POSTHARVEST ANALYSIS OF VEGETABLES IN...

POSTHARVEST ANALYSIS OF VEGETABLES IN FIJI

EGGPLANT, OKRA AND TOMATO

by

Binesh Prasad

A thesis submitted in fulfillment of the requirement for the degree of

Master of Agriculture

Copyright © 2015 by Binesh Prasad

School of Agriculture and Food Technology

Faculty of Business and Economics

The University of the South Pacific

March, 2015

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TABLE OF CONTENTS

PAGE

1.0 INTRODUCTION 1

1.1 Research Problem 3

1.2 Research Objectives 4

2.0 LITERATURE REVIEW 5

2.1 Background of Fiji 5

2.1.1 Fiji’s agriculture industry 5

2.1.2 The export of vegetables from Fiji 6

2.2 The Postharvest Technology of the Selected Vegetable Crops 7

2.2.1 Eggplant 7

2.2.2 Okra 7

2.2.3 Tomato 8

2.3 Status Of Postharvest Handling And Losses 9

2.4 Causes of Postharvest Losses 18

2.4.1 Mechanical injury 18

2.4.2 Postharvest pathogens 18

2.4.3 Physiological deterioration 18

2.5 Postharvest Loss and Quality Indicators 19

2.6 Significance of Postharvest Loss to Natural Resource Management 19

2.7 Climatic Factors Affecting Postharvest Quality of Vegetables 20

2.8 Firmness and Decay of Vegetables 21

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2.9 Commodity System Analysis Methodology 21

2.9.1 Causes of losses at different points of the system 24

3.0 RESEARCH METHODOLOGY 25

3.1 Scope 25

3.2 Research Design and Sampling 27

3.3 Crop Selection 28

3.4 Data Collection 29

3.4.1 Types of losses at production level 29

3.4.2 Types of losses at exporter level 29

3.4.3 Types of losses at retailer level 30

3.4.4 General data 30

3.5 Quantitative Loss Assessment 30

3.5.1 Percentage of rejected crops at different levels 31

3.5.2 Types of rejected crops at different levels 31

3.5.3 End use of rejected crops at different levels 31

3.5.4 Observed tomatoes 32

3.6 Statistical Analysis 32

4.0 RESULTS AND DISCUSSIONS 33

4.1 Eggplant 33

4.1.1 Postharvest losses in eggplants at different levels 33

4.1.1.1 Postharvest losses in eggplants at production strata level 33

4.1.1.2 Postharvest losses in eggplants at local municipal retailer level 35

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4.1.1.3 Postharvest losses in eggplants at exporter strata level 36

4.1.2 End use of rejected eggplants at different levels 37

4.1.2.1 End use of rejected eggplants at production strata level 37

4.1.2.2 End use of rejected eggplants at local municipal retailer stratalevel

38

4.1.2.3 End use of rejected eggplants at exporter strata level 39

4.1.3 Aggregate postharvest losses and end use of rejected eggplants 39

4.1.4 Non-trade loss vs. absolute loss of eggplants 41

4.2 Okra 42

4.2.1 Postharvest losses in okra at different levels 42

4.2.1.1 Postharvest losses in okra at production strata level 42

4.2.1.2 Postharvest losses in okra at local municipal retailer strata level 44

4.2.1.3 Postharvest losses in okra at exporter strata level 46

4.2.2 End use of rejected okra at different levels 47

4.2.2.1 End use of rejected okra at production strata level 47

4.2.2.2 End use of rejected okra at local municipal retailer strata level 47

4.2.2.3 End use of rejected okra at exporter strata level 48

4.2.3 Aggregate postharvest losses and end use of rejected okra 49

4.2.4 Non-trade loss vs. absolute loss of okra 51

4.3 Tomato 51

4.3.1 Postharvest losses in tomato at different levels 52

4.3.1.1 Postharvest losses in tomato at production strata level 52

4.3.1.2 Postharvest losses in tomato at local municipal retailer stratalevel

53

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4.3.2 End use of rejected tomato at different levels 54

4.3.2.1 End use of rejected tomato at production strata level 54

4.3.2.2 End use of rejected tomato at local municipal retailer strata level 55

4.3.3 Aggregate postharvest losses and end use of rejected tomato 55

4.3.4 Non-trade loss vs. absolute loss of tomato 58

4.4 Five Hundred (500) Observed Tomatoes 59

4.5 Postharvest Operations 61

4.5.1 Harvesting 61

4.5.2 Sorting and Grading 61

4.5.3 Handling and Transportation 61

5.0 SUMMARY, CONCLUSIONS AND POLICY IMPLICATIONS 62

REFERENCES 70

APPENDICES 75

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LIST OF FIGURES

PAGE

Figure 1 Levels of Hunger in different continents (in millions) 2

Figure 2 Multi-Stratified Sampling 28

Figure 3 Overall postharvest losses in eggplants 40

Figure 4 Overall end use of rejected eggplants 41

Figure 5 Non-trade loss vs. absolute loss of eggplants 42

Figure 6 Overall postharvest losses in okra 49

Figure 7 Overall end use of rejected okra 50

Figure 8 Non-trade loss vs. absolute loss of okra 51

Figure 9 Overall postharvest losses in tomatoes 56

Figure 10 Overall end use of rejected tomatoes 57

Figure 11 Non-trade loss vs. absolute loss of tomatoes 58

Figure 12 Flow network and losses of eggplant from farmers’ fields to consumers

62

Figure 13 Flow network and losses of okra from farmers’ fields to consumers

63

Figure 14 Flow network and losses of tomato from farmers’ fields to consumers

64

Figure 15 Projected loss of tomatoes over a storage period of 12 days under farmer’s conditions.

65

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LIST OF PLATES

PAGE

Plate 1 Map of Fiji 25

Plate 2 Sigatoka Valley 25

Plate 3 Photo of Sigatoka Valley 26

Plate 4 Photo of Sigatoka Valley 26

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LIST OF TABLES

PAGE

Table 1 Income Classification of Selected Countries of the Asia-Pacific Region

10

Table 2 Estimated Levels of Postharvest Losses in the Asia-Pacific

Region

11

Table 3 Average Levels of Postharvest Losses in Vegetables at Various Steps of the Marketing Chain

17

Table 4 Postharvest losses in eggplants at production level 34

Table 5 Postharvest losses in eggplants at local municipal retailer level 35

Table 6 Postharvest losses in eggplants at exporter level 37

Table 7 End use of rejected eggplants at production level 38

Table 8 End use of rejected eggplants at local municipal retailer level 38

Table 9 End use of rejected eggplants at exporter level 39

Table 10 Postharvest losses in okra at production level 43

Table 11 Postharvest losses in okra at local municipal retailer level 45

Table 12 Postharvest losses in okra at exporter level 46

Table 13 End use of rejected okra at production level 47

Table 14 End use of rejected okra at local municipal retailer level 48

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Table 15 End use of rejected okra at exporter level 48

Table 16 Postharvest losses in tomatoes at production level 52

Table 17 Postharvest losses in tomato at local municipal retailer level 54

Table 18 End use of rejected tomatoes at production level 55

Table 19 End use of rejected tomatoes at local municipal retailer level 55

Table 20 Losses in 500 tomatoes observed at four (4) day intervals 59

Table 21 Summary of total postharvest losses in selected vegetables 66

Table 22 Summary of types of postharvest losses in selected vegetables 66

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LIST OF APPENDICES

PAGE

Appendix 1 Questionnaire and Data Collection Sheet at Production Level 75

Appendix 2 Questionnaire and Data Collection Sheet at Exporter Level 79

Appendix 3 Questionnaire and Data Collection Sheet at Retailer Level 82

Appendix 4 The Fiji Quarantine Pathway – Bilateral Quarantine Agreement 85

Appendix 5 Analysis of variance for % losses of eggplant at farmer level

88

Appendix 6 Analysis of variance for % losses of eggplant at retailer level

89

Appendix 7 Analysis of variance for % losses of eggplant at exporter level

90

Appendix 8 Analysis of variance for % losses of okra at farmer level

91

Appendix 9 Analysis of variance for % losses of okra at retailer level

92

Appendix 10

Analysis of variance for % losses of okra at exporter level

93

Appendix 11

Analysis of variance for % losses of tomato at farmer level

94

Appendix 12

Analysis of variance for % losses of tomato at retailer level

95

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ACKNOWLEDGEMENT

I would like to put across my sincere appreciation and positive reception to a number of

people who were very generous and ready to lend a hand during the course of my research.

Without their backing, things would not have gone virtually as well.

Heartfelt thanks to ACIAR/USP for availing the funds for the study and providing all the

required backup support and services.

I am greatly indebted to Mr Falaniko Amosa and Professor Steven J. R. Underhill for

being my supervisor and co-supervisor respectively, providing initial guidance and

assistance during my planning, field research and thesis writing stages.

A very special recognition and thanks to Mr Sanjay Anand for tolerating me during the

entire period of my initial planning and thesis writing. Thank you very much for your

valuable expertise in statistical analysis, patience and continuous guidance and kind

words of encouragement and support.

Countless thanks to Rohit, Shonal and Kalawa for accompanying and helping me

tirelessly during the execution of field tasks and data collection. I also thank my

colleagues: Dinesh, Ami, Bimlesh and the staff of Sigatoka Agriculture Station especially

Pranil, Ajay, Naresh and Siti for their assistance in numerous ways.

I also thank and dedicate this thesis to my beautiful wife (Anjini), handsome son

(Animesh) and cute daughter (Anisha) for making me this capable through their

sacrifices, guidance, patience and continuous encouragement.

And finally to my parents and the Glory of the Almighty, my Saviour to whom I owe

everything. You were the pillars of my strength.

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ABSTRACT

Research was conducted in Fiji to determine the extent of perceived postharvest losses

occurring at three levels - production level, exporter level and local municipal retailer

level - and the end use of the rejected perishable vegetable commodities, namely;

eggplant, okra and tomato. Postharvest losses of these vegetables were found to be

ranging from 25.2 to 40.4; 23.9 to 31.5 and 19.5 to 31 per cent respectively. An

aggregate average postharvest loss of 32.8% was ascertained for eggplants, 27.5% for

okra and 25.8% for tomatoes along the postharvest chain.

The postharvest loss caused by shape was relatively similar i.e. 7.8% and 8.7% for

eggplant and okra respectively. Losses due to physical abrasion was quite high (10.5%)

in eggplant whereas okra and tomato were in the lower bracket of 3.8% and 4%

respectively. Percentage loss caused by senescence/overripe ranged from 8.8 to 10.9 for

the three crops and loss caused by pest/disease was very high in tomato 11% whereas

eggplant and okra were in the lower bracket of 5.9 and 6.1 per cent respectively.

The total postharvest losses of the selected commodities were further categorised into

non-trade loss (monetary gains partially realised in terms of domestic consumption and

livestock feed) and absolute loss (wastage). Eggplant (80%) had the highest absolute loss

followed by okra (76%) and tomatoes (71%).

Actual postharvest loss in tomatoes were also ascertained at production level by observing

tomatoes from the three production strata (lower valley, mid valley and upper valley) and

a very interesting data was obtained, which is challenging the traditional view that Fijian

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farmers are often poorly connected with market-based postharvest losses. The actual

postharvest loss in tomatoes observed after four days was 15.3% and the perceived

postharvest loss in tomato at production level was 14.6%.

A number of deficiencies currently exist in the postharvest management and processing of

vegetables in Fiji and action must be taken in order to upgrade systems, in order to reduce

the levels of postharvest losses. There is a great need to adopt and develop simple

technologies for loss prevention and value addition along the postharvest chain.

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CHAPTER 1

INTRODUCTION

Fresh vegetables have been a part of the human diet since the dawn of history. However,

their full nutritional importance has only been recognised in recent times (Wills et al.,

1998). Despite the remarkable advances made in increasing food production at the global

level, approximately one-third of all food produced is lost or wasted from farm to fork.

(Food and Agriculture Organisation-FAO, 2011). There are many reasons for this, one of

which is food losses occurring in the postharvest and marketing system. The report

suggests that these losses tend to be highest in those countries where the need for food is

greatest. There are several accounts on the estimate of postharvest losses to be anywhere

between 20 – 100% (FAO, 1989). In the light of growing demand for food and land

resources, such losses are simply unacceptable.

This wastage not only has an enormous negative impact on the global economy and food

availability, it also has major environmental impacts. It is distressing to note that so much

time is being devoted to the culture of the plant, so much money is spent on irrigation,

fertilisers and crop protection measures, but little attention is paid and resources devoted

to the issues related with postharvest losses resulting in failure to meet food requirement

of the hungry millions (FAO, 2010, Fig. 1).

Preventing postharvest losses reduces the use of resources required for food production,

labour and disposal costs, and reduces all the environmental, economic and social impacts

linked to food waste disposal (FAO, 2011).

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Figure 1: Levels of Hunger in different continents (in millions). (Source: FAO, 2011)

Agriculture is the third predominant sector of the economy of Fiji as this contributes 9.35

% to the gross domestic production (Ministry of Primary Industries-MPI- Annual Report,

2010). The agriculture sector not only creates a large number of employment

opportunities but also provides a source of livelihood for the majority of the rural

population and outer island population.

For the improvement of the agriculture sector, the proper understanding of the dynamics

of vegetable quality from farm to fork is critical. Studies show that reduction in the

postharvest loss, particularly if it can economically be avoided, would be of great

significance to growers and consumers alike (FAO, 2011). Food losses during harvest and

storage translate into lost income for farmers and into higher prices for consumers. It can

also indirectly reduce the rate of deforestation caused by agricultural land expansion.

3

Increased emphasis should be placed on conservation after harvest, rather than

endeavouring to further boost crop production, as this would appear to offer a better return

for the available resources of labour, energy and capital (Wills et al., 1998).

1.1 Research Problem

The growing importance of vegetables in Fiji’s economy can be well appreciated in terms

of their rising domestic demand on account of increase in population and per capita

income; their increasing export potential; the need for providing employment

opportunities in the rural areas, and vegetables being relatively more remunerative crops.

Due to the large distances that separate the production areas and the sub-optimal

postharvest technology management (including the method of picking/plucking/digging,

grading, packing, storing and transporting), a large proportion of vegetables is lost or

spoiled at various stages of the postharvest activity chain (Kumar, 2004).

Many studies have been conducted for estimating the postharvest losses, particularly in

the developed countries. However, the importance of postharvest losses in agricultural

commodities is not fully recognised in developing countries where agricultural production

is not commercial or market oriented. Meanwhile, the number of scientists involved in

production research in these countries is significantly higher than those engaged in

postharvest losses in agricultural commodities (FAO, 2011).

4

The study by Karim and Wee (1996) had revealed that well managed postharvest

activities for vegetables led to higher yields and profits to producers. It is therefore,

important to estimate the nature and extent of postharvest losses of vegetables occurring

in Fiji, why they are occurring and the best way to remediate them.

Hence, keeping all these problems into consideration, a study on postharvest analysis of

vegetable crops in Fiji was undertaken.

1.2 Research Objectives

1.2.1 To estimate the postharvest losses in the selected vegetable crops namely

eggplant, okra and tomato at farmer, exporter and local municipal retailer

levels;

1.2.2 To separate the postharvest losses into “non-trade postharvest loss” and

“absolute postharvest loss”;

1.2.3 To estimate the actual postharvest losses in tomato at four (4) day intervals for

12 days;

1.2.4 To make suggestions to minimise postharvest losses in vegetable crops namely

eggplant, okra and tomato.

5

CHAPTER 2

LITERATURE REVIEW

2.1 Background of Fiji

Fiji is a group of islands in the South Pacific, lying about 4,450 km (2,775 miles)

southwest of Honolulu and 1,770 km (1,100 miles) north of New Zealand. Of the 322

islands and 522 smaller islets making up the archipelago, about 106 are permanently

inhabited. Viti Levu, the largest island, covers about 57 % of the nation's land area, hosts

the two official cities (the capital Suva, and Lautoka) and most other major towns, such as

Ba, Nasinu, and Nadi (the site of the international airport), and contains some 69 % of the

population. Vanua Levu, 64 km to the north of Viti Levu, covers just over 30 % of the

land area though is home to only some 15 % of the population. Its main towns are Labasa

and Savusavu (Wikipedia, 2012).

2.1.1 Fiji’s agriculture industry Agriculture being the mainstay of Fiji’s economy, contributes around 28% to total

employment in the formal sector and indirectly employing many more. This sector which

was once a major stronghold of Fiji’s economy is the third largest now, contributing $416

million (9.35%) annually to the nations GDP. Sugarcane which used to dominate the

sector now only contributes (1.7%) and has been surpassed by other crops, horticulture

and livestock production (3.6%) and subsistence sector (2.75%) (Agriculture Fiji Online,

2012).

The non-sugar agricultural sector over the years has shown a promising trend. The main

commodities’ that constitute this sector are root crops (taro, cassava, yams and sweet

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potato), tropical fruits (pineapple, papaya and mango), vegetables, spices, kava, coconut

products and livestock (Agriculture Fiji Online, 2012).

Agriculture has the potential in other sectors such as tourism and agro-industries and as a

major economic activity in the rural areas; agriculture plays an important role in the

process of rural development as it is an interwoven component of rural life. Having a rich

resource base and tropical climate, Fiji has an advantage in producing a wide variety of

tropical fruits and vegetables. Given Fiji’s fast expanding tourism sector, agricultural

growth is necessary to supply the ever increasing demand from the local and hotel and

tourism sector. Thus, the potential for Fiji’s agriculture sector is in production for local

consumption, export of high value commodities and niche agricultural produce.

2.1.2 The export of vegetables from Fiji

A Bilateral Quarantine Agreement (BQA) (Appendix 4) was signed between Fiji and the

main vegetable export market i.e., New Zealand for selected fresh produce. This

agreement necessitates that Fiji facilitate technical requirements of pest risk management

in accordance with requirements of the importing country. As a follow up to the

establishment of this BQA, an export pathway for fruits and vegetables destined for export

to New Zealand was developed. In accordance with this agreement, a High Temperature

Forced Air (HTFA) treatment facility was established in Nadi, Fiji to fulfill the

pre-requisite for fresh export of fruit fly host crops.

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2.2 The Postharvest Technology of the Selected Vegetable Crops

2.2.1 Eggplant

The botanical name of eggplant is Solanum melongena L., also known as Guinea squash,

garden egg, aubergine, and bringal or bringall. The fruit shape varies from globular to pear

to elongate. Eggplants require an optimum temperature range of 21o to 29oC for best

growth and should not be exposed to extremes of temperature, but can produce well under

light or heavy rainfall conditions (Nonnecke, 1989).

Eggplants are ready for harvest when fully formed and before the fruit has begun to

change colour usually fifty days (early types) to eighty days (late types) under optimum

growing conditions. Harvest is by hand and progressive as the season advances and fruits

mature in successive waves. The appropriately matured eggplant fruit is firm, heavy

feeling, and glistening, and the calyx should be fresh and green. Anything less than this in

appearance gives the impression of excessive water loss and aging i.e. eggplant

postharvest damage/loss (Nonnecke, 1989).

2.2.2 Okra

Okra, or Hibiscus esculentus L, is a member of the Malvaceae (mallow) family, also

known as gumbo, gombo, quingumbo, lady’s finger, or quaibo. The edible portion of the

okra is the immature tender seed pod, which quickly loses its desirable characteristics as it

matures (Nonnecke, 1989).

The okra pods must be harvested at the most appropriate stage of maximum quality and

acceptability. To be attractive okra pods should appear bright green, firm, free of

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blemishes and because okra bruises easily, the pods must be tightly placed in containers

for transportation (Nonnecke, 1989).

2.2.3 Tomato

The botanical name of tomato is Lycopersicon esculentum and is a highly perishable crop

of the Solanaceae family. The thrust of all tomato production is to have fruit acceptable to

the market for which the crop was grown. Definitions of tomato maturity have to be

precise in order to identify the differing requirements for the harvested fruits (Nonnecke,

1989).

The United States Department of Agriculture (USDA), (1963) has established tomato fruit

colour codes that express the maturity of fruit using colour:

i. Green Fruit – mature green, the jelly surrounding the seed has formed –

when treated the fruit becomes equivalent to vine ripened fruit.

ii. Breakers – 10 per cent pink or red, usually internally pink

iii. Turning – 10 to 30 per cent pink or red

iv. Pink – 30 to 60 per cent pink or red

v. Light red – 60 to 90 per cent pink or red

vi. Red – over 90 per cent surface red

According to Nonnecke (1989), the tomato throughout its maturity cycle should remain

firm and be free from puffiness, bruises, blemishes and off-odours. Harvested tomatoes in

the postharvest handling cycle should be firm to the touch and its quality is at its peak

when the fruit has reached the red ripe stage.

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2.3 Status of Postharvest Handling and Losses

Rapid growth in horticultural development has been witnessed in the Asia-Pacific region

(FAO, 2011). The developments in science and technology could provide an opportunity

for intensifying the production of horticultural produce.

The World Food Conference convened in Rome in 1974, drew attention to the concept of

postharvest food loss reduction as a significant means to increase food availability. The

Special Action Program for Food Loss Prevention, of the Food and Agriculture

Organisation of the United Nations (FAO) initially focused on durable food grains, owing

to their prominence in developing country diets. An Expert Consultation on Food Loss

Prevention in Perishable Crops, mainly covering fruit and vegetables was held in Rome in

1980.

A recent study in Fiji by Underhill (2013) stated that a postharvest horticultural loss along

a commercial tomato supply chain from farm to vendor is 32.93 %. Of the total losses, 8.8

% of the harvested crop is rotten at time of packing due to high ripening temperature and

humidity because the grower places tomatoes under plastic sheeting or leaves in the sun to

speed up the on-farm ripening process from day 1 to 4. Furthermore, farmers pick hard

green fruits to reduce damage by birds but 8.9 % of tomatoes failed to ripen at the time of

packing and 0.13 % had physical damages during transportation on day 5 and 6.4 % of

tomatoes are rejected by vendor on the first day of trading due to overripe or rotting.

Underhill further, stated that a projected further 14.45% loss will occur if tomato fruits are

not consumed within 48 hours and after reaching the vendor and if there was a 1 day delay

or break in the chain then total postharvest wastage would be 60.78%.

10

In the same work, Underhill (2013) reported that the total rejected tomatoes (32.93%) that

are removed from the commercial supply chain are used either at home or undergoes

intra-community trading (11%), fed to domestic livestock (6.34%), ends up as on-farm

and municipal refuse (14.69%) and 0.9 % of product end use was not identified.

Poor infrastructures for storage, processing and marketing in many countries of the region

contribute to a high proportion of waste, which average between 10% and 40%

(Choudhury, 2004). Sirivatanapa (2004) also presented that postharvest losses which

average between 24% and 40% in developing countries, and between 2% and 20% in

developed countries, are a major source of waste. Major infrastructural limitations also

continue to impose severe constraints to domestic distribution as well as to the export of

horticultural produce. Rolle (2004) stated that many low and middle income countries

(Table 1) continue to focus on capacity building in order to minimise losses in fruits and

vegetables as they struggle to overcome technical, infrastructural and managerial

constraints and maintain quality and safety.

Table 1 Income Classification of Selected Countries of the Asia-Pacific Region

Low Income Low-Middle

Income

Upper Middle High Income

Cambodia China Malaysia Singapore

India Fiji Japan

Vietnam Iran Korea

Philippines Hong Kong

Sri Lanka

Thailand

(Source: World Bank Indicators, 2003)

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According to Rolle (2004), poor quality produce and high levels of postharvest losses

(Table 2) occur primarily due to the use of poor quality inputs, poor cultural practices at

the production level, lack of knowledge and skill in harvesting, postharvest handling,

packing and packaging, inadequacies in basic and postharvest specific infrastructure in

terms of pre-cooling facilities, transport, storage and marketing, lack of processing

facilities, high transportation costs, poor integration of activities along the chain and

complex marketing channels. The situation is further aggravated by the warm humid

climates of most countries within the Asia-Pacific region.

Table 2 Estimated Levels of Postharvest Losses in the Asia-Pacific Region

Country Estimated level of losses (%)

India 40Indonesia 20 - 50 Iran >35 Korea 20 - 50 Philippines 27 - 42 Sri Lanka 16 - 41 Thailand 17 - 35 Vietnam 20 - 25

Choudhury (2004) in his paper also stated that considerable waste occurs owing to the fact

that small farmers lack resources and are unable to market their produce and implement

suitable postharvest handling practices. Spoilage of fresh produce is also accelerated by

the hot and humid climate of the region. Postharvest management and processing of

horticultural produce has assumed considerable significance in light of increasing demand

for fruits and vegetables in the region.

12

Doza (2005) in a country paper presented that postharvest losses in food grains in

Bangladesh are reported at an estimated 15%, while in fruits and vegetables they are

estimated at 20%–25%. For highly perishable fruits and vegetables, these losses may go

as high as 40%. Furthermore, Doza (2005) said that the problem of postharvest losses is

compounded by the lack of proper processing, preservation and storage systems. The

absence of a well-developed marketing network and rapid transportation in Bangladesh

also contributes significantly to high postharvest losses in fruits and vegetables.

According to Mao (2005), growth in the Cambodian agricultural sector can be fuelled by:

increased production through higher productivity, containment of losses which could

often be as high as 35%– 40%, sound postharvest support systems, crop diversification

including horticulture and floriculture, and clearing of large areas of landmines and

unexploded ordinances, and increased emphasis on animal husbandry and fisheries.

Ahsan (2005) reported that India is the second largest producer of vegetables in the world,

ranking next to China, and accounts for about 15% of global vegetable production. It is

estimated that between 30% and 35% of India’s total vegetable production is lost owing to

poor postharvest practices. Verma and Joshi (2000) stated that greater emphasis must be

placed on problem oriented research which employs integrated approaches to solving

postharvest issues. Furthermore, they stated that while mechanical harvesting of

horticultural crops increases efficiency, it results in considerable waste.

13

The problems encountered with production agriculture are more easily overcome than

those experienced in the postharvest sector. The production of horticultural crops in

Indonesia showed an increasing trend for the period 2001 through 2003. Fruit production

increased from 9.96 million tons in 2001, to 11.7 million tons in 2002, and reached 13.6

million tons in 2003. Similar trends were observed for vegetables, the production of which

increased from 6.9 million tons in 2001 to 7.1 million tons in 2002, and reached 8.6

million tons in 2003 (Haryanto and Rochani, 2005).

Despite this progressively growing trend in production, constraints to postharvest

handling continue to be encountered. Considerable losses therefore, occur in horticultural

products. Budiastra (1995) reported losses of the order of 30% to 40% while Tridjaya

(2005) reported losses of 10% for fruits and 9.6% for vegetables in Indonesia.

According to Haryanto and Rochani (2005), postharvest handling of fresh fruits and

vegetables has a relatively insignificant impact on farmer income, given the low level of

consumer demand for fruits and vegetables that have been cleaned, sorted and graded.

Farmers are therefore, reluctant to apply proper postharvest handling techniques.

Furthermore, the insignificant price reward for produce quality often results in losses to

the farmer when postharvest handling is done on an individual, rather than on a

collaborative basis. A case study on banana marketing in West Java Province in Indonesia

indicated that farmers were reluctant to adopt quality improvement technologies since

there was no guarantee of improved prices (Setijadi et al., 2003).

14

Similarly, Moghaddasi et. al. (2005) reported that considerable volumes of agricultural

crops produced in developing countries go to waste between their production and

consumption points. Levels of waste vary between 30% and 35%. Approximately 7.6

metric tonnes of the 25 metric tonnes of fruits and vegetables produced in Iran go to waste.

Significantly lower quantities of waste of the order of 7% to 10% are realised in developed

countries. The most significant losses occur in strawberries (35%–40%) while the lowest

level of losses is realised in saffron (2%–3%).

Horticultural produce is highly perishable and is thus highly prone to postharvest losses.

Losses in horticultural produce in Nepal vary between 15% and 35% at different stages

along the chain from harvesting to marketing (Kaini, 2000).

According to the Nepalese Master Plan for Horticulture Development (MPHD, 1991), as

reported by Paudel (2005), conservative estimates of losses on a weight basis were 25%

for vegetables, 20% for fruits and 32% for potatoes including tuber seed. The postharvest

shelf life of horticultural produce is dependent upon the condition of production, season,

variety, the stage of harvesting, the method of harvesting, as well as the packaging,

transportation and marketing system.

Bajracharya (2000), reported that the total loss during the transportation of tomato from

Syangja (mid hills) to Butwal (markets in the plains) was around 23% and Sharma

(2001/2002) reported that the losses sustained during transportation of tomato up to

Kathmandu from Kapurkot, Salyan (western hills) and Lal Bandi, Sarlahi (Terai) were

approximately 35%.

15

Werner et al. (1991) reported physical losses of 22.85% in tomatoes, 15.84% in cabbage

and 12.85% in cauliflower, in addition to the 5% to 10% moisture losses determined by

research conducted by FAO, in Terai, Kalimati market and retail shops in Kathmandu.

A study on losses during the transportation of horticultural produce from Bhairahwa,

Nepal to Gorakhpur, India, conducted by the Marketing Development Division (MDD,

1999/2000), determined a 74% loss in oranges, 26.3% loss in apples, 17.39% loss in

cabbages and 15% loss in potatoes. Losses incurred during the transportation of apples,

mangoes, cauliflower and cabbages from Birgunj, Nepal to Patna, India were also

assessed by the MDD. These were 22.22%, 36.36%, 18.75% and 19.23%, respectively.

Physical losses, which occur during the transportation of tomato, French bean, capsicum

and cauliflower from Kapurkot, Shalyan, Nepal to Sitapur market Lucknow, India, were

10%, 5%, 5% and 5%, respectively (MDD). Similarly physical losses in tomatoes, French

beans, capsicum and cauliflower from Kapurkot, Salyan, Nepal to Azadpur market, New

Delhi, India were 1.33%, 1.25%, 5.88% and 1%, respectively. In the case of transporting

cabbage, radish, cauliflower and orange from Birtamod, Nepal to Silguri, India, these

were 6.7%, 3.48%, 4.48% and 2.06%, respectively. Thapa and Shrestha (2001/02)

reported that losses in mandarin oranges during transportation from Dhankuta to

Kathmandu by bus ranged between 2.7 and 8.2% and thereby recommended the use of

small wooden and bamboo boxes of 18''x12''x12'' for packaging these fruit.

16

The Agra-Business and Trade Promotion Multi-Purpose Co-operative (ABTRACO-2003)

reported a 50% postharvest loss in mandarin oranges during their export to Tibet and

Bangladesh.

Anjum and Awan (2005) in their report stated that Pakistan has a comparative advantage

in the production and export of high value and non-traditional crops as the Government

has adopted an Act namely; Agricultural Produce (Grading and Marking Act), under

which grades and standards of quality of agricultural and livestock commodities are laid

down and enforced for export. Despite this comparative advantage, returns to farmers are

low, due to postharvest losses, which average between 30% and 40%.

Serrano (2005) reported that according to Pantastico (1979), postharvest losses in fruit

crops in the Philippines averaged at 28% in 1979. Approximately 6% of fruit production

was used either as feed or went to waste in 1985 (Statistical Handbook of Agriculture,

MAF-BAECON, 1985).

Losses in bananas ranged from 4% to 60% and were caused by physical damage, green

soft disorder, weight loss, disease, and over ripening. Losses in the ‘Carabao’ variety of

mangoes, ranged from 5% to 87% owing to stem-end rot, mechanical damage and

rejection by mango exporters. Variability in national data on losses in these crops

stemmed from the use of several loss assessment methods each with different objectives,

as well as the manner in which data on losses was presented (Lizada, 1990).

17

According to Rapusas (2005), loss studies conducted in Philippines by the Postharvest

Horticulture Training and Research Centre (PHTRC) on the tomato cultivar ‘Improved

Pope’, shipped from Claveria in Mindanao to Los Baños, Laguna in Luzon, losses ranged

from 4% to 8%. This transport loss was based on the proportion of rotten fruits as well as

diseased and severely damaged fruits. Weight (moisture) losses after ripening of sound

fruits, slightly damaged fruits and fruits with severe abrasions were found to be 7.9%,

18.0% and 58.6%. Mangaoang (1982) reported a postharvest loss of 11.9% and a

post-storage loss of 12.1% amounting to a total postharvest loss of 24%.

Cyril (2005) stated that postharvest losses in Sri Lanka significantly reduce the

availability of local produce in markets, and widen the price gap between the producer and

consumer. Losses are generally higher in fruits than in vegetables. Results (Table 3) of an

Island-wide survey in Sri Lanka conducted by the Institute of Postharvest Technology of

Sri Lanka in the Year 2002, revealed postharvest losses in vegetables to vary between

16% and 41%. These losses were highest for cabbage and leeks and lowest for okra.

Table 3 Average Levels of Postharvest Losses in Vegetables at Various Steps of

the Marketing Chain Postharvest Loss (%)

Crop Grower Collector Wholesaler Retailer Total Brinjal (Eggplant) 10.99 8.96 2.22 10.75 34.76 Beet 7.21 9.12 2.13 8.56 27.02 Cabbage 8.36 13.11 6.17 13.23 40.87 Carrots 6.47 9.32 2.83 9.78 28.40 Leeks 9.77 14.47 5.2 11.44 40.88 Tomato 7.25 10.25 4.59 13.33 35.42 Beans 6.07 7.93 1.54 9.5 25.04 Bitter Gourd 5.13 5.13 1.86 10.25 22.37 Okra 4.5 4.55 2.38 4.64 16.02

18

2.4 Causes Of Postharvest Losses

2.4.1 Mechanical injury

Mechanical damage during harvesting and associated handling operations can result in

defects on the produce (Wills et al., 1998). According to Choudhury (2004), fresh fruits

and vegetables are extremely vulnerable to mechanical injury due to their tender texture

and high water content. Improper handling, inappropriate packaging and poor packing

during transit are the cause of bruising, cutting, breaking, impact wounding, and other

forms of damage in fresh fruits and vegetables.

2.4.2 Postharvest pathogens

The incursion of fruits and vegetables by fungi, bacteria, insects and other organisms, is a

major cause of postharvest losses in fruits and vegetables. Microorganisms readily attack

fresh produce and spread rapidly, owing to the lack of natural protection mechanisms in

the tissues of fresh produce, and the large quantity of nutrients and moisture which

supports their growth. Managing postharvest rot is ever more becoming a complicated

task, since the number of pesticides available is rapidly declining as end user concern for

food safety is greater than ever (Choudhury, 2004).

2.4.3 Physiological deterioration

Vegetable tissues still respire after harvest, and continue their physiological activity. It

occurs due to lack of minerals or unattractive ecological conditions such as low or high

temperature injury and humidity. Physiological deterioration can also occur unexpectedly

owing to enzymatic activity, leading to over ripeness and senescence (Choudhury, 2004).

19

2.5 Postharvest Loss and Quality Indicators

Postharvest loss is defined as a “measurable quantitative and qualitative loss of a given

product at any point along the postharvest chain” (De Lucia & Assennato, 1994); and

includes the change in the availability, edibility and wholesomeness of the food that

prevents it from being consumed (FAO, 1989). Postharvest losses are highest with

horticultural produce whose postharvest quality is much dependent on climatic

conditions.

Quality is defined as “the composite of product characteristics that offers value to the

buyer or consumer” (De Lucia & Assennato, 1994) or more loosely as “the degree of

excellence of a product or its suitability for a particular use” (Abott, 1999). There are

several quality attributes of fresh produce that changes after harvesting. Therefore, it is

fundamental to establish good management practices in the agricultural industry,

especially during distribution and marketing chains.

Like fruits, vegetables are perishable crops. These crops deteriorate very rapidly after

harvest owing to a number of factors. Quantitative losses, which are readily measurable,

occur as a result of reduced weight due to product decay and senescence. Qualitative

losses occur due to deterioration in texture, flavour and nutritional value (Liu, 1999).

These forms of losses can be translated into monetary loss due to reduced prices.

2.6 Significance of Postharvest Loss to Natural Resource Management

High postharvest losses mean that vegetable farmers have to expand the land area under

cultivation or to continuously crop the same land from season to season to compensate for

20

the anticipated losses. This practice of continued expansion of farm land is exerting more

pressure on the fragile natural resource base. For example, FAO (2006) reported that there

is widespread nutrient depletion of soils arising from continuous cropping. The

over-exploitation of forest resources for food production is a major cause of deforestation

and loss of biodiversity throughout the world and postharvest losses have been found to

contribute significantly to deforestation.

2.7 Climatic Factors Affecting Postharvest Quality of Vegetables

The principal weapon in the postharvest armoury relates to control of the storage

environment and handling practices. Temperature, the most significant environmental

factor, is very crucial in the postharvest chain. Rates of postharvest deterioration are

affected by increase in temperature owing to the elevated rate of postharvest physiological

processes occurring in crop produce after harvest.

Castro et al., (2005) reported that vegetables can be stored for a relatively longer period

provided conditions are favourable, notably a temperature and relative humidity of

10-15oC and 85-95%, respectively. Studies by Getinet et al. (2008) also proved that

maintaining relatively lower temperature and higher relative humidity during storage

using evaporative cooling systems could maintain the quality of vegetables.

Moreover, Yeshida et al. (1984) indicated that high temperature increases enzymatic

catalysis and leads to biochemical breakdown of compounds in fruits and vegetables.

Paull (1999) also stated that temperature and relative humidity are two major criteria used

21

to define critical limits in monitoring programs associated with the hazard analysis and

critical control point (HACCP) system.

2.8 Firmness and Decay of Vegetables

According to Van Dijk and Tijskens (2000), the texture and firmness of fruits and

vegetables depend on the presence and interactions of different chemical components,

such as pectin’s in the middle lamellae and cellulose/hemi-cellulose matrix in the primary

cell wall, as well as on physical aspects like archestructure and turgor. During transit and

storage some of these chemical components or physical aspects are affected, whilst others

are not. Therefore, it is assumed that the firmness of vegetables consists of two parts, a

variable part and a fixed part. Components adding to the fixed part of the firmness include

the (chemically inert) cellulose/hemi-cellulose matrix. Turgor and part of pectin that is

susceptible to enzymatic degradation constitute the variable part of the firmness.

2.9 Commodity System Analysis Methodology

There are 26 components in the Commodity System Analysis Methodology and each

component is potentially important but not always relevant for all commodities. This

methodology permits analysis of a whole commodity system and requires a

multidisciplinary team (La Gra, 1990).

Components 1-7 (Pre-Production) put the commodity into perspective within the

horticultural market, and gain some understanding of how much competition one may

22

face, whether there are any political, economic or environmental constraints or incentives,

and if there is any technical or marketing assistance available.

Components 8 – 11 (Production) deals with many of the choices made during production

that will later affect postharvest quality, food safety, produce losses and economic value.

The first step in identifying possible improvements is to determine whether any of these

production components are contributing to postharvest problems. As you collect

information on each component, compare current practices to known recommendations

for producing the commodity.

Components 12-21 (Postharvest)-Postharvest handling practices will have an enormous

impact on produce quality, losses and safety. Postharvest handling maintains the quality

of produce, but cannot improve it. Understanding each step of the postharvest chain will

enable you to determine whether any current practices are causing problems. Sometimes it

is possible to measure losses at each step and determine whether making a simple change

can have a major impact.

Component 22-26 (Marketing) is not simply the last step of handling fresh produce, but

must be part of the overall plan to provide produce that best meets the needs of the

consumer. Consumer preferences play a large role in determining the economic value of

the produce.

23

(Source: La Gra., 1990)

24

2.9.1 Causes of losses at different points of the system

(Source: La Gra., 1990)

25

CHAPTER 3

METHODOLOGY

3.1 Scope

This study was conducted in the Suva, Sigatoka, Nadi and Lautoka municipal markets

and along the west bank of Sigatoka Valley, also known as the ‘salad bowl’ of Fiji

(Fig.2). It was purposely selected since they are the major vegetable producing and

marketing area, with a number of producers, marketing agencies and exporters.

Plate 1 Map of Fiji (Source: www.fijimaps.com)

Plate 2 Sigatoka Valley (Source: www.fijimaps.com)

Sigatoka Valley

26

Plate 3 Photo of Sigatoka Valley (Source: https://www.google earth.com/Fiji, 2012)

Plate 4 Photo of Sigatoka Valley (Source: https://www.google earth.com/Fiji, 2012)

27

3.2 Research Design and Sampling

For selection of vegetable growers and market functionaries’ multi-stage stratified

sampling was carried out (Fig. 2). At the first stage, one principal vegetable market,

namely Suva Municipal market was selected based on maximum annual arrival of

vegetables.

At the second stage, three primary markets were selected for the present study. These

were: Sigatoka municipal market, Nadi municipal market and Lautoka municipal

market. At the third stage, 15 vegetable farmers per commodity from Sigatoka Valley

West Bank, feeding the municipal markets and exporters were randomly selected.

Considering the geographical condition of the area, out of 15 farmers per commodity,

5 each were selected from the lower valley, mid valley and upper valley of Sigatoka

West Bank.

The sample also included market functionaries of each category, viz. exporters and

local municipal retailers. Three (3) exporters were included in the sample. Five (5)

local municipal retailers each from secondary as well the three selected primary

markets were taken for the study. As such, a total of 20 local municipal retailers were

selected.

28

Figure 2 Multi-Stratified Sampling

3.3 Crop Selection

Several vegetable crops are cultivated in the Sigatoka Valley. For the present study,

three major vegetables grown in the study area were considered. The selection of

major vegetables was done on the basis of total annual production of different

vegetables in the Sigatoka district and its potential for export under the Bilateral

Quarantine Agreement (BQA), non BQA and value adding. Thus, eggplant (pritam

variety), okra (Clemson spineless variety) and tomato (money maker variety) were

selected for the study.

Crops

1. Tomato 2.Eggplant 3.Okra

Producers Lower Valley

(5)

Mid Valley (5)

Upper Valley (5) Exporters

(3)

Retailers

Suva Market (5)

Sigatoka Market (5)

Nadi Market (5)

Lautoka Market (5)

29

Local Market Crop (Tomato)

Produce BQA Crop (Eggplant)

Export Market

Non-BQA Crop (Okra)

3.4 Data Collection

The study was based on the primary data collected from the selected farmers,

exporters and local municipal retailers involved in the production and marketing using

a pre-structured schedule by personal interview, respective questionnaires and data

collection sheet method (Appendices 1, 2, 3). Data from the different agencies were

collected during 2013 vegetable growing season (May-August) that covered the

following.

3.4.1 Types of losses at production level:

i. Shape

ii. Physical abrasion

iii. Senescence/overripe

iv. Pest/disease

3.4.2 Types of losses at exporter level:

i. Shape



iv. Pest/disease

30

3.4.3 Types of losses at retailer level:

i. Shape



iv. Pest/disease

3.4.4 General Data:

i. End use of rejected crops at each level i.e. home use, animal feed and

waste/throw away.

ii. Rejects from high temperature forced air (HTFA) at exporter level was

also recorded.

3.5 Quantitative Loss Assessment

The flow network of vegetables from farmers’ field to the consumers was studied to

identify the types of losses. The extent of loss was calculated using the equation given

below:

Loss in crops, % =

Where, Wdv = Weight of rejected and damaged vegetables sorted out

Wtv = Total weight of vegetables before sorting at any level

31

3.5.1 Percentage of rejected crops at different levels

The total weight (yield) of vegetables was recorded at production (farm gate),

local municipal retailer and exporter level. The vegetables were then sorted out

and weight of rejected vegetables was taken. From these weights, the percentage

loss was calculated using the above equation.

3.5.2 Types of rejected crops at different levels

The rejected vegetables were then sorted out into four categories i.e. shape,

physical abrasion, senescence/overripe and pest/disease and individual group

weights were recorded again. From these weights, the percentage losses for the

four categories were calculated using the above equation.

3.5.3 End use of rejected crops at different levels

The farmers, local municipal retailers and exporters were asked to quantify the end

use of rejected vegetables into home use, animal feed and waste. From these

weights, the percentage end use for the three categories was calculated using the

above equation.

The data from end use of rejected crops was further classified into two categories:

i. Non-trade loss – whereby the rejected vegetables had monetary value

attached to it in terms of domestic use and animal feed.

ii. Absolute loss – whereby no monetary gain can be realised from the rejected

vegetables i.e. waste.

32

3.5.4 Observed tomatoes

The postharvest loss of 500 tomatoes from each of the three production strata was also

observed after harvest at every four day intervals for 12 days to ascertain the actual

postharvest losses and further categorised into various types (causes).

3.6 Statistical Analysis

In the study, postharvest losses in vegetables were calculated at different stages. The

losses were calculated to find out at which level maximum loss was incurred.

Descriptive statistical tools like means and percentages were used to present the data

from the study. The data collected was subjected to analysis of variance to determine

any significant losses occurring between the three productions strata, during handling

between the three exporting facilities, between the three local municipal retail outlets

as well as between the four types (causes) of postharvest losses. The Discover Version

of the GENSTAT Statistical Software package was used.

33

CHAPTER 4

RESULTS AND DISCUSSIONS

This chapter is divided into five sections. Section 4.1, 4.2 and 4.3 discusses the

postharvest losses (PHL) and the end use of the rejected eggplant, okra and tomato

vegetable respectively. The perceived losses of these vegetables were ascertained first at

production level, then at local municipal retailer level and also at exporter level. The types

of loss at each level were also ascertained, viz. shape, physical abrasion,

senescence/over-mature and pest/disease along the postharvest chain. The total

postharvest loss has been further categorised into non-trade loss (monetary gains partially

realised) and absolute loss (wastage). The observed results of tomatoes from the three

production strata (lower valley, mid valley and upper valley) have been presented in

section 4.4. Section 4.5 elaborates the different operations practiced in selected vegetables

along the postharvest chain.

4.1 Eggplant

The postharvest losses and end use of rejected eggplants at different levels along the

postharvest chain are presented in sub-sections 4.1.1 and 4.1.2 respectively and at

aggregate level these are presented in sub-section 4.1.3. The total postharvest loss of

eggplant is further categorised into non-trade loss and absolute loss in sub-section 4.1.4.

4.1.1 Postharvest losses in eggplants at different levels

4.1.1.1 Postharvest losses in eggplants at production strata level

Five (5) farmers each from the lower, mid and upper valley were selected. A total of

1200kg, 1000kg and 680kg of eggplants from the respective strata were sampled. Table 4

34

reveals that the types of postharvest losses in different production strata varied in extent

and nature. The extent of losses varied from strata to strata as well as the types of

postharvest losses. On the overall basis, the maximum loss in eggplant was ascertained in

the lower valley (17%), followed by upper valley (16.8%) and mid valley (11.3%). On

studying the different types of losses, it was observed that the maximum average loss was

due to shape (4.2%), followed by pest/disease (3.9%), physical abrasion (3.5%) and

senescence/over-mature (3.4%). The average postharvest loss of eggplant at production

level was 15%. Cyril (2005) reported a 10.99 % loss in eggplants at grower level in Sri

Lanka.

Table 4 Postharvest losses in eggplants at production level

Types of Losses

Production Strata

Range

Mean (%)

Lower Valley

Mid Valley

Upper Valley

Shape 4.5 (54) 4.1 (41) 4.1 (28) 4.1-4.5 4.2 a*

Physical Abrasion 3.4 (41) 3.1 (31) 4.1 (28) 3.1-4.1 3.5 a

Senescence/Over-mature 4.6 (55) 1.9 (19) 3.7 (25) 1.9-4.6 3.4 a

Pest/Disease 4.6 (55) 2.2 (22) 4.8 (33) 2.2-4.8 3.9 a

Total Loss 17.0 (204) 11.3 (113) 16.8 (114) 11.3-17 15.0

LSD (5% level) 1.494

* Means followed by the same letter are not significantly different. ( ) Weight in kilograms

There were no significant difference (P>0.05) among the four types of losses at

production level. There were also no significant differences (P>0.05) in eggplant losses

between the three production strata. This can be attributed to eggplant being an export

crop and as such follows a stringent export requirement pathway due to its susceptibility

to fruit fly infestation. All the farmers growing for the export market follow a standard

35

protocol of management practices as approved under the bilateral quarantine agreement

(Annex 4); therefore the types of losses are uniform among them.

4.1.1.2 Postharvest losses in eggplants at local municipal retailer level

A total of 220kg, 150kg, 180kg and 380kg of eggplants were sampled from five (5)

retailers each from the Lautoka, Nadi, Sigatoka and Suva municipal markets respectively.

A comparison of the extent of postharvest losses in eggplants between the four local

municipal retail outlets, presented in Table 5, reveal that maximum loss was in Nadi

(16.1%), followed by Sigatoka (13%). The Lautoka and Suva municipal retailers

registered the lowest postharvest losses of 11% and 10.7% respectively. Across different

types, it is revealed that physical abrasion (5.4%) and senescence/over-mature (4.7%)

registered highest average postharvest losses, while pest/disease (1.5%) and shape (1.2%)

had an average postharvest loss on the lower bracket. The average postharvest loss of

eggplant at local municipal retailer level was 12.7%. Cyril (2005) reported a 10.75 % loss

in eggplants at retailer level in Sri Lanka.

Table 5 Postharvest losses in eggplants at local municipal retailer strata level

Types of Losses

Local Municipal Retailer Strata Range

Mean

(%) Lautoka Nadi Sigatoka Suva

Shape 0.7 (1) 2.0 (3) 1.0 (2) 1.1 (4) 0.7-2.0 1.2 b*

Physical Abrasion 5.7 (12) 6.2 (9) 3.7 (7) 6.0 (23) 3.7-6.2 5.4 a

Senescence/Over-mature 3.0 (7) 6.5 (10) 6.8 (12) 2.4 (9) 2.4-6.8 4.7 a

Pest/Disease 1.7 (4) 1.4 (2) 1.5 (3) 1.3 (5) 1.3-1.7 1.5 b

Total Loss 11.0 (24) 16.1(24) 13.0 (23) 10.7 (41) 10.7-16.1 12.7



36

There were no significant difference (P>0.05) in the percentage losses of eggplant

between the four local municipal retail outlet. This can be partially explained by the

identical prevailing trading and storage conditions at the four outlets.

Significant differences (P<0.05) were found to exist between the types of postharvest

losses at local municipal retailer levels. Higher losses resulted from physical abrasion and

over-maturity compared to losses due to shape and pest and diseases. Increased physical

abrasion results from the crop undergoing additional handling during sorting and grading

as the premium crop from the harvest goes for the export market, where it fetches higher

prices and the rejects from the export grade enters the local municipal market.

Over-maturity results from physiological deterioration and enzymatic activity as the crop

still respires after harvest (Choudhary, 2004). Lower rejects were due to shape rejection

and pest and disease as optimum cultural practices were followed as per export

requirements. In addition, rejection of the crop due to these causes from the export market

may partially be acceptable at local outlets.

4.1.1.3 Postharvest losses in eggplants at exporter strata level

A total of 1500kg of eggplants were sampled from Exporter I, 5000kg from Exporter II

and 187kg from Exporter III. The postharvest losses at exporter level were also worked

out and are presented in Table 6. It was found that types of maximum average loss was

registered by shape (2.4%), followed by physical abrasion (1.6%),

senescence/over-mature (0.7%) and pest/disease (0.5%). The average loss at exporter

level was registered as 5.1%.

37

Table 6 Postharvest losses in eggplants at exporter level

Types of Losses

Exporter Strata

Range

Mean

(%) Exporter I Exporter II Exporter

III

Shape 3.3 (50) 2.2 (110) 1.6 (3) 1.6-3.3 2.4 a

Physical Abrasion 2.7 (40) 1.6 (80) 0.5 (1) 0.5-2.7 1.6 ab

Senescence/Over-mature 0.7 (10) 0.8 (40) 0.5 (1) 0.5-0.8 0.7 bc

Pest/Disease 0.7 (10) 0.2 (10) 0.5 (1) 0.2-0.7 0.5 c

Total Loss 7.3 (110) 4.8 (240) 3.2 (6) 3.2-7.3 5.1



Percentage eggplant losses between the three exporters surveyed for this study did not

differ significantly (P>0.05). This again can be due to similar postharvest handling

practices and standard grading criteria being followed by all the export facilities for the

crop. Crop losses due to different causes were significantly different (P<0.05) upon

screening by the exporters. Higher losses were encountered from rejection due to shape

and physical abrasion as opposed to senescence/over-maturity and pest/disease.

4.1.2 End use of rejected eggplants at different levels

4.1.2.1 End use of rejected eggplants at production strata level

A perusal of Table 7 reveals that the end use of postharvest loss eggplants in different

production strata also varied in nature. On the overall basis, the average maximum end use

in loss eggplant was ascertained as waste (10.6%), followed by animal feed (2.3%) and

domestic use (2.2%).

38

Table 7 End use of rejected eggplants at production level

End use

Production Strata

Range

Mean

(%) Lower Valley

Mid Valley

Upper Valley

Animal feed 1.8 (21) 4.0 (40) 1.0 (7) 1.0-4.0 2.3

Domestic use 2.2 (26) 1.7 (17) 2.6 (18) 1.7-2.2 2.2

Waste 13.1 (157) 5.6 (56) 13.2 (90) 5.6-13.2 10.6

Total Loss 17.0 204) 11.3 (113) 16.8 (114) 11.3-17 15.0

( ) Weight in kilograms

4.1.2.2 End use of rejected eggplants at local municipal retailer strata level

The result of end use of postharvest rejected eggplants at local municipal retailer level is

presented in Table 8. Across the three different end uses, it is revealed that waste (10.6%)

registered highest average postharvest loss end use, while domestic use (1.5%) and animal

feed (0.6%) registered a lower average postharvest loss end use.

Table 8 End use of rejected eggplants at local municipal retailer level

End use

Local Municipal Retailer Strata

Range

Mean


Animal feed 0.0 (0) 2.5 (4) 0.0 (0) 0.0 (0) 0.0-2.5 0.6

Domestic use 1.7 (4) 0.0 (0) 4.2 (8) 0.2 (1) 0.0-4.2 1.5

Waste 9.3 (21) 13.6 (20) 8.8 (16) 10.5 (40) 8.8-13.6 10.6

Total Loss 11.0 (24) 16.1 (24) 13.0 (23) 10.7 (41) 10.7-16.1 12.7


39

4.1.2.3 End use of rejected eggplants at exporter strata level

The end uses of postharvest rejected eggplants at exporter level were also worked out and

have been presented in Table 9. It was found that maximum average end use was

registered by eggplants being returned to farmers (4.4%), followed by waste from high

temperature forced air (HTFA) treatment (0.7%) carried out as an export requirement for

fruit fly host crops.

Table 9 End use of rejected eggplants at exporter level

End use

Exporter Strata

Range

Mean

(%) Exporter I Exporter II Exporter III

Returned to farmers 6.7 (100) 4.0 (200) 2.7 (5) 2.7-6.7 4.4

Domestic use 0.0 (0) 0.0 (0) 0.0 (0) 0 0.0

Waste (from HTFA) 0.7 (10) 0.8 (40) 0.5 (1) 0.5-0.8 0.7

Total Loss 7.3 (110) 4.8 (240) 3.2 (6) 3.2-7.3 5.1


4.1.3 Aggregate postharvest losses and end use of rejected eggplants

The aggregate postharvest losses in eggplants were calculated by taking together the

losses at production level, local municipal retailer level and exporter level. Figure 3

reveals that postharvest losses were maximum at production level (15%) followed by

local municipal retailer level (12.7%) and minimum at exporter level (5.1%). Across

different types, it was found that maximum postharvest loss in eggplant was caused by

physical abrasion (10.5%), followed by senescence/over-mature (8.8%), shape (7.8%)

and pest/disease (5.9%). An aggregate average postharvest loss of 32.8% was ascertained

for eggplants along the postharvest chain. Cyril (2005) reported a total postharvest loss of

34.76 % in eggplants in Sri Lanka which are very similar to the results of this work.

40

Figure 3 Overall postharvest losses in eggplants

A read-through of Figure 4 reveals that the overall end use of rejected eggplants in

different production strata is wide-ranging in nature. On the overall basis, majority of the

postharvest loss eggplant was ascertained as waste (21.9%), whereas 3.7% and 2.9% is

ascertained for domestic use and animal feed respectively. An ascertained 4.4% of loss

eggplant that is returned to farmers from the exporters is also characterised as part of

waste.

0

5

10

15

20

25

30

35

Production Local MunicipalRetailer

Exporter Total Loss

Los

s (%

)

Different Levels

Shape Physical Abrasion Senescence/Over-mature Pest/Disease

41

Figure 4 Overall end use of rejected eggplants

4.1.4 Non-trade loss vs. absolute loss of eggplants

The end use of rejected eggplants is further categorised into non-trade and absolute loss as

shown in figure 5. Out of the total eggplant rejects, 80% falls in the category of absolute

loss (waste & return to farmers) and therefore, no monetary gain can be realised from it.

On the other hand, only 20% of the rejected eggplants fall under non-trade loss and has

monetary value attached to it in terms of animal feed and domestic consumption.

0

5

10

15

20

25

30

35


Exporter Total

End

Use

(%)

Different Levels

Animal Feed Domestic use Waste Return to Farmers

42

Figure 5 Non-trade loss vs. absolute loss of eggplants

4.2 Okra

The postharvest losses and end use of rejected okra at different levels along the

postharvest chain have been presented in sub-sections 4.2.1 and 4.2.2 respectively and at

aggregate level these have been presented in sub-section 4.2.3. The total postharvest loss

of okra is further categorised into non-trade loss and absolute loss in sub-section 4.2.4.

4.2.1 Postharvest losses in okra at different levels

4.2.1.1 Postharvest losses in okra at production strata level

A total of 385kg of okra from five farmers in lower valley, 280kg from five farmers in mid

valley and 315kg from five farmers in upper valley were sampled. A perusal of Table 10

reveals that the types of postharvest losses in different production strata varied in extent

Absolute Loss 80%

Non-Traded Loss 20%

43

and nature. The extent of losses varied from strata to strata as well as the types of

postharvest losses. On the overall basis, the maximum loss in okra was ascertained in the

lower valley (12.3%), followed by mid valley (11.6%) and upper valley (10.7%). On

studying the different types of losses, it was observed that the maximum average loss was

due to shape (4.9%), followed by pest/disease (3.4%), senescence/over-mature (1.7%) and

physical abrasion (1.6%). The average postharvest loss of okra at production level was

11.5%. Cyril (2005) reported only 4.5% loss in okra at grower level in Sri Lanka.

Table 10 Postharvest losses in okra at production level

Types of Losses

Production Strata

Range

Mean

(%) Lower Valley

Mid Valley

Upper Valley

Shape 6.0 (23) 5.0 (14) 3.8 (12) 3.8-6.0 4.9 a*

Physical Abrasion 0.6 (2) 2.0 (5) 2.1 (7) 0.6-2.1 1.6 b

Senescence/Over-mature 2.1 (8) 1.5 (4) 1.5 (5) 1.5-2.1 1.7 b

Pest/Disease 3.7 (14) 3.2 (9) 3.2 (10) 3.2-3.7 3.4 a

Total Loss 12.3 (47) 11.6 (32) 10.7 (34) 10.7-12.3 11.5


* Means followed by the same letter are not significantly different. ( ) Weight in kilograms There were no significant differences (P>0.05) in the percentage loss of okra between the

three production strata. However, significant differences (P<0.05) exist between the types

of losses at production level. Higher losses resulted from rejection due to inappropriate

shape and higher levels of pest and disease infestation as opposed to physical abrasion and

44

over-maturity of the crop. This may be because management practices among growers are

highly variable as the crop is a non-bilateral quarantine agreement (non BQA) commodity

with no strict protocols being administered. It can also perhaps be due to higher degree of

water stress at critical times leading to deformations and increasing the susceptibility of

the crop to pest and disease infestation, particularly formation of galls and incidence of

pod borers. Losses resulting from physical abrasion and over-maturity are at a minimal as

regular harvesting of tender pods is done and crates are used for transportation.

4.2.1.2 Postharvest losses in okra at local municipal retailer strata level

A total of 190kg of okra sampled from the Lautoka, 150kg from Nadi, 380kg from

Sigatoka and 220kg from Suva municipal markets were sampled. The comparison of

postharvest rejection in okra at local municipal retailer level, presented in Table 11, reveal

that maximum loss was in Nadi (13.2%), followed by Sigatoka (11.3%). The Lautoka and

Suva municipal retailer outlets registered the lowest postharvest losses of 10.2% and

10.5%, respectively. Across different types, it is revealed that senescence/over-mature

(6.7%) registered highest average postharvest loss, while pest/disease (1.7%), physical

abrasion (1.5%) and shape (1.4%) had average postharvest loss on the lower bracket. The

average postharvest loss of okra at local municipal retailer level was 11.3%. Cyril (2005)

reported a 4.64 % loss in okra at retailer level in Sri Lanka.

45

Table 11 Postharvest losses in okra at local municipal retailer level

Types of Losses


Range

Mean (%)

Lautoka Nadi Sigatoka Suva

Shape 1.8 (3) 1.2 (2) 1.0 (4) 1.7 (4) 1.0-1.8 1.4 b

Physical Abrasion 2.8 (5) 0.0 (0) 0.3 (1) 2.7 (6) 0.0-2.8 1.5 b

Senescence/Over-mature 3.6 (7) 10.9 (16) 9.0 (34) 3.5 (8) 3.5-10.9 6.7 a

Pest/Disease 1.9 (4) 1.2 (2) 1.0 (4) 2.7 (6) 1.0-2.7 1.7 b

Total Loss 10.2 (19) 13.2 (20) 11.3 (43) 10.5 (23) 10.2-13.2 11.3



There were no significant differences (P>0.05) in the percentage losses of okra between

the four local municipal retail outlets. This can be partially explained by the identical

prevailing trading and storage conditions at the four outlets.

At the local municipal retailer outlets, significantly (P<0.05) higher losses resulted from

over-maturity of the crop due to textural changes resulting in increased fibre content after

harvest (Nonnecke, 1989). The crop is stored at room temperature which favours high

physiological activity leading to faster respiration and deterioration of the crop. The

frequency of harvest also plays an important part in contributing to higher losses due to

over-maturity. Okra is harvested at 2-3 days interval, so before one crop is sold, fresh crop

arrives at the local municipal markets, resulting in higher rejection of the former crop.

46

4.2.1.3 Postharvest losses in okra at exporter strata level

A total of 500kg of okra from Exporter I, 2000kg from Exporter II and 100kg from

Exporter III were sampled. The postharvest losses at exporter level were also worked out

and have been presented in Table 12. It was found that types of highest average loss were

registered by shape (2.4%), followed by pest/disease (1.0%), physical abrasion (0.7%)

and senescence/over-mature (0.6%). The average loss at exporter level was registered as

4.7%.

Table 12 Postharvest losses in okra at exporter level

Types of Losses

Exporter Strata Range

Mean (%) Exporter I Exporter II Exporter III

Shape 1.8 (9) 2.5 (50) 3.0 (3) 1.8-3.0 2.4 a* Physical Abrasion 0.2 (1) 0.8 (15) 1.0 (1) 0.2-1.0 0.7 b Senescence/Over-mature 0.4 (2) 0.5 (10) 1.0 (1) 0.4-1.0 0.6 b Pest/Disease 0.6 (3) 1.3 (25) 1.0 (1) 0.6-1.3 1.0 b Total Loss 3.0 (15) 5.0 (100) 6.0 (6) 3.0-6.0 4.7 LSD (5% level) 0.4768


There were significant differences (P<0.05) between the three exporters for percentage

loss of okra. This can be attributed to okra being a non-bilateral quarantine agreement

(BQA) crop; hence, being subjected to a more flexible grading and handling criteria as

opposed to BQA crops, which follow a standard export protocol.

Rejection due to unacceptable shape (for export) was significantly higher (P<0.05) than

other types of losses. Shape is a critical index for the export criteria of okra. Since the crop

47

is a non BQA commodity, management practices are highly variable as no strict

guidelines are imposed.

4.2.2 End use of rejected okra at different levels

4.2.2.1 End use of rejected okra at production strata level

A perusal of Table 13 reveals that the end use of postharvest loss okra in different

production strata also varied in extent and nature. On the overall basis, the average

maximum end use in loss okra was ascertained as waste (6.9%), followed by domestic use

(4.6%).

Table 13 End use of rejected okra at production level

End use

Production Strata

Range

Mean

(%) Lower

Valley

Mid

Valley

Upper

Valley

Animal feed 0.0 (0) 0.0 (0) 0.0 (0) - 0.0

Domestic use 4.8 (18) 4.9 (14) 4.2 (13) 4.2-4.9 4.6

Waste 7.5 (29) 6.7 (19) 6.4 (20) 6.4-7.5 6.9

Total Loss 12.3 (47) 11.6 (32) 10.7 (34) 10.7-12.3 11.5


4.2.2.2 End use of rejected okra at local municipal retailer strata level

The comparison of end use of postharvest rejects okra between local municipal retail

outlets is presented in Table 14. Across different end uses, it is revealed that waste (9.4%)

also registered highest average postharvest loss end use, while domestic use (2.0%) had an

average postharvest loss end use on the lower bracket.

48

Table 14 End use of rejected okra at local municipal retailer level

End use


Range

Mean


Animal feed 0.0 (0) 0.0 (0) 0.0 (0) 0.0 (0) 0 0.0

Domestic use 3.8 (7) 0.5 (1) 1.1 (4) 2.3 (5) 0.5-3.8 2.0

Waste 6.3 (12) 12.7 (19) 10.2 (39) 8.2 (18) 6.3-12.7 9.4

Total Loss 10.2

(19)

13.2 (20) 11.3 (43) 10.5 (23) 10.2-13.2 11.3


4.2.2.3 End use of rejected okra at exporter strata level

The end uses of postharvest rejects of okra at exporter level were also worked out and

have been presented in Table 15. It was found that the only end use registered for okra at

exporter level was being returned to farmers (4.7%). This was because the exporters pay

premium price only for export quality okra and the rejects are returned to farmers.

Table 15 End use of rejected okra at exporter level

End use

Exporter Strata

Range

Mean

(%) Exporter I Exporter II Exporter III

Returned to farmers 3.0 (15) 5.0(100) 6.0 (6) 3.0-6.0 4.7

Domestic use 0.0 0.0 0.0 0 0.0

Waste (from HTFA) 0.0 0.0 0.0 0 0.0

Total Loss 3.0 (15) 5.0 (100) 6.0 (6) 3.0-6.0 4.7


49

4.2.3 Aggregate postharvest losses and end use of rejected okra

The aggregate postharvest loss in okra was calculated by ascertaining the losses at

production level, local municipal retailer level and exporter level. Figure 6 reveals that

postharvest losses were maximum at production level (11.5%) followed by local

municipal retailer level (11.3%) and minimum at exporter level (4.7%). Across different

types, it was found that maximum postharvest loss in okra was caused by

senescence/over-mature (9%) and shape (8.7%) followed by pest/disease (6.1%) and

physical abrasion (3.8%). The mean cumulative loss of 27.5% was ascertained for okra

along the postharvest chain. Cyril (2005) reported a total loss of 16.02 % in okra in Sri

Lanka.

The differences in findings may be due to different production environment and grading

criteria along the marketing and supply chain.

Figure 6 Overall postharvest losses in okra

0

5

10

15

20

25

30


Exporter Total Loss

Los

s (%

)

Different Levels Shape Physical Abrasion Senescence/Over-mature Pest/Disease

50

A read-through of Figure 7 reveals that the overall end use of rejected okra in different

production strata is wide-ranging in nature. On the overall basis, majority of the

postharvest rejected okra was ascertained as waste (16.3%), whereas 6.6% was

ascertained for domestic use. An ascertained 4.7% of loss okra that is returned to farmers

from the exporters can also be characterised as part of waste.

Figure 7 Overall end use of rejected okra

0

5

10

15

20

25

30


Exporter Total

End

Use

(%)

Different Levels

Domestic use Waste Return to Farmers

51

4.2.4 Non-trade loss vs. absolute loss of okra

The end use of rejected okra is further categorised into non-trade and absolute loss as

shown in figure 8. Out of the total okra rejects, 76% falls in the category of absolute loss

(waste and returned to farmers) and therefore, no monetary gain can be realised from it.

On the other hand, only 24% of the rejected okra fall under non-trade loss and has

monetary value attached to it in terms of domestic consumption.

Figure 8 Non-trade loss vs. absolute loss of okra

4.3 Tomato

The postharvest losses and end use of rejected tomatoes at different levels along the

postharvest chain have been presented in sub-sections 4.3.1 and 4.3.2 respectively and at

aggregate level these have been presented in sub-section 4.3.3. The total postharvest loss

is further categorised into non-trade loss and absolute loss in sub-section 4.3.4.

Absolute Loss 76%

Non-Traded Loss 24%

52

4.3.1 Postharvest losses in tomatoes at different levels

4.3.1.1 Postharvest losses in tomato at production strata level

A sample of 120kg, 635kg and 340kg from lower, mid and upper valley were taken. A

perusal of Table 16 reveals that the types of postharvest losses in different production

strata varied in extent and nature. Therefore, the extent of losses varied from strata to

strata as well as the types of postharvest losses. On the overall basis, the maximum loss in

tomato was ascertained in the lower valley (18%), followed by upper valley (15.5%) and

mid valley (10.4%). On studying the different types of losses, it was observed that the

maximum average loss was due to senescence/over-ripe (5.7%), followed by pest/disease

(5.0%) and physical abrasion (4.0%). The average postharvest loss of tomatoes at

production level was 14.6%. Cyril (2005) reported a 7.25 % loss in tomato at grower level

in Sri Lanka.

Table 16 Postharvest losses in tomatoes at production level

Types of Losses

Production Strata Range

Mean (%)

Lower Valley

Mid Valley

Upper Valley

Physical Abrasion 5.0 (6) 2.7 (17) 4.3 (15) 2.7-5.0 4.0 b*

Senescence/Over-ripe 7.3 (9) 4.3 (27) 5.4 (18) 4.3-7.3 5.7 a

Pest/Disease 5.8 (7) 3.4 (22) 5.8 (20) 3.4-5.8 5.0 ab

Total Loss 18.0 (22) 10.4 (66) 15.5 (53) 10.4-18 14.6

Mean (%) 6.0 a 3.5 c 5.2 b

LSD (5% level) 1.13 1.132 * Means followed by the same letter are not significantly different. ( ) Weight in kilograms

53

There were significant differences (P<0.05) in the percentage loss of tomato between the

three production strata. Lower valley has the highest postharvest loss in tomatoes since it

is a secondary crop as the farmers are primarily engaged with high value export crops

namely eggplant, chilli, okra and papaya. Tomato is entirely grown for the local markets

and therefore, receives less attention with no standard guidelines being followed.

However, the crop receives much higher attention in the mid and upper valley regions

where limited cultivation of export crops is practiced due to large distances from the

exporters who are based in the lower valley.

Over-ripeness and pest/disease infestation are main causes of losses in tomatoes. This can

be partially explained by the strong seasonality of the crop and negligence during peak

production times when prices are not lucrative. Un-uniform maturity and low volumes of

harvest also lead to higher losses due to over-ripening.

4.3.1.2 Postharvest losses in tomato at local municipal retailer strata level

A total of 107kg, 204kg, 218kg and 190kg of tomato were sampled from Lautoka, Nadi,

Sigatoka and Suva municipal markets respectively. The comparison of postharvest reject

losses in tomatoes between the local municipal retail outlets, presented in Table 17, reveal

that maximum loss was in Nadi (13.0%), followed by Lautoka (11.9%). The Suva and

Sigatoka municipal retailers registered the lowest postharvest losses of 10.7% and 9.1%,

respectively. Across different types, it was revealed that pest/disease (6.0%) registered

highest average postharvest losses, while senescence/over-mature (5.2%) had an average

postharvest loss on the lower bracket. The average postharvest loss of tomatoes at local

54

municipal retailer level was 11.2%. Cyril (2005) reported a 13.33 % loss in tomatoes at

retailer level in Sri Lanka.

Table 17 Postharvest losses in tomato at local municipal retailer level

Types of Losses Local Municipal Retailer Strata

Range Mean (%) Lautoka Nadi Sigatoka Suva

Senescence/Over-mature 5.7 (6) 6.8 (14) 3.8 (8) 4.6 (9) 3.8-6.8 5.2a*

Pest/Disease 6.2 (7) 6.3 (13) 5.3 (12) 6.1 (12) 5.3-6.3 6.0a

Total Loss 11.9 (13) 13.0 (27) 9.1 (20) 10.7 (20) 9.1-13.0 11.2



There were no significant differences (P>0.05) between the four local municipal retailer

outlets for percentage loss of tomato encountered during the marketing phase. This can be

partially explained by the identical prevailing trading and storage conditions at the four

outlets.

The types of losses in tomato at local municipal retailer outlets is mainly due to

senescence/overripe and infestation by pest and disease. Physical abrasion losses are

negligible as tomatoes with minor abrasion are accepted and traded to a point where it is

overripe and is not suitable for consumption.

4.3.2 End use of rejected tomatoes at different levels

4.3.2.1 End use of rejected tomato at production strata level

A perusal of Table 18 reveals that the end use of postharvest loss tomatoes in different

production strata also varied in nature. On the overall basis, the average maximum end use

55

of rejected tomato was ascertained as waste (9.8%), followed by domestic use (3.3%) and

animal feed (1.5%).

Table 18 End use of rejected tomatoes at production level End use

Production Strata Range

Mean (%)

Lower Valley

Mid Valley

Upper Valley

Animal feed 0.7 (1) 3.1 (19) 0.8 (3) 0.7-3.1 1.5 Domestic use 5.3 (6) 2.3 (14) 2.4 (8) 2.3-5.3 3.3 Waste 12.0 (14) 5.0 (32) 12.3 (42) 5.0-12.3 9.8 Total Loss 18.0 (22) 10.4 (66) 15.5 (53) 10.4-18 14.6 ( ) Weight in kilograms

4.3.2.2 End use of rejected tomato at local municipal retailer strata level

The comparison of end use of postharvest rejected tomatoes between the local municipal

retail outlets is presented in Table 19. Across different end uses, it is revealed that waste

(8.5%) also registered highest average postharvest loss end use, while domestic use

(2.7%) had an average postharvest loss end use on the lower bracket and animal feed had

0% end use.

Table 19 End use of rejected tomatoes at local municipal retailer level End use

Local Municipal Retailer Strata Range

Mean (%) Lautoka Nadi Sigatoka Suva

Animal feed 0.0 0.0 0.0 0.0 0 0.0 Domestic use 2.6 (3) 1.1 (2) 4.1 (9) 2.9 (5) 1.1-4.1 2.7 Waste 9.3 (10) 11.9 (24) 5.1 (11) 7.8 (15) 5.1-11.9 8.5 Total Loss 11.9 (13) 13.0 (27) 9.1 (20) 10.7 (20) 9.1-13.0 11.2 ( ) Weight in kilograms

4.3.3 Aggregate postharvest losses and end use of rejected tomatoes

The aggregate postharvest losses in tomatoes were calculated by taking together the losses

at production level and local municipal retailer level. Figure 9 reveals that postharvest

56

losses was highest at production level (14.6%) and followed by local municipal retailer

level (11.2%). Across different types, it was found that maximum postharvest loss in

tomato was caused by pest/disease (11%) and senescence/over-mature (10.9%) whereas

physical abrasion had only 4% loss. An aggregate average postharvest loss of 25.8% was

ascertained for tomatoes along the postharvest chain. Cyril (2005) reported a total loss of

35.42 % in tomatoes in Sri Lanka. Mangaoang (1982) reported a total postharvest loss of

24 % in tomatoes in Philippines.

Figure 9 Overall postharvest losses in tomatoes

0

5

10

15

20

25

30

Production Local Municipal Retailer Total Loss

Los

s (%

)

Different Levels

Physical Abrasion Senescence/Over-mature Pest/Disease

57

A read-through of Figure 10 reveals that the overall end use of rejected tomatoes in

different production strata is wide-ranging in nature. On the overall basis, majority of the

postharvest loss tomatoes was ascertained as waste (18.3%), whereas 6.0% and 1.5% was

ascertained for domestic use and animal feed, respectively.

Figure 10 Overall end use of rejected tomatoes

0

5

10

15

20

25

30

Production Local Municipal Retailer Total

End

Use

(%)

Different Levels

Animal Feed Domestic use Waste

58

4.3.4 Non-trade loss vs. absolute loss of Tomatoes

The end use of rejected tomato is further categorised into non-trade loss and absolute loss

as shown in Figure 11. Out of the total tomato rejects, 71% falls in the category of absolute

loss (waste) and therefore, no monetary gain can be realised from it. On the other hand,

only 29% of the rejected tomatoes fall under non-trade loss and has monetary value

attached to it in terms of domestic consumption and animal feed.

Figure 11 Non-trade loss vs. absolute loss of tomatoes

Absolute Loss 71%

Non-Traded Loss 29%

59

4.4 Five Hundred (500) Observed Tomatoes

The postharvest loss of 500 tomatoes from each of the three production strata was also

observed after harvest at every four day intervals for 12 days to ascertain the actual

postharvest losses. The results are presented in Table 20 below.

Table 20 Losses in 500 Tomatoes observed at four (4) day intervals

Production Strata

Types of Losses

Time Total (%)

Day 4 Day 8 Day 12 Lower Valley

Senescence/ Overripe

6.0 2.0 2.0 10.0

Pest/Disease 8.0 6.0 12.0 26.0

Physical Abrasion

6.0 6.0 0.0 12.0

Green/Unripe 0.0 0.0 12.0 12.0

Total (%) 20.0 14.0 26.0 60.0

Mid Valley


4.0 2.0 12.0 18.0

Pest/Disease 4.0 6.0 4.0 14

Physical Abrasion

2.0 6.0 0.0 8

Green/Unripe 0.0 0.0 0.0 0

Total (%) 10.0 14.0 16.0 40

Upper Valley


6.0 2.0 0.0 8.0

Pest/Disease 6.0 6.0 2.0 14.0

Physical Abrasion

4.0 6.0 0.0 10.0

Green/Unripe 0.0 0.0 10.0 10.0

Total (%) 16.0 14.0 12.0 42.0

Mean Loss (%) 15.3 14.0 18.0 47.3

60

A perusal of Table 20 reveals that the extent of actual losses in the 500 observed tomatoes

varied between production strata as well as the types of postharvest losses. On the overall

basis, the maximum loss in tomato after 4 days was ascertained in the lower valley (20%),

followed by upper valley (16%) and mid valley (10%). On studying the different types of

losses, it was observed that the maximum average loss was due to pest/disease (6.0%),

followed by senescence/over-mature (5.3%) and physical abrasion (4.0%). The average

actual postharvest loss of tomatoes after four (4) days was 15.3%.

The result of postharvest losses in tomatoes after eight (8) days, reveal that losses were the

same (14%) in the three strata. Across different types, it was revealed that pest/disease

(6.0%) and physical abrasion (6%) registered highest average postharvest losses, while

senescence/over-mature (2.0%) had an average postharvest loss on the lower bracket. The

average actual postharvest loss of tomatoes after eight (8) days was 14%.

The postharvest losses after 12 days were also worked out and it was found that the lower

valley had maximum loss (26%) in tomato, followed by mid-valley (16%) and upper

valley (12%). It was ascertained that even after 12 days, on average, 7.3% of tomatoes

were still green. Other average losses were registered by pest/disease (6.0%) and

senescence/over-mature (4.7%). The average loss in tomatoes after 12 days was registered

as 18%.

This was a very interesting data obtained about perceived and actual postharvest loss,

which is challenging the traditional view that Fiji farmers are often poorly connected with

market-based postharvest losses. The actual postharvest loss in tomatoes observed after

61

four days was 15.3% (Table 20) and the ascertained postharvest loss in tomato at

production level was 14.6% (Table 16). This proves that the farmers have a fair idea on the

percentage loss of vegetables at production level.

4.5 Postharvest Operations

The basic postharvest operations carried in the vegetable postharvest chain are briefly

discussed below.

4.5.1 Harvesting

Serious quantitative postharvest losses and quality deterioration of vegetables occur due

to adoption of improper postharvest practices at the production level. Such observed

practices are harvesting at incorrect stage of maturity and adoption of improper handling

and packaging methods. At present, harvesting is carried out manually.

4.5.2 Sorting and Grading

In Sigatoka, majority of farmers and exporters market their produce after sorting and

grading. At present, sorting and grading are carried out manually as per the Bilateral

Quarantine Agreement (Appendix 4).

4.5.3 Handling and Transportation

Vegetables are often packed tightly by forcing in polypropylene sacks. The fruits and

vegetables packed in poly-sacks are usually transported in open trucks. This provides the

possibilities to exposure of fresh produce to sun or rain. Because of high transportation

cost, the middleman generally tends to transport the maximum amount possible. Thus,

produce is often bruised, infested by postharvest pathogens and is not of optimum quality

on reaching distribution points.

62

CHAPTER 5

SUMMARY, CONCLUSIONS AND POLICY IMPLICATIONS

The flow diagram summarizing the market stages and percentage losses in eggplants

(Figure 12), okra (Figure 13) and tomato (Figure 14) from farmers’ field to consumer is

shown below. If the supply chain is long, the total postharvest loss will also increase

because of transportation and storage of vegetables in the process.

Figure 12 Flow network and losses of eggplant from farmers’ fields to consumers

Harvesting

(100%)

Exporter

(45.3%)

Exported

(40.2%)

Loss at Exporter Level

(5.1%)

Local Municipal Retailer

(39.7%)

Consumers

Eggplant (27%)

Loss at Local Municipal Retailer

Level

(12.7%)

Loss at Production

Level

(15%)

63

Figure 13 Flow network and losses of okra from farmers’ fields to consumers

Harvesting

(100%)

Exporter

(59.6%)

Exported

(54.9%)

Loss at Exporter Level

(4.7%)


(28.9%)

Consumers

(17.6%)

Loss at Local Municipal Retailer

Level

(11.3%)

Loss at Production Level

(11.5%)

64

Figure 14 Flow network and losses of tomato from farmers’ fields to consumers

Harvesting

(100%)


(85.4%)

Consumers

(74.2%)

Loss

(11.2%)

Loss at Production Level

(14.6%)

65

A very interesting data was also obtained about perceived and actual postharvest loss,

which is challenging the traditional view that Fiji farmers are often poorly connected with

market-based postharvest losses. The actual postharvest loss in tomatoes observed after

four days was 15.3% (Figure 15) and the ascertained postharvest loss in tomato at

production level was 14.6% (Figure 14). The study by Underhill (2013) on tomatoes in

Fiji is similar to the results of this work. This proves that the farmers have a fair idea on

the percentage loss of vegetables at production level.

Tomatoes 15.3% Loss 14.0% Loss 18% Loss Harvested Stored at Projected further Projected further from field farmers’ home loss if not consumed loss if not consumed

Figure 15 Projected loss of tomatoes over a storage period of 12 days under farmer’s

conditions.

The aggregate postharvest losses in sample vegetables were calculated by taking together

the losses at production level, local municipal retailer level and exporter level. Table 21

reveals that postharvest losses were maximum in eggplant (32.8%), followed by okra

(27.5%) and tomato (25.8%). Across different levels, it was found that the losses were

highest at the grower level in all the vegetables.

The study has ascertained postharvest losses in three major vegetables grown in Sigatoka

Valley, Fiji. At production level, the postharvest losses have been found maximum in

eggplant (15%) followed by tomato (14.6%) and minimum in okra (11.5%). At the local

Day 0 Day 4 Day 8 Day 12

66

municipal retailer level also, eggplant has registered maximum loss, followed by okra and

tomato. Across different stages, the losses have been found to be highest at the production

level in all the vegetables.

Table 21 Summary of total postharvest losses in selected vegetables

Vegetable

Losses at different levels (%)

Range

Total (%) Production Local Municipal

Retailer

Exporter

Eggplant 15.0 12.7 5.1 25.2 - 40.4 32.8

Okra 11.5 11.3 4.7 23.9 – 31.5 27.5

Tomato 14.6 11.2 - 19.5 – 31.0 25.8

Table 22 shows that the postharvest loss caused by shape was relatively similar i.e. 7.8%

and 8.7% for eggplant and okra respectively. Losses due to physical abrasion was quite

high (10.5%) in eggplant whereas okra and tomato were in the lower bracket of 3.8% and

4% respectively. Percentage loss caused by senescence/overripe ranged from 8.8 to 10.9

for the three crops and loss caused by pest/disease was very high in tomato 11% whereas

eggplant and okra were in the lower bracket of 5.9 and 6.1 per cent respectively.

Table 22 Summary of types of postharvest losses in selected vegetables

Types of Losses

% Loss

Eggplant Okra Tomato

Shape 7.8 8.7 0

Physical Abrasion 10.5 3.8 4

Senescence/Overripe 8.8 9 10.9

Pest/Disease 5.9 6.1 11

Total 32.8 27.6 25.8

67

The reject loss of vegetables across the postharvest chain is thought to result from lack of

knowledge about proper postharvest management. Improper grading, packing, lack of

storage and inadequate transportation facilities contribute more to the problem. One of the

most important types of postharvest losses is harvest at inappropriate maturity, resulting

in erratic ripening and poor quality.

Based on the findings of this study, the following recommendations are made for policy

actions to reduce the postharvest losses in vegetables.

1) Provision of appropriate storage facilities, such as holding areas with adequate

ventilation, low temperatures, to store the produce at production level and also at

local municipal retailer level to reduce the losses that occur.

2) Training initiatives for the vegetable growers and local municipal retailers on

scientific postharvest techniques should be encouraged and follow ups, feedback

and adoption measurement should be conducted periodically for sustainability.

3) Roads linking farms to market should be improved to reduce physical abrasion.

4) Establishment of producer co-operatives to handle various activities relating to

production and marketing of vegetables. This will not only help reduce the

postharvest losses but will also increase the bargaining power of growers in

marketing. It will help them in adopting consumer-oriented approach to vegetable

marketing.

68

5) Promoting packaging methods and transportation – a national level project to

distribute plastic crates and to modify transportation vehicles on a subsidised rate

for the reduction of postharvest losses in vegetables.

6) Establishment of cottage industries such as vacuum packing, drying or canning of

vegetables should be encouraged.

7) Enhancing research capabilities of institutions engaged in postharvest research

and development activities.

A number of deficiencies currently exist in the postharvest management and processing of

vegetables in Fiji. Action must be taken in order to upgrade systems, in order to reduce the

levels of postharvest losses in Fiji. In a civilised world, when millions go hungry, it would

be a crime to allow postharvest losses to continue. It is unfortunate that in Fiji, policy

makers and planners set targets for increased production without making any effort to

reduce postharvest losses.

Expenditure on crop production is required on an annual basis, while the establishment of

infrastructural facilities for postharvest operations is a onetime capital investment which

must be undertaken and compensated for by the annual savings from reducing postharvest

losses. Proper infrastructure, logistics and management and human resources are essential

to improving postharvest management and marketing of fruits and vegetables.

69

It is not possible to survive in this era of globalisation by employing traditional farming

techniques only. Geographically, Fiji is a small country with limited land resources. The

availability of cultivable land is decreasing proportionately with increasing population.

The country must therefore increase its productivity, diversify its agricultural production

base and increase value addition through the processing of farm products.

Efforts must be made to strengthen the postharvest sector through intensive investment in

research and development. The food industry must focus on the production of quality

products for both the domestic and export markets. The economy of the country will be

strengthened through quality improvement, increased production, increased market share

and greater foreign exchange earnings derived from increased export of fresh and

processed fruits and vegetables.

70

REFERENCES

Abbott, J. A. (1999). Quality measurement of fruits and vegetables. Postharvest Biology

and Technology, 15(3), 207-225. Agra-Business and Trade Promotion Multi-Purpose Co-operative (ABTRACO, 2003). A

Summary of the Findings and Recommendations of the Study on Promotion of Marketing of Selected High Value Agricultural Commodities to Bangladesh and Tibet Markets, Anam Nagar, Kathmandu.

Agriculture Fiji (Online). Available at: http://www.un.org/esa/agenda21/natlinfo/countr/fiji/agriculture.pdf (Accessed, September 20, 2012)

Ahsan, H. (2005). India Country Paper. In: Proceedings of the APO seminar on Marketing and Food Safety: Challenges in Postharvest Management of Agricultural/ Horticultural Products in Islamic Republic of Iran, 23–28 July 2005, Asian Productivity Organization, 2006, Pp 131-134.

Anjum, M. I., Awan, I. A. (2005). Pakistan Country Paper. In: Proceedings of the APO

seminar on Marketing and Food Safety: Challenges in Postharvest Management of Agricultural/ Horticultural Products in Islamic Republic of Iran, 23–28 July 2005, Asian Productivity Organization, 2006, Pp 209-211.

Bajracharya, A. 2000. An Overview of Postharvest Handling Activities in MARD Project Areas. Budiastra I.W and H.K Purwadaria. (1995). Post Harvest Handling of Vegetable and Fruit

in Packing House. Training Material on Postharvest of Fruits and Vegetables, Bogor. (In Indonesian)

Castro, L. R., Vigneault, C., Charles, M. T. & Cortez, L. A. (2005). Effect of cooling delay and cold-chain breakage on ‘Santa Clara’ tomato. Journal of Food Agriculture and Environment, 3, 49-54.

Choudhury, M. L. (2004). Recent Developments in Reducing Postharvest Losses in the Asia Pacific Region. In: Proceedings of the APO seminar on Reduction of Postharvest Losses of Fruit and Vegetables, held in India, 5–11 October 2004, Asian Productivity Organization, 2006, Pp 15 - 22.

Cyril, S. D. P. (2004). Sri Lanka Country Paper. In: Proceedings of the APO seminar on

Reduction of Postharvest Losses of Fruit and Vegetables, held in India, 5–11 October 2004, Asian Productivity Organization, 2006, Pp 252-255.

De Lucia, M. & Assennato, D. (1994). Agricultural engineering in development: postharvest operations and management of food grains (Publication. Retrieved

71

August 25, 2012, from FAO: http://www.fao.org/inpho/pp-dr/pp-arch/full-doc/frame-e.htm)

Doza, A. F. B. (2005). Bangladesh Country Paper. In: Proceedings of the APO seminar on Marketing and Food Safety: Challenges in Postharvest Management of Agricultural/ Horticultural Products in Islamic Republic of Iran, 23–28 July 2005, Asian Productivity Organization, 2006, Pp 105-108.

FAO. World Hunger Statistics, (2010), Available at: http://www.fao.org (Accessed, March 25, 2013)

FAO. (2011). Global Food Losses and Waste. Extent, Causes and Prevention. (available at http://www.fao.org/docrep/014/mbo6oe/mbo6oeoo.pdf)

FAO. (2006, 30 January – 3 February). Enhancing the Competitiveness of Agriculture and Natural Resource Management under Globalisation and Liberalisation to Promote Economic Growth. Paper presented at the Twenty-Fourth Regional Conference for Africa, Bamako, Mali.

Gajana, T.M., Murthy, D. Sreenivasa, Sudha, M. And Dakshinamoorty, V. (2006), Marketing and estimation of postharvest losses of crop in Karnataka. Indian Journal of Agricultural Marketing, 20 (1): 1-7.

Getinet, H., Seyoum, T. & Woldetsadik, k. (2008). The effect of cultivar, maturity stage and storage environment on quality of tomatoes. Journal of Food Engineering, 87(4), 467-478.

Google earth. (2012). Fiji (Online). Available at: http://www.googleearth.com/Fiji (Accessed, October 01, 2012)

Google. (2013). Map of Fiji (Online). Available at: http://www.fijimaps.com/ (Accessed, March 10, 2013)

Haryanto, B., Rochani, A. (2004). Indonesia Country Paper. In: Proceedings of the APO seminar on Reduction of Postharvest Losses of Fruit and Vegetables, held in India, 5–11 October 2004, Asian Productivity Organization, 2006, Pp 158-161.

HMG/N and ADB/N, (1991). Master Plan for Horticulture Development. Nepal. Kaini, B. R. (2000). Country Paper on Postharvest Techniques for Horticultural Crops in

Nepal, In Report of the APO Seminar on appropriate Technologies for Horticultural Crops, held in Bangkok from 5–9 July 1999. Asian Productivity Organization, 2000, pp11– 218.

Karim, A. and Wee, M.M.B. (1996) Reducing post harvest losses in vegetables. In:

Proceedings of Workshop on Vegetable Crops Agribusiness, held at BARC, Farm Gate, Dhaka. 2-4 May.

72

Kumar, D. K, Basavaraja, H. and Mahajanshetti, S. B. (2006). An economic analysis of

postharvest losses in vegetables in Karnataka. Indian Journal of Agricultural Economics, 61 (1): 134-146.

Kumar, V. (2004). Fiji Country Paper. In: Proceedings of the APO seminar on Reduction

of Postharvest Losses of Fruit and Vegetables, held in India, 5–11 October 2004, Asian Productivity Organization, 2006, Pp 123 - 128.

La Gra, Jerry (1990). A Commodity System Assessment Methodology for Problem and Project Identification. Moscow, Idaho: University of Idaho, College of Agriculture, Postharvest Institute for Perishables.

Liu, F.W. (1999). Post harvest handling in Asia 2. Horticultural crops. Food and Fertilizer Technology Center, Taipei, Taiwan.

Lizada, MCC. (1990). Postharvest Losses in and Loss Assessment Methods for Fruits,

Vegetables and Cutflowers. Paper presented during the Forum – Workshop on Postharvest Losses and Loss Assessment Methods, 21 May 1990. DA-ATI Conference Room, Quezon City.

MAF-BAEcon. (1985). Statistical Handbook in Agriculture. Statistical Handbook No. 1. Mangaoang, C.C. (1982). Losses of selected fruits and vegetables. Report: Research

Division, Technical Research and Extension Directorate, National Food Authority, Quezon City.

Mao, M. (2004). Cambodia Country Paper. In: Proceedings of the APO seminar on


Marketing Development Division (MDD, 1999/2000). Marketing System Including

Packaging of Apple from Jumla, Harihar Bhawan, Lalitpur. Moghaddasi, R., Elaheh, M., Shariati, S. (2005). Islamic Republic of Iran Country Paper.

In: Proceedings of the APO seminar on Marketing and Food Safety: Challenges in Postharvest Management of Agricultural/ Horticultural Products in Islamic Republic of Iran, 23–28 July 2005, Asian Productivity Organization, 2006, Pp 164-168.

MPI (2010), Annual Report, Ministry of Primary Industries, Government of Fiji.

Nonnecke I. L. (1989). Vegetable Production, New York. Van Nostrand Reinhold publishers.

73

Pantastico, Er.B. (1979). Postharvest losses of fruits and vegetables in developing countries – An action program. Paper delivered during the SEARCA Professorial Chair Lecture held at PHTRC, 23 October 1979.

Paudel, K. B. (2004). Nepal Country Paper. In: Proceedings of the APO seminar on


Paull, R. E. (1999). Effect of temperature and relative humidity on fresh commodity quality. Postharvest Biology and Technology, 15(3), 263-277.

Rapusas, R. S. (2004). Philippine Country Paper (2). In: Proceedings of the APO seminar on Reduction of Postharvest Losses of Fruit and Vegetables, held in India, 5–11 October 2004, Asian Productivity Organization, 2006, Pp 227-239.

Rolle, R. S. (2004). Improving Postharvest Management and Marketing in the Asia

Pacific Region: Issues and Challenges. In: Proceedings of the APO seminar on Reduction of Postharvest Losses of Fruit and Vegetables, held in India, 5–11 October 2004, Asian Productivity Organization, 2006, Pp 23 - 26.

Sharma, G., and Singh, S. P. (2011), Economic analysis of postharvest losses in marketing

of vegetables in Uttarakhand. Agricultural Economics Research Review, vol. 24 July-December 2011: 309-315.

Sharma, N.K., (2001/2002). Vegetable and Fruit Postharvest Technology. India.

Serrano, E. P. (2004). Philippine Country Paper (1). In: Proceedings of the APO seminar on Reduction of Postharvest Losses of Fruit and Vegetables, held in India, 5–11 October 2004, Asian Productivity Organization, 2006, Pp 215-217.

Setiajit, Dimyati, Ahmad and Sinung Basuki, Rofik 2003. Vertical and Horizontal

Integration for National Horticulture Products Marketing. Sirivatanapa, S. (2004). Packaging and Transportation of Fruits and Vegetables for better

Marketing. In: Proceedings of the APO seminar on Reduction of Postharvest Losses of Fruit and Vegetables, held in India, 5–11 October 2004, Asian Productivity Organization, 2006, Pp 43-48.

Thapa, M.J. and M.B. Shrestha, (2001/02). Study on Grading, Packaging and

Transportation of Orange. In Annual Report, Food Research Unit (Postharvest Research Programme). Nepal Agriculture Research Council, Khumaltar, Lalitpur, Nepal.

74

Tridjaya, N. O. (2005). Growing Fruit Processing Centers to Stimulate Quality Improvement and Value Added. Technical Meeting of Horticulture Mechanization. Agricultural Research and Development Agency. Jakarta. (In Indonesian)

Underhill, S. J. R. (2013). Postharvest horticultural losses along a commercial tomato

supply chain in Fiji. Pacific Agricultural Research for Development Initiative (PARDI).

United States Department of Agriculture –USDA (1963), Agricultural Handbook No. 8.

Van Dijk, C. & Tijskens, L. M. M. (2000). Mathematical modeling of enzymatic reactions as related to texture after storage and mild preheat treatment: In S. M. Alzamora, M. S. Tapia, & A. Lopez-Malo (Eds.), Minimally processed fruits and vegetables. Maryland, USA: Aspen Publishers.

Verma, L. R. and Joshi, V. K. (2000). Post Harvest Technology of Fruits and Vegetables. An Overview. In: Post Harvest Technology of Fruits and Vegetables. 1:68.

Werner, R.A. and Subedi D.K., 1991. Postharvest Losses Assessment in Selected

Vegetables in Nepal: Tomato, Cabbage, and Cauliflower. FAO-VDD/DOH-GCP/NEP/046/SWI, Kathmandu, Nepal.

Wikipedia. (2012). Fiji (Online). Available at: http://en.wikipedia.org/wiki/Fiji (Accessed, August 25, 2012)

Wills R., McGlasson B., Graham D., & Joyce D. (1998). Postharvest: An Introduction to the Physiology & Handling of Fruit, Vegetables & Ornamentals. Fourth edition.CAB International.

Yeshida, O., Nakagaua, H., Ogura, N. & Sato. (1984). Effect of heat treatment on the development of polygalacturonase activity in tomato fruit ripening. Plant Cell Physiology, 25(3), 500-509.

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APPENDICES

Appendix 1

Questionnaire and Data Collection Sheet

PRODUCTION LEVEL

A. PERSONAL DETAILS

1. Name: __________________________________________

2. Location: ________________________________________

3. Occupation: ______________________________________

4. What is your age? (Please tick only one):

i. Less than 18 years

ii. Between 18 and 25 years

iii. Between 26 and 35 years

iv. Between 36 and 45 years

v. Between 46 and 55 years

vi. More than 55 years

5. Gender (Please tick only one):

Male Female

6. Marital Status (Please tick only one):

Single Married Widowed Divorced

7. What is your Education Level? (Please tick only one):

i. No Education Level

ii. Primary School

iii. Secondary School

iv. Post-Secondary/University

v. Others

76

(Please specify: ........................................................................................

..............................................................................................................)

8. Number of members in your Family (Please write the numbers):

Adults Children

(18+ Years) (Less than 18 Years)

B. FARM DETAILS

9. Land Tenure (More than one tick is allowed):

Native Crown Freehold Others

(Please specify): ____________________

10. What is the total land area? (Please tick only one):

i. Less than 5 acres

ii. Between 5 and 10 acres

iii. Between 10 and 15 acres

iv. Between 15 and 20 acres

v. Between 20 and 25 acres

vi. Between 25 and 30 acres

vii. More than 30 acres

11. How many years in vegetable farming?

............................................................

12. What is the total area under respective vegetable cultivation? (Please write area in acres)

i. Eggplant

ii. Tomato

iii. Okra

77

13. What are some of the Problems faced by farmer? (Please tick)

a. Far off location of selling point

b. Transport facility (i) Inadequate (ii) Costly

c. Lack of Market Information

d. Malpractices of buyers

e. Lack of grading facility

f. Lack of packing facility

g. Lack of storage facility

h. Lack of cold shelf facility

i. Lack of financial assistance from any company or Government.

j. Delay in payment and sale proceeds

k. Others specify

…………………………………………………………………………………

…………………………………………………………………………………

…………………………………………………………………………………

…………………………………………………………………………………

14. What does your Marketing Agent tell you about your crop (i.e.any feedback on

postharvest quality)?

……………………………………………………………………………………

……………………………………………………………………………………

……………………………………………………………………………………

……………………………………………………………………………………

15. What are some suggestions for improvement?

……………………………………………………………………………………………

……………………………………………………………………………………………

……………………………………………………………………………………………

……………………………………………………………………………………………

……………………………………………………………………………………………

78

A. PRODUCTION

LEVEL

Egg Plant Tomato Okra

Wt (kg) Wt (kg) Wt (kg)

Total Harvested

Losses due to:

Shape

Physical Abrasion

Senescence/Overripe

Pest/Disease

Total Loss

Type of Packing Material

Time of Harvesting

Time Transported to Market

Selling Price ($)

Transportation Type

Distance Transported

End Use of Rejected

Crops

Animal Feed

Domestic Use

Waste

79

Appendix 2


EXPORTER LEVEL

A. PERSONAL DETAILS

1. Name: __________________________________________

2. Location: ________________________________________

3. Occupation: ______________________________________

4. How many years in export business? __________________









Male Female



80


i. No Education Level

ii. Primary School

iii. Secondary School

iv. Post-Secondary/University

v. Others

(Please specify: ........................................................................................

..............................................................................................................)


Adults Children


81

B. EXPORTER

LEVEL



Total Received

Losses due to:

Shape

Physical Abrasion

Senescence/Overripe

Pest/Disease

Total Loss

Type of Packing Material

Time Transported to Packing shed

Selling Price ($)

Transportation Type

Distance Transported

End Use of Rejected Crops

Animal Feed

Domestic Use

Waste

82

Appendix 3


RETAILER LEVEL

A. PERSONAL DETAILS

1. Name: __________________________________________

2. Location: ________________________________________

3. Occupation: ______________________________________

4. How many years in retailing business? _________________









Male Female



83


vi. No Education Level

vii. Primary School

viii. Secondary School

ix. Post-Secondary/University

x. Others

(Please specify: ........................................................................................

..............................................................................................................)


Adults Children


84

C. RETAILER

LEVEL



Total Purchased

Losses due to:

Shape

Physical Abrasion

Senescence/Overripe

Pest/Disease

Total Loss

Type of Storage Material

Selling Price ($)

End Use of Rejected Crops

Animal Feed

Domestic Use

Waste

85

Appendix 4

THE FIJI QUARANTINE PATHWAY

Bilateral Quarantine Agreement (BQA)

Following establishment of the High Temperature Forced Air (HTFA) treatment, a

Bilateral Quarantine Agreement (BQA) was signed by NZMAF. This agreement

necessitates that Fiji facilitate technical requirements of pest risk management in

accordance with requirements of the importing country. As a follow up to the establishment

of this BQA, an export pathway for fruits and vegetable destined for export to New Zealand

was developed.

Grower and Site Registration Growers who produce eggplants for export to New Zealand

are required to sign a declaration. These growers and their production sites are

subsequently registered by the Fijian Ministry of Agriculture, who provides them with a

grower number. Grower and exporter records are subsequently retained by the Extension

and Quarantine Division of the Ministry of Agriculture.

Field Control Measures

Field Hygiene Growers ensure that eggplants and other fruit fly hosts, crops that are ripe,

overripe (not needed for use), and that have fallen in the field, or discarded during

harvesting, are removed from the registered site and surrounding area and disposed off in

the proper manner.

86

Harvest Growers only harvest eggplants for export to New Zealand from the registered

sites. Only sound eggplants are harvested using proper techniques. Harvested eggplants are

taken to the exporter’s pack house for grading in well-secured grower numbered bins.

Exporter/Pack house All export pack houses are registered and licensed by Fiji’s

Agriculture Quarantine Division.

Grading and Selection Pack houses maintain daily records of growers who supply

eggplants for packing. All eggplants (100%) supplied by growers for export to New

Zealand are inspected for the presence of fruit fly eggs, larvae and pupa and for symptoms

of their presence. Eggplants which are bruised or which contain soft-spots, skin punctures,

stings, infestation from other quarantine pests, and decay are rejected for export to New

Zealand. All records are maintained by the exporter and made available for inspection to

the Fiji Agriculture Quarantine Division.

Inspection Procedures Staff of the Quarantine section of the Ministry of Agriculture

undertakes thorough inspection of eggplants supplied on a grower basis after the pack

house staff have completed their inspection and grading. Eggplants with bruises, soft spots,

skin punctures, stings, infections and infestation by pests, signs of decay and suspect fruits

are rejected. The exporter ensures that the eggplants are transferred promptly to the High

Temperature Forced Air Chamber with a complete transfer slip/form. Fruit fly surveillance

and monitoring is carried out in the production area.

87

Treatment Facility/Quarantine Inspection & Post Treatment Security Eggplants graded by

HTFA staff are further inspected by Agriculture Quarantine staff, following which they are

treated in the chamber in accordance with the Quarantine Procedures Manual for the

operation of the chamber.

Phytosanitary Certificate On completion of the treatment a further inspection is carried out

prior to the issuance of an International Phytosanitary Certificate.

(Source: Ministry of Agriculture Sugar and Land Resettlement, “Fiji commodity pathway procedures for New Zealand”, Technical paper, Fiji.)

88

Appendix 5

Analysis of variance for % losses of eggplant at farmer level

Variate: %_Loss Source of variation d.f. s.s. m.s. v.r. F pr. strata stratum 2 5.2467 2.6233 4.69 strata.*Units* stratum loss_type 3 1.2492 0.4164 0.75 0.563 Residual 6 3.3533 0.5589 Total 11 9.8492 Tables of means Variate: %_Loss Grand mean 3.76 loss_type 1 2 3 4 4.23 3.53 3.40 3.87 Standard errors of means Table loss_type rep. 3 d.f. 6 e.s.e. 0.432 Standard errors of differences of means Table loss_type rep. 3 d.f. 6 s.e.d. 0.610 Least significant differences of means (5% level) Table loss_type rep. 3 d.f. 6 l.s.d. 1.494

89

Appendix 6

Analysis of variance for % losses of eggplant at retailer level

Variate: %_Loss Source of variation d.f. s.s. m.s. v.r. F pr. strata stratum 3 4.452 1.484 0.82 strata.*Units* stratum loss_type 3 55.962 18.654 10.25 0.003 Residual 9 16.383 1.820 Total 15 76.797 Message: the following units have large residuals. strata 3 *units* 3 2.06 Tables of means Variate: %_Loss Grand mean 3.19 loss_type 1 2 3 4 1.20 5.40 4.67 1.47 Standard errors of means Table loss_type rep. 4 d.f. 9 e.s.e. 0.675 Standard errors of differences of means Table loss_type rep. 4 d.f. 9 s.e.d. 0.954 Least significant differences of means (5% level) Table loss_type rep. 4 d.f. 9 l.s.d. 2.158

90

Appendix 7

Analysis of variance for % losses of eggplant at exporter level

Variate: %_Loss Source of variation d.f. s.s. m.s. v.r. F pr. strata stratum 2 2.3450 1.1725 4.05 strata.*Units* stratum loss_type 3 6.9625 2.3208 8.03 0.016 Residual 6 1.7350 0.2892 Total 11 11.0425 Tables of means Variate: %_Loss Grand mean 1.28 loss_type 1 2 3 4 2.37 1.60 0.67 0.47 Standard errors of means Table loss_type rep. 3 d.f. 6 e.s.e. 0.310 Standard errors of differences of means Table loss_type rep. 3 d.f. 6 s.e.d. 0.439 Least significant differences of means (5% level) Table loss_type rep. 3 d.f. 6 l.s.d. 1.074

91

Appendix 8

Analysis of variance for % losses of okra at farmer level

Variate: %_Loss Source of variation d.f. s.s. m.s. v.r. F pr. strata stratum 2 0.4117 0.2058 0.32 strata.*Units* stratum loss_type 3 22.7092 7.5697 11.86 0.006 Residual 6 3.8283 0.6381 Total 11 26.9492 Message: the following units have large residuals. strata 1 *units* 2 -1.18 s.e. 0.56 Tables of means Variate: %_Loss Grand mean 2.89 loss_type 1 2 3 4 4.93 1.57 1.70 3.37 Standard errors of means Table loss_type rep. 3 d.f. 6 e.s.e. 0.461 Standard errors of differences of means Table loss_type rep. 3 d.f. 6 s.e.d. 0.652 Least significant differences of means (5% level) Table loss_type rep. 3 d.f. 6 l.s.d. 1.596

92

Appendix 9

Analysis of variance for % losses of okra at retailer level

Variate: %_Loss Source of variation d.f. s.s. m.s. v.r. F pr. strata stratum 3 1.482 0.494 0.09 strata.*Units* stratum loss_type 3 82.087 27.362 4.89 0.028 Residual 9 50.326 5.592 Total 15 133.894 Message: the following units have large residuals. strata 2 *units* 3 3.66 s.e. 1.77 Tables of means Variate: %_Loss Grand mean 2.83 loss_type 1 2 3 4 1.43 1.45 6.75 1.70 Standard errors of means Table loss_type rep. 4 d.f. 9 e.s.e. 1.182 Standard errors of differences of means Table loss_type rep. 4 d.f. 9 s.e.d. 1.672 Least significant differences of means (5% level) Table loss_type rep. 4 d.f. 9 l.s.d. 3.783

93

Appendix 10

Analysis of variance for % losses of okra at exporter level

Variate: %_Loss Source of variation d.f. s.s. m.s. v.r. F pr. strata stratum 2 1.18500 0.59250 10.40 strata.*Units* stratum loss_type 3 6.53583 2.17861 38.26 <.001 Residual 6 0.34167 0.05694 Total 11 8.06250 Tables of means Variate: %_Loss Grand mean 1.175 loss_type 1 2 3 4 2.433 0.667 0.633 0.967 Standard errors of means Table loss_type rep. 3 d.f. 6 e.s.e. 0.1378 Standard errors of differences of means Table loss_type rep. 3 d.f. 6 s.e.d. 0.1948 Least significant differences of means (5% level) Table loss_type rep. 3 d.f. 6 l.s.d. 0.4768

94

Appendix 11

Analysis of variance for % losses of tomato at farmer level

Variate: %_Loss Source of variation d.f. s.s. m.s. v.r. F pr. strata stratum 2 10.2289 5.1144 20.50 strata.*Units* stratum loss_type 2 4.2222 2.1111 8.46 0.037 Residual 4 0.9978 0.2494 Total 8 15.4489 Tables of means Variate: %_Loss Grand mean 4.89 loss_type 1 2 3 4.00 5.67 5.00 Standard errors of means Table loss_type rep. 3 d.f. 4 e.s.e. 0.288 Standard errors of differences of means Table loss_type rep. 3 d.f. 4 s.e.d. 0.408 Least significant differences of means (5% level) Table loss_type rep. 3 d.f. 4 l.s.d. 1.132

95

Appendix 12

Analysis of variance for % losses of tomato at retailer level

Variate: %_Loss Source of variation d.f. s.s. m.s. v.r. F pr. strata stratum 3 4.3800 1.4600 3.19 strata.*Units* stratum loss_type 1 1.1250 1.1250 2.45 0.215 Residual 3 1.3750 0.4583 Total 7 6.8800 Tables of means Variate: %_Loss Grand mean 5.60 loss_type 1 2 5.23 5.98 Standard errors of means Table loss_type rep. 4 d.f. 3 e.s.e. 0.339 Standard errors of differences of means Table loss_type rep. 4 d.f. 3 s.e.d. 0.479 Least significant differences of means (5% level) Table loss_type rep. 4 d.f. 3 l.s.d. 1.523

POSTHARVEST ANALYSIS OF VEGETABLES IN...

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