20 Rendang 27 61 44 22 15 48.682 18.993 29.688 1.979

Bottom 20

1 Grogak 0 0 7 2.3 1 0.639 9.073 (8.434) (8.434)

2 Rendang 0 0 5 1.3 1 0.456 6.923 (6.466) (6.466)

3 Mendoyo 0 0 8 8.0 1 0.730 7.005 (6.275) (6.275)

4 Rendang 3 18 15 2.5 1 6.702 12.884 (6.182) (6.182)

5 Rendang 0 0 6 3.0 1 0.548 5.009 (4.462) (4.462)

6 Mendoyo 0 0 3 1.5 1 0.274 4.480 (4.207) (4.207)

7 Mendoyo 0 0 3 1.5 1 0.274 4.480 (4.207) (4.207)

8 Rendang 0 0 5 2.5 1 0.456 4.641 (4.185) (4.185)

9 Mendoyo 0 0 9 4.5 2 0.821 8.878 (8.057) (4.029)

10 Grogak 0 0 14 7.0 3 1.278 13.063 (11.786) (3.929)

11 Mendoyo 0 0 4 4.0 1 0.365 4.073 (3.708) (3.708)

12 Mendoyo 0 0 2 1.0 1 0.183 3.747 (3.565) (3.565)

13 Mendoyo 0 0 2 1.0 1 0.183 3.747 (3.565) (3.565)

14 Mendoyo 0 0 2 1.0 1 0.183 3.747 (3.565) (3.565)

15 Mendoyo 0 0 7 3.5 2 0.639 7.412 (6.774) (3.387)

16 Grogak 0 0 4 1.3 2 0.365 6.874 (6.509) (3.254)

17 Busungbiu 2 33 6 3.0 1 4.048 7.199 (3.152) (3.152)

18 Mendoyo 0 0 6 3.0 2 0.548 6.679 (6.132) (3.066)

19 Busungbiu 0 0 5 2.5 2 0.456 6.466 (6.010) (3.005)

20 Mendoyo 0 0 1 0.5 1 0.091 3.014 (2.923) (2.923)


Appendix 1

212


Table 11

Table 11 Effects of flock size on annual turn off rate (%), GM(A-B) (IDR million) and GM/doe

(IDR million) of goats reared in Banjar, Busungbiu, Grogak, Mendoyo and Rendang Districts, Bali

Province.

Flock size

(goats)

Turn off rate (%)




n=7 n=25 n=12 n=68 n=68 n=175

1≤10 0 ± 20 56 ± 9 0 ± 11 7 ± 4 36 ± 6 20 ± 5a

11≤20 24 ± 17 52 ± 10 15 ± 14 * 38 ± 7 32 ± 6be

21≤30 54 ± 20 56 ± 20 76 ± 29 * 53 ± 8 60 ± 10cfg

31≤42 * 29 ± 17 * * * 29 ± 17aefhi

41≤53 * * * 0 ± 14 * 0 ± 14ah

51≤85 * * * * 61 ± 9 61 ± 9dgi

1 - 85 26 ± 11afh 48 ± 7be 30 ± 11cfg 3 ± 7dgh 47 ± 4ae 35 ± 4

Flock size

(goats)





1≤10 (6.652 ± 5.255) 0.221 ± 2.241 (6.726 ± 2.809) (3.708 ± 1.041) (0.803 ± 1.622) (3.534 ± 1.330)a

11≤20 (4.593 ± 4.291) 1.911 ± 2.477 (4.935 ± 3.716) * 1.642 ± 1.705 (1.494 ± 1.606)b

21≤30 8.127 ± 5.255 8.311 ± 5.255 11.960 ± 7.432 * 9.437 ± 2.145 9.459 ± 2.682cg

31≤42 * 10.100 ± 4.291 * * * 10.100 ± 4.291dg

41≤53 * * * (16.810 ± 3.716) * (16.810 ± 3.716)e

51≤85 * * * * 24.66 ± 2.241 24.660 ± 2.241f

1 - 85 (1.039 ± 2.861)aeg 5.137 ± 1.891a 0.100 ± 2.924cef (10.260 ± 1.929)dfg 8.733 ± 0.973b 2.009 ± 0.964

Flock size

(goats)





1≤10 (1.216 ± 1.195) (0.304 ± 0.509) (3.208 ± 0.639) (2.570 ± 0.237) (0.691 ± 0.369) (1.598 ± 0.302)a

11≤20 (0.936 ± 0.976) 0.243 ± 0.563 (1.358 ± 0.845) * 0.093 ± 0.388 (0.489 ± 0.365)bfj

21≤30 0.869 ± 1.195 0.893 ± 1.195 1.994 ± 1.690 * 1.115 ± 0.488 1.218 ± 0.61cgk

31≤42 * 0.446 ± 0.976 * * * 0.446 ± 0.976dfghi

41≤53 * * * (1.853 ± 0.845) * (1.853 ± 0.845)ahj

51≤85 * * * * 1.946 ± 0.509 1.946 ± 0.509eik

1 - 85 (0.427 ± 0.65)a 0.32 ± 0.43a (0.857 ± 0.665)bd (2.211 ± 0.439)cd 0.616 ± 0.221a (0.283 ± 0.219)


Appendix 1

213


Table 12

Table 12 Effects of flock size on labourer ratio, number of does owned per household (does), and

number of goat sold per household (goats) in Banjar, Busungbiu, Grogak, Mendoyo and Rendang


Flock size

(goats)





n=7 n=25 n=12 n=68 n=63 n=175

1≤10 3 ± 1.8 3.8 ± 0.8 3.1 ± 0.9 1.5 ± 0.3 3 ± 0.5 2.9 ± 0.4a

11≤20 7.2 ± 1.4 7.3 ± 0.8 9.6 ± 1.3 * 5.6 ± 0.6 7.4 ± 0.5bg

21≤30 12 ± 1.8 16.2 ± 1.8 7 ± 2.5 * 9.1 ± 0.7 11.1 ± 0.9ch

31≤42 * 17.8 ± 1.4 * * * 17.8 ± 1.4di

41≤53 * * * 8.2 ± 1.3 * 8.2 ± 1.3egh

51≤85 * * * * 17.4 ± 0.8 17.4 ± 0.8fi

1 - 85 7.4 ± 1ad 11.3 ± 0.6a 6.6 ± 1cd 4.8 ± 0.6b 8.8 ± 0.3a 8.2 ± 0.3

Flock size

(goats)





1≤10 1 ± 2 3 ± 1 3 ± 1 1 ± 0 3 ± 1 2 ± 1a

11≤20 6 ± 2 5 ± 1 6 ± 2 * 5 ± 1 5 ± 1b

21≤30 8 ± 2 8 ± 2 6 ± 3 * 8 ± 1 8 ± 1c

31≤42 * 24 ± 2 * * * 24 ± 2d

41≤53 * * * 13 ± 2 * 13 ± 2eg

51≤85 * * * * 13 ± 1 13 ± 1fg

1 - 85 5 ± 1a 10 ± 1a 5 ± 1a 7 ± 1b 7 ± 0a 7 ± 0

Flock size

(goats)





1≤10 (0 ± 3) 4 ± 4 (0 ± 2) 0 ± 1 3 ± 1 1 ± 1a

11≤20 3 ± 3 7 ± 1 3 ± 2 * 6 ± 1 5 ± 1b

21≤30 13 ± 3 12 ± 3 16 ± 4 * 12 ± 1 13 ± 2cf

31≤42 * 12 ± 3 * * * 12 ± 3df

41≤53 * * * (0 ± 2) * 0 ± 2a

51≤85 * * * * 24 ± 1 24 ± 1e

1 - 85 5 ± 2ae 9 ± 1a 6 ± 2def 0 ± 1bf 11 ± 1c 7 ± 1


Table 13

Table 13 Prices of goats sold/year in Rendang, Banjar, Busungbiu, Grogak and Mendoyo Districts,

Bali Province. Description Age (months) Prices (IDR million) Description Age (months) Prices (IDR million)

F preweaned 1 – 4.5 1.000 – 1.250 M preweaned 1 – 4.5 1.250 – 1.500

F weaner 4.5 - 10 1.250 – 1.500 M weaner 4.5 - 10 1.500 – 1.750

F yearling 12 1.500– 1.750 M yearling 12 1.750 – 2.000

F dry ≥12 1.500 – 1.750 M buck ≥12 2.000 – 2.500

Mecaru 3-12 1.000 – 2.000 Male for Eid Qurban 12-24 1.800 – 2.500

F=Female, M=Male, All preweaned=aged 0 – 4.5 months; All weaner=4.5 month – I0; All yearling=I1; F dry, and buck had I1 –

toothless.

Appendix 1

214


Table 14

Table 13 Effects of housing (battery and colony) systems on annual turn off rate (%), GM(A-B)

(IDR million) and GM/doe (IDR million) of goats reared in Banjar, Busungbiu, Grogak, Mendoyo

and Rendang Districts, Bali Province.

Housing (battery

or colony)

systems

Turn off rate (%)




n=7 n=25 n=12 n=68 n=63 n=175

Battery 26 ± 11 51 ± 6 * 6 ± 4 45 ± 5 32 ± 4

Colony * * 11 ± 9 * 44 ± 5 27 ± 5

Battery - Colony 26 ± 11ae 51 ± 6bcf 11 ± 9a 6 ± 4a 44 ± 38def 31 ± 3

Housing (battery

or colony)

systems





Battery (1.547 ± 3.645) 2.662 ± 1.929 * (4.661 ± 1.300) 8.551 ± 1.654 1.251 ± 1.157

Colony * * (4.572 ± 2.784) * 3.727 ± 1.791 (0.422 ± 1.655)

Battery - Colony (1.547 ± 3.645)afh 2.662 ± 1.929ae (4.572 ± 2.784)cfg (4.661 ± 1.300)dgh 6.139 ± 1.219be 0.693 ± 0.948

Housing (battery

or colony)

systems





Battery (0.500 ± 0.685) 0.079 ± 0.363 * (2.518 ± 0.245) 0.477 ± 0.311 (0.615 ± 0.218)

Colony * * (2.158 ± 0.524) * 0.200 ± 0.337 (0.979 ± 0.311)

Battery - Colony (0.500 ± 0.685)ad 0.079 ± 0.363a (2.158 ± 0.524)cde (2.518 ± 0.245)be 0.339 ± 0.229a (0.737 ± 0.178)


Table 15

Table 14 Effects of housing (battery and colony) systems on labourer ratio, number of does owned

per household (does), and number of goat sold per household (goats) in Banjar, Busungbiu, Grogak,

Mendoyo and Rendang Districts, Bali Province.

Housing (battery

or colony)

systems





n=7 n=25 n=12 n=68 n=63 n=175

Battery 7.4 ± 1.7 7.7 ± 0.9 * 1.9 ± 0.5 8.8 ± 0.8 6.4 ± 0.5

Colony * * 5.6 ± 1.3 * 5.9 ± 0.8 5.8 ± 08

Battery - Colony 7.4 ± 1.7a 7.7 ± 0.9a 5.6 ± 1.3a 1.9 ± 0.5b 7.3 ± 0.6a 6.2 ± 0.4

Housing (battery

or colony)

systems





Battery 5 ± 2 6 ± 1 * 2 ± 1 7 ± 1 5 ± 1

Colony * * 4 ± 1 * 5 ± 1 5 ± 1

Battery - Colony 5 ± 2ad 6 ± 1a 4 ± 1ac 2 ± 1bcd 6 ± 1a 5 ± 0

Housing (battery

or colony)

systems





Battery 5 ± 2 7 ± 1 * 0 ± 1 11 ± 1 6 ± 1

Colony * * 2 ± 2 * 7 ± 1 5 ± 1

Battery - Colony 5 ± 2adf 7 ± 1ag 2 ± 2ae 0 ± 1bde 9 ± 1cfg 6 ± 1


Appendix 2 Questionnaire

215


Appendix 2

Questionnaire for village goat production in Bali Province

Name of interviewer : …………………………………………………………..….…

Date of interview : …………………………………………………………..…….

Village : ………………………………………………………..……….

District : ……………..….………………………………………………

Regency : ……………………………………..…… Province: Bali

I General information about smallholder labourers and their profiles

1. Household indentification

Name of farmer:

[………………………………….] [……………………………………]

Main job :

:

Side job :

:

Date/month/year of birth : ……. ………… …………

Sex : [1] Male [2] Female

Religion : [1] Hindu [2] Muslim

: [3] Buddha [4] Christian

2. Level and length of education

Level of education Completed

Never had formal education

Primary school/Kejar Paket A (Grade 1 to 6)

Secondary school/Kejar Paket B (Grade 7 to 9)

High school (Grade 10 to 12)

University

3. Number of dependant in a family (people)

Sex Relationship to the head of family age [year] Education

M F

4. Do you rear goats? [1] Yes [2] No

5. How long have you been raising goat? Since Year ……….. Month ………………..


216

6. Do you raise goats continuously?

[1] Yes [2] No if No, go to No. 13

7. For how long did you stop? Since Year … Month …….. to Year …… Month ……..

8. If you stopped raising goats, the reasons were:

[ ] ……………………….……………………………………………………..…………

[ ] ……………………….……………………………………………………..…………

9. Main reasons to rearing goats in general. [Give scale of priority]

[ ] To increase income [ ] Hobby or killing time

[ ] To utilise agricultural by-products [ ] Low inputs

[ ] To utilise roughage [ ] Easy to raise

[ ] To get goat manure as fertilizer [ ] Easy to sell

[ ] For consuming the meat & milk [ ] Breeding purposes

[ ] Resale [ ] High price

[ ] Low loss [death, theft] [ ] Religion [Livestock offering]

[ ] Inherit [ ] Others …………………………..……….

10. What is the major source of your cash income?

This must be calculated and mentioned each amount roughly.…………….….……..……

.………………………………………………………………………………………….…

……………………………….……………………..………………………………………

11. The goats being raised now, are they yours?

[1] Yes [2] No [3] Partly if No, go to No. 17

12. Whose goats are they?

[1] Group [2] Shared [3] Others

13. What the reasons to rearing goats for the group or others or shared?

……………………………………… ….................................................................

……………………….……………… ……………….…………………………….

II. General information about goats and their profiles

1. The composition of goats owned by a farmer

Physiology of goat Quantity [%]

Female preweaned

Female weaner

Female yearling

Female pregnant

Female lactating

Female dry

Male preweaned

Male weaner

Male yearling

Male buck

Total 100%


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2. Identity of an individual goat

Dam #/name: …………………… Sire #/name: ……………………….

Breed

[………………………………….]

Number of goat :

Name of goat :

Sex :

Date/month/year of birth :

Type of birth: [1] Single [2] Twins [3] Triplets

Teeth at the first recording

I0 – 2 – 4 – 6 – 8 – Broken

3. Regular recording for female and male goats

Measurements Time of data recorded in year 2013

1st 2

nd 3

rd 4

th

.../….. .../…. .../…. .../….

FAMACHA©

score [1 – 5]

Body weight [kg]

Body length [cm]

Chest circumference [cm]

Chest depth [cm]

Height at withers [cm]

Rump height [cm]

4. Data collection

Description

Body size

[1] Good [2] Average [3] Bad [4] Very bad

Body condition

[1] Good [2] Average [3] Bad [4] Very bad

Pregnancy status

[1] First … [2] Second .. [3] Third . [4] Fourth

[1] Empty… [2] Early pregnancy [3] Mid pregnancy [4] Late pregnancy

Lactation status

[1] First [2] Second [3] Third [4] Fourth

[1] Empty [2] Early pregnancy [3] Mid pregnancy [4] Late pregnancy

Milk production at the moment

[1] ≤ 500 ml [2] 500 ml ≤Milk ≤ 1000 ml [3] 1000 ml ≤Milk ≤ 1500 ml


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III. Breeding and reproduction

1. Where do you get the goat breed? Write their scores

[ ] Born in own farm

[ ] Sharing goat

[ ] Buy from other farmers

[ ] Buy from livestock market

[ ] Buy from breeding station

2. Do you find any constraints in selecting the breed?

[1] Yes [2] No

Reason: ……………………………………………………………………………………..…

………………..………………………………………………………………………………..

3. Are you satisfied with this goat breed?

[1] Yes [2] No [3] Not really sure

Reason: …………..……………………………………………………………………………

…………………………………………..………………………………………………………

4. How do you select the breed? What type/characteristic of the breed do you prefer?

Please scale the priority Please write the type/characteristic of goats do you prefer?

[ ] Age

[ ] Body size

[ ] Colour

[ ] Litter size

[ ] Milk production

[ ] Other

5. How do you predict the age of goat?

…………………………………………………………………………………………………

…………………………………………………………………………………………………

6. How do you predict the weight of goat?

…………………………………………………………………………………………….……

………………………………………………………………………………………………….

7. Have you ever weighed you goats?

[1] Yes [2] No

WHY …………………………………………………………………………………………..

………………………………………………………………………………………………….

8. What is the mating system used to your goats?

[1] Natural mating [2] Artificial insemination [3] Mixed

9. In general, what month of the year do your does kid? …………………………………..

10. How often do your does kid? ………………………..………………………………….


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11. How many kids do they produce in the year?

Kidding intervals Kids/kidding [litter size] Kids/year

1 2 3 >3

1 Kidding/year

2 Kiddings/year

3 Kidding/2 years

12. How big the litter size is?

First kidding = ……………………………………… kid[s]/kidding

Second kidding = ……………………………………… kid[s]/kidding

Third kidding = ……………………………………… kid[s]/kidding

Fourth kidding = ……………………………………… kid[s]/kidding

Fifth kidding = ……………………………………… kid[s]/kidding

13. In the mating, are the bucks run together with does?

[1] Never [2] All year around [3] Part of the year [specify, up to 3 months]

14. Where do bucks come from and are they selected for joining?

Source of buck Selected [criteria] Not selected

Own buck bred

Own buck bought

Borrow from neighbours

Shared

Rental

Others

15. How many years do you use your does for breeding purposes?

After kidding …….times or when she reaches ……years of age then they will be culled

16. How many years do you use your bucks for breeding purposes?

After he reaches … years of age then they will be culled

17. Kidding data for the last twelve months

Age of does No. of does/group No. of does kidded No. of kids born No. of kids dead

<1 year

1–2 years

> 2 year

18. Mortalities

How many kids die?

At birth … goats 1 month old … goats

1–3 months old … goats > 3months old … goats

19. What is the major cause of death [give scale of priority]

[ ] Abortion [ ] Diseases [ ] Under-nutrition

[ ] Accident [ ] Predator [Dog?] [ ] Others ……………..

20. When did most of the kids die [which months of the year?]

…………………………………………………………………………………………………

…………………………………………………………………………………………………


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21. Has abortion every occurred in your flock?

[1] Yes [2] No, go to No. 17 [3] Don‘t know

22. What did you do with does that aborted?

[ ] Nothing

[ ] Treated, how?

…………………………………………………….………………………………………….

…………………………………………………….………………………………………….

[ ] Killed

[ ] Sold

[ ] Others…………………………………………………………………………………….

23. Reproductive dan productive performance of an individual goat

Reproductive & productive performance Measurement

Birth [date/month/year]

Weight [kg]

Weaning Age

Weight [kg]

First maturity Age

Weight [kg]

First mating Age

Weight [kg]

Service per conception [S/C]

First pregnancy Age

Weight [kg]

Length of gestation [day]

First kidding Age

Weight [kg]

Ratio female to male kids

Litter size

Kidding interval [day]

Mortality [%]

Milk production [ml/day]

Length of lactation [day]

Interval between parturition and

subsequent mating [day]

IV. Management and Nutrition

1. Land available for farmer [either owned or rented or shared]

Agriculture …... m2/ha

Animal use …... m2/ha

2. What is the rearing system is applied? Please give the scale of priority

Scale of priority of rearing system Reasons

[ ] Tethering

[ ] Extensive grazing

[ ] Cut and carry

[ ] Integration with tree

[ ] Combination

[ ] Others


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3. Do you plant roughage, legume or fodder for your goat?

[1] Yes ………...………………. m2/ha

[2] No

4. How much feedstuff given to a doe every day

Feedstuffs given Quantity given [kg/goat/day] Feeding frequency per day

Dry Pregnant Lactating

Roughage

Rice pollard

Tofu waste

Coconut waste

Cassava waste

Cacao pod

Coffee pulp

Cashew nut pulp

Feed additive

5. What the age of a kid weaned is and firstly fed separately from its doe? ………….Month

6. How much feedstuff given to a kid every day

Feedstuffs given Quantity [kg/goat/day] Feeding frequency per day Detail

Roughage

Rice pollard

Tofu waste

Coconut waste

Cassava waste

Cacao pod

Coffee pulp

Cashew nut pulp

Feed additive

Total kg/goat/day]

7. With the current number of goat reared, how do you find the availability of the roughage?

[ ] Limited only when it is dry season

[ ] Limited throughout the year

[ ] Enough throughout the year

[ ] More than enough throughout the year

8. When the availability of feedstuffs is more than required, what do you do with them?

[ ] make silage

[ ] sometimes make the silage

[ ] throw away because don‘t know to make silage and make them as fertilizer

V. The role of farmer group

1. Are you a member of goat farmer group?

[1] Yes [2] No If Yes since year …...as:

[1] As a leader [2] As a committee [3] As a member

If No go to No.4


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2. What group activities do the members often do together?

......................................................................................................................

......................................................................................................................

3. What are the benefits being a participant of goat farmer group?

.......................................................................................................................

.......................................................................................................................

4. What the drawbacks for being not a participant of goat farmer group are?

.......................................................................................................................

.......................................................................................................................

VI. Health and Disease control management

1. In the last twelve months, were any of your goats sick?

[1] Yes [2] No

2. What type of disease did your goats have?

[ ] Do not know how to describe the symptoms

[ ] Specify if you know [give the scale of priority]

Name of disease Number of goat

Sick [goat] Death [goat]

3. What did you do when your goats were sick?

[ ] Did nothing

[ ] Homemade medicine

[ ] Bought drugs and treated by yourself

[ ] Asked help from other farmers

[ ] Asked help from vet

VII. Marketing

1. When do you usually sell your goats?

When ………………………………………..……………..…………………………………

Reason: ……………………………………………..………………………………………..

When …….………………………………….……………………………………….….……

Reason: ……………………………………………………...……………………….……….

2. What are the characteristics of goat to be sold?

………………………………………………….………………………………….…………

……………………………………….…………………………………………………….…

3. Please fill the form the latest selling goats

Physiology of goat Time selling

[Month]

Age of goat

[year]

Predicted weight

[kg]

Price

[IDR/goat]

Female preweaned

Female weaner

Female yearling

Female pregnant

Female lactating


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Female dry

Male preweaned

Male weaner

Male yearling

Male buck

4. Have you ever sold productive does?

[1] Yes [2] No If Yes, why?

[1] Urgently need cash

[2] Insufficient feed resources as there are enough number of goats reared

[3] Others, mention …………………………………………………………….……………...

5. Where do you usually sell your goats?

[1] In caged [2] Livestock markets

[3] Slaughtering houses [4] Inter island goat spots

[5] Others, mention ………………………………………………………………..…………..

6. Who usually buy your goats?

[1] Other goat farmers [2] Slaughtering house

[3] Goat traders [4] Inter island goat traders

[5] Others, mention ……………………………………………..……………………………..

7. Where do you usually get the information of current price for your goats?

[1] Other goat farmers [2] Slaughtering house

[3] Goat traders [4] Inter island goat traders

[5] Others, mention …………………………………………………..………………………..

8. How do you usually put the price?

[ ] By weighing the goats

[ ] By calculating special equation for goats

[ ] By predicting the weight and age of goats

[ ] Others, mention ………………………………………………………………………..…..

9. How do you do with the selling goats

[1] Done by individual [2] Done by group [3] Others, mention …

10. Do you need a help from others when you need to sell your goats

[1] Yes [2] No

If Yes, who is going to deal with? Mention ………….……………………………………….

What is the service fee? Mention ……………………………………………….…………….

11. Does the group give help in marketing your goats?

[1] Greatly helpful [2] Helpful enough [3] Less helpful

[4] Not helpful at all [5] Others, mention …...

VIII. The role of goat in Hindu ceremony

1. Have you ever used goat as an offering sacrifice when you perform your ceremony?

[1] Yes [2] No

Reason: ……………………………………………………………………………….……….


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2. Would please give the scale of priority of these animals as offering sacrifices in Hindu

ceremony?

[ ] Goat [ ] Swan [ ] Buffalo

[ ] Cattle [ ] Pig [ ] Duck

[ ] Hen [ ] Others, please mention ………….……………

3. In future, will you use goat as an offering sacrifice?

[1] Yes [2] No

Reason: ……………………….…………………….………………………………………….

…………………………………………………………………………………………………..

IX. Constraints and Challenges faced in goat rearing

1. Mention the constraints faced in goat rearing

………………………………………………….……………………………………………..

…………………………………………………….……………………………………….….

2. Mention challenges faced in goat rearing

…………………………………………………………….…………………………………..

…………………………………………………………….…………………………………..

Full name of respondent and signature

[ ]

…………………………………., ……………… …………………. 2014.

Improvement of rearing goats in Bali Province, Indonesia687794/s005151_phd_correcte… · Banjar,...

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