HarvestPlus c/o CIAT A.A. 6713 • Cali, Colombia Tel: +57(2)4450000 • Fax: +57(2)4450073 HarvestPlus@cgiar.org • www.HarvestPlus.org

Research advances of

HarvestPlus socioeconomic

studies in LAC

Carolina Gonzalez Impact Assessment, Harvest Plus LAC

CIAT-IFPRI

26 Jun 2014

Contents

• Portfolio of socioeconomic studies for H+LAC

• Biofortification Prioritization Index (BPI) for Colombia

• Rice production, consumption and commercialization in Bolivia

• Consumer Acceptance of a HIB variety (Super Chiva) in Guatemala

HarvestPlus

AgroSalud LAC -14

countries HarvestPlus

LAC

2002-2004 2005 2006-2008-2009-2010-2011 2012-2013 (- 2018)

Guatemala, Nicaragua,

Haiti, Bolivia

Panama, Brazil and

Colombia

HarvestPlus

Global

Honduras, El Salvador

We develop nutrient-rich seeds: Beans-iron/zinc; rice-zinc;

maize: VIT A/zinc; cassava-VIT A; sweet Potato-VIT A

Overall portfolio in LAC/Brazil

• Where to invest? 1. Prioritization exercise 2. Opportunities map

• Informing delivery and breeding 1. Varietal adoption studies 2. Consumer acceptance studies 3. Farmer field day evaluation

• Measuring impact 1. Farmer feedback studies 2. Impact assessment 3. Impact evaluation/effectiveness

• Policy studies

COLOMBIA BPI

José Funes, Carolina González, Salomón Perez,

Alexander Buritica, Ekin Birol, Manfred Zeller

Three basic conditions

The geographic areal unit must be a producer of the crop.

The geographical areal unit’s population must consume a substantial quantity of the crop under consideration.

The geographical areal unit’s population suffers from deficiencies for the key micronutrients, namely vitamin A, zinc, or iron.

Asafo et al. (2013) www.harvestplus.org/content/prioritizing-countries-biofortification-interventions-using-country-level-data

Production index

• Production index = [1/3*per capita area harvestedr] +

[1/3*Agricultural land allocated to the cropr] + [1/3*Spatial Interaction Factorr]x

Department

Production

Index

Cassava

GUAINIA 1.00

ARAUCA 0.49

AMAZONAS 0.45

GUAVIARE 0.45

SUCRE 0.41

BOLIVAR 0.30

CAQUETÕ 0.29

VAUPES 0.29

MAGDALENA 0.27

CORDOBA 0.21

Department

Production

Index Maize

(interaction

index)

CORDOBA 0.70

ARAUCA 0.58

GUAVIARE 0.50

BOLIVAR 0.43

SUCRE 0.40

GUAINIA 0.39

PUTUMAYO 0.39

CESAR 0.34

CAQUETA 0.34

MAGDALENA 0.32

Department

Production Rice

Index (spatial

interaction)

CASANARE 0.94

TOLIMA 0.70

META 0.62

SUCRE 0.37

CHOCO 0.34

NORTE DE SANTANDER 0.29

HUILA 0.25

CESAR 0.19

ARAUCA 0.18

BOLIVAR 0.12

Department

Production

Index Bean

(interaction

index)

HUILA 0.62

CUNDINAMARCA 0.46

CALDAS 0.37

QUINDIO 0.33

SANTANDER 0.28

ANTIOQUIA 0.27

NARINO 0.26

CAUCA 0.24

TOLIMA 0.23

NORTE DE SANTANDER 0.22

The spatial index a

Figure. Rice food deficit/ rice food surplus/ rice food balanced

Source: Authors calculations based on DANE –ENA 2011

• Food surplus

(ration <=0.8)

• Food balanced

(0.8-1.2)

• Food deficit

areas (>=1.2).

SII: Measures the potential spatial interaction between

departments that have surpluses on their aggregate supply

and with their neighbors departments.

Consumption index

• Consumption Index i = [(rur_popi/tot_popi) * rur_ cons_capitai + (urb_popi/total_popi) * urb_ cons_capitai]r

DepartmentConsumption

Index Maize

CHOCO 1.00

VAUPES 0.99

TOLIMA 0.82

CALDAS 0.69

GUAINIA 0.65

RISARALDA 0.65

ANTIOQUIA 0.49

CAUCA 0.45

QUINDIO 0.40

CAQUETA 0.38

DepartmentConsumption

Index Bean

CALDAS 1.00

ANTIOQUIA 0.96

GUAINIA 0.86

TOLIMA 0.85

QUINDIO 0.84

RISARALDA 0.83

META 0.78

VAUPES 0.74

GUAVIARE 0.72

VICHADA 0.71

DepartmentConsumption

Index Rice

BOLIVAR 1.00

VALLE DEL CAUCA 0.72

ANTIOQUIA 0.63

CAUCA 0.48

ATLANTICO 0.38

MAGDALENA 0.35

SUCRE 0.35

CORDOBA 0.30

LA GUAJIRA 0.28

CESAR 0.21

www.Laylita.com

DepartmentConsumption

Index Cassava

LA GUAJIRA 1.00

NORTE DE SANTANDER 0.92

CESAR 0.80

MAGDALENA 0.79

SANTANDER 0.75

CAQUETA 0.74

BOLIVAR 0.70

SUCRE 0.62

ATLANTICO 0.57

ARAUCA 0.49

Micronutrients:

Vitamin A micronutrient deficiency index

– Micronutrient Index (Vitamin A) = ½*Serum Retinol 0.7 + ½*(100 - proportion of consumption by food groups fruits).

Iron micronutrient deficiency index

– Micronutrient Index (Iron) = ½*ferritin 12 + ½*(100 - proportion of consumption by food groups meats and eggs)

Zinc micronutrient deficiency index

– Micronutrient Index (Zinc) = ½*Inadequate Zinc + ½*Stunting prevalence

Micronutrients - Results:

𝑩𝒊𝒐𝒇𝒐𝒓𝒕𝒊𝒇𝒊𝒄𝒂𝒕𝒊𝒐𝒏 𝑷𝒓𝒊𝒐𝒓𝒊𝒕𝒚 𝑰𝒏𝒅𝒆𝒙 𝑩𝑷𝑰

= 𝑀𝑖𝑐𝑟𝑜𝑛𝑢𝑡𝑟𝑖𝑒𝑛𝑡 𝐷𝑒𝑓𝑖𝑐𝑖𝑒𝑛𝑐𝑦 𝐼𝑛𝑑𝑒𝑥 ∗ 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝐼𝑛𝑑𝑒𝑥 ∗ 𝐶𝑜𝑛𝑠𝑢𝑚𝑝𝑡𝑖𝑜𝑛 𝐼𝑛𝑑𝑒𝑥

BPI:

Rice

DepartmentRank_bpi

_rice

Rank_bpi_rice_

pop_weighted

Rank_bpi_rice_

spatial_interac

tion_suppliers

Production

rice

[intervention]

Impact

rice

Intervention

& impact

rice

CHOCO 1 12 1 1 1 1

SUCRE 2 8 2 1 0 0

CAUCA 3 2 3 0 1 0

ANTIOQUIA 4 1 4 1 0 0

BOLIVAR 5 4 6 1 0 0

LA GUAJIRA 6 6 5 1 1 1

CESAR 7 13 7 1 1 1

MAGDALENA 8 10 9 0 1 0

TOLIMA 9 5 8 1 0 0

CORDOBA 10 3 10 1 0 0

Candidate sites for biofortification with zinc: rice

Beans

Candidate sites for biofortification with iron: beans

DepartmentRank_bpi

_beans

Rank_bpi_b

eans_pop_

weighted

Rank_bpi_b

eans_spatial

_interaction

Production

bean

[intervention]

Impact

beans

Intervention

& impact

beans

ANTIOQUIA 1 1 1 1 1 1

CALDAS 2 7 3 1 0 0

QUINDIO 3 19 4 0 0 0

RISARALDA 4 10 5 1 0 0

CUNDINAMARCA 5 2 2 0 0 0

NORTE DE SANTANDER6 9 6 1 0 0

TOLIMA 7 5 7 1 1 1

HUILA 8 6 8 0 0 0

BOYACA 9 3 9 0 0 0

SANTANDER 10 4 10 1 0 0

Cassava

DepartmentRank_bpi

_cassava

Rank_bpi_cassava

_pop_weighted

Production

cassava

[intervention]

Impact

cassava

Intervention

& impact

cassava

SUCRE 1 5 1 1 1

BOLIVAR 2 3 0 0 0

ARAUCA 3 17 1 0 0

GUAINIA 4 24 0 1 0

MAGDALENA 5 4 0 1 0

AMAZONAS 6 21 1 1 1

GUAVIARE 7 22 1 0 0

CORDOBA 8 2 0 0 0

VAUPES 9 26 1 0 0

CESAR 10 9 0 0 0

PUTUMAYO 11 15 1 1 1

LA GUAJIRA 12 7 0 0 0

CAQUETA 13 14 0 0 0

VICHADA 14 25 1 0 0

NORTE DE SANTANDER15 10 0 0 0

ATLANTICO 16 18 1 1 1

CASANARE 17 20 1 1 1

SANTANDER 18 6 0 0 0

ANTIOQUIA 19 1 0 0 0

HUILA 20 12 1 0 0

Candidate sites for biofortification with VIT A: cassava

Maize

DepartmentRank_bpi

_maize

Rank_bpi_

maize_pop

_weighted

Rank_bpi_m

aize_spatial

_interaction

Production

maize

[intervention]

Impact

maize

Intervention

& impact

maize

VAUPES 1 24 1 1 1 1

GUAINIA 2 25 2 0 1 0

ANTIOQUIA 3 1 3 0 1 0

GUAVIARE 4 20 5 1 1 1

ARAUCA 5 18 7 1 0 0

CORDOBA 6 2 4 1 1 1

SUCRE 7 10 6 1 1 1

CESAR 8 12 8 0 0 0

LA GUAJIRA 9 8 9 1 0 0

CHOCO 10 13 11 1 1 1

Candidate sites for biofortification with VIT A: maize

Next Steps

Finalize the working paper…

Develop a subnational Biofortification Prioritization Index to rank regions in Guatemala where biofortification could have the highest impact using the food basket approach.

To include US cost/benefits

Data sources

• Micronutrient deficiency statistics: the National Survey of Nutritional Situation (ENSIN) assesses the nutritional state in Colombia. The survey is national, regional (6 regions) and department (32 departments) representative. It is also representative for urban and rural areas (ENSIN, 2010). [departments, n=32]

• Production statistics: the annual evaluation of agriculture and livestock of municipalities 2011 produced by the ministry of agriculture [municipalities, n=1120] and FAO food balance sheet.

• Consumption statistics: the ENSIN 2005 survey provides per capita food consumption statistics[departments, n=32; municipalities, n=252].

• Population statistics: 2011 population projections, based on 2005 population census (DANE, 2011). [districts, n=1120] % & UN Population prospects (2013).

• BPI – departments

17

Diana Lopera, Ricardo Labarta, Victor Zuluaga, José María

Martinez, Roger Taboada and Carolina Gonzalez

Rice in Bolivia

Adoption study of rice varieties in

Bolivia

General Objectives (some preliminary results)

• Characterization of the rice production system in Bolivia.

• Identification of the rice varieties in Bolivia (farmers’ identification vs. molecular markers).

• Estimation of current adoption rates for rice varieties in the country and factors associated with farmers’ choice of rice varieties.

• Estimation of the proportion used for home consumption and sales across rice producing households and preferences

• Identify household main source(s) of information, about agricultural techniques and health and nutrition.

• Collect secondary information with the local organizations (secretaries of health, municipalities, and hospitals) about micronutrient deficiency. Available

Sampling

We used a multi-stage sampling procedure:

Total surveys required due to the sampling

Total surveys actually conducted (due to logistical

constraints)

Households Village Households Village

Irrigated producers 84 7 83 6 Rainfed producers 900 75 855 94 Total producers 984 82 938 100

12 producers/community

Study sites

Department Province Freq.

Santa Cruz (n=613)

Guarayos 150 Ichilo 238

Ñuflo de Chávez 39

Obispo Santistevan

65

Sara 58

Warnes 62

Beni (n=244)

Ballivian 72

Cercado 45 Marban 67

Moxos 60 Cochabamba

(n=81) Carrasco 81

Department Province Municipality Village 3 11 24 100

Preliminary descriptive statistics :

Household characteristics

Total

Department

Santa Cruz Beni Cochabam

ba Anova Obs. Mean Mean Mean Mean

Household size 846 4.6 4.4 4.8 5.1 **

(2.22) (2.2) (2.3) (2.1)

Gender of head of hh (%male) 848 0.96 0.96 1.0 1.0

(0.18) (0.2) (0.2) (0.2)

Age of head of hh (years) 842 46.0 45.9 47.1 43.8 *

(12.41) (12.4) (12.4) (12.0)

Years of schooling received by household head

792 6.6 6.7 6.4 6.2

(4.14) (4.1) (4.2) (4.2)

(whitout japanese)

Preliminary descriptive statistics :

Production unit and Rice

Total

Departments

Santa Cruz Beni Cochabamba Anova

Obs. Mean Median Mean Median Mean Median Mean Median

Total land available for production (ha)-APU

852 57.5 37 80.90 50 18.1 2 23.7 11.5 *** (150.6) (185.79) (29.07) (46.48)

Total rice area planted (ha)

853 17.2 3.0 25.7 10 2.5 1 5.5 1 *** (58.6) (72.7) (4.7) (17.6)

Total rice production (ton)

835 42.0 4.8 63.4 16 6.0 1.2 14.2 1.53 ***

(175.6) (220.4) (14.7) (46.1)

Yield (ton/ha) 835 2.1 1.9 2.3 2 1.8 1.6 2.0 2 *** (1.5) (1.5) (1.3) (1.4)

(whitout japanese)

Production constraints

Pest and Insects

Drought

Diseases

other

Floods

Grain yield

Low soil fertility

Lack of inputs

Seed quality

53.39%

26.28%

6.66%

4.28%

3.57%

3.57%

1.07%

0.71%

0.48%

What are your main production constraints? (most important)

(N= 841) (N= 828)

High yield

Resistance to pest and Insects

Resistance to diseases

Tolerance to drought

Short-cycle varieties

Lower levels of inputs

Other

70.51%

8.32%

3.45%

12.01%

3.09%

0.71%

1.90%

What characteristics do you look for in rice varieties when deciding what

varieties to use on your plot? (most important)

Main varieties planted

MAC 18

GRANO DE ORO

ESTAQUILLA

JASAYE

EPAGRI

URUPE

POPULAR

TARI

PAITITI

CRISTAL

DORADO

IAC 101

PANACU

BLUEBONNET

CARANDEÑO

IAC 103

OTRAS

22.0%

10.3%

9.2%

7.5%

6.3%

5.8%

4.5%

3.8%

3.3%

2.5%

2.1%

1.5%

1.5%

1.5%

1.2%

1.0%

16.2%

Planted varieties by plot excluding Japanese (2012-2013)

CAISY 50

EPAGRI

EPAGRI 109

IAC 101

MAC 18

0.5%

26.2%

3.3%

34.3%

35.7%

Planted varieties by plot (2012-2013): Japanese

N= 1019 plots N= 210 plots

Our sampling covers around 15.794 ha

MAC 18

GRANO DE ORO

EPAGRI

URUPE

ESTAQUILLA

TARI

PANACU

IAC 101

PAITITI

EPAGRI 115

JASAYE

NOVENTON

IAC 103

IAC 115

SAAVEDRA 44

OTHER

47.77%

8.79%

7.72%

6.14%

5.49%

4.28%

3.74%

3.59%

2.78%

1.58%

1.51%

1.37%

1.02%

0.51%

0.44%

3.26%

Main rice varieties in Bolivia: percentage of total area planted

Main varieties planted by department

ESTAQUILLA

GRANO DE ORO

POPULAR

MAC 18

JASAYE

EPAGRI

OTHER

22.0%

17.0%

15.2%

9.5%

5.3%

4.2%

26.9%

BENI: planted varieties by plot (2012-2013)

CRISTAL

ESTAQUILLA

URUPE

MAC 18

CAROLINA

PAITITI

OTHER

28.9%

15.6%

7.8%

8.9%

6.7%

5.6%

26.7%

COCHABAMBA: planted varieties by plot (2012-2013)

MAC 18

JASAYE

GRANO DE ORO

URUPE

EPAGRI

TARI

OTHER

29.6%

9.4%

9.0%

8.6%

8.0%

5.6%

29.9%

SANTA CRUZ: planted varieties by plot (2012-2013)

Commercialization and Consumption

Sale is 81% vs. 19% consumption and seed*

Disaggregating by department we found that the change share was 85% vs. 15% for Santa Cruz and 71% vs. 29% for Beni respectively*

Consumption

Dto N Mean (kg/d) p50 sd min max

Beni 243 1.2 1 0.8 0.1 6

Cochabamba 81 1.3 1 0.8 0.25 5

Santa Cruz 515 1.3 1 0.8 0.2 9

Total 839 1.2 1 0.8 0.1 9

Rice food - Bolivia

Consumer preferences

Grain type (shape and length)

Grain quality

 Easier to thresh

Easier to sell/ good marketing

Good taste

Other

41.91%

20.89%

7.61%

10.02%

18.48%

1.09%

What qualities do you look for in rice varieties when deciding what varieties to

use on your plot? (most important)

Long and thin

Short and round

Super-fine rice and aromatic

Millet rice and polished

Brown rice (less polished)

Popular (medium and round)

66.40%

16.10%

7.00%

10.80%

0.70%

38.20%

Which type of rice do you prefer? (count of 1=yes)

(n= 855 whitout japanese)

Next Steps

Identification of the rice

varieties in Bolivia (farmers’

identification vs. molecular

markers).

Finish the analysis..

Outputs

Master Thesis

Papers (2)

Consumer Acceptance of a HIB variety

(super chiva) in Guatemala Salomón Perez, Carolina González, Ekin Birol, Manfred

Zeller – ICTA- U. Hohenheim

Objectives

1. Determine the socioeconomic and organoleptic factors affecting the acceptance of iron biofortifed beans varieties in Guatemala.

1. Estimate the premium/discount related with HIB variety (super chiva) in Guatemala.

2. Evaluate the acceptance of the HIB variety from a gender basis

32

Why Guatemala?

Prevalence of anemia in

children 6 – 59 months: 47% (ENSMI, 2009).

Prevalence of anemia pregnant women: 29.1% (ENSMI, 2009).

Prevalence of anemia non pregnant women: 21.4% (ENSMI, 2009).

Source: http://www.desdeabajo.info

*Anemia: hemoglobin < 11g/dl 33

Data Collection

Location: Municipality of San Sebastian Huehuetenango (North-West of Guatemala)

34

Methodology

Sample size : 360 HH’s randomly selected in 8 districts.

Home use testing approach

Three treatments:

1. No information

2. Information (once)

3. Information (three times)

Becker-DeGroot-Marschak (BDM) auction: 1. Ask willingness to pay for

each variety 2. Select a paper with a

variety figure from a bag 3. Select one price from the

bag 4. Win or lost - purchase the

variety.

Source:Fieldwork 36

Methodology (b)

Preliminary results (PR): Sample characterization

37

Variable

Construction

Mean

Treatment 1 Treatment 2 Treatment 3 Prob > F

Age Respondent’s age in years 36.24 35.82 34.96 0.7340

Literacy HH’s head knows to write and read 70% 68.33 70.59% 0.7791

HH size** Number of members in the HH 6.32 6.06 5.46 0.0210

Income Expenses in the last 30 day in

Quetzales

2,447 2,629 2,265 0.2022

Poverty PPI 61.25% 66.47% 65.34% 0.3631

Consumption Beans consumption per week

(pounds)

3.34 3.15 2.65 0.3824

Food

frequency

index

Count of 15 food groups consumed in

the last 7 days (less than 4=0, 4-

6=1,7+=2)

6.34 5.90 5.93 0.3933

Babies HH with babies less than 12 months 22.5% 25% 20% 0.4055

Children (1-5

years)*

HH with children between 1-5 years 53.3% 40% 45% 0.0688

Pregnancy HH with pregnant women 3.33% 6.67% 5.04% 0.3907

p<0.1*, p<0.05**, p<0.01***

PR: (Mean hedonic rating (MHR) of bean variety)

38

Bean variety Raw bean color

Raw bean size

Bean taste Time of cooking

Cooked bean thickness

Cooked bean toughness

Overall

Co

ntr

ol (

T1):

No

In

form

atio

n Local (Hunapu) 6.55±0.59 6.57±0.72 6.59±0.75 6.10±1.35 6.17±1.29 1.85±2.95 6.47±1.00

HIB (Superchiva) 6.63±0.72 6.61±0.67 6.75±0.74 6.58±0.74 6.66±0.66 1.95±3.07 6.66±0.66

Difference in means

HIB vs Local 0.75 0.042 0.16 0.47*** 0.49*** 0.11 0.19*

T2:

Info

rmat

ion

p

rese

nt

on

ce Local (Hunapu) 6.53±0.46 6.5 ±0.56 6.63±0.52 6.37±1.09 6.40±0.93 1.42±2.73 6.59±0.63

HIB (Superchiva) 6.77±0.65 6.74±0.46 6.85±0.42 6.64±0.76 6.6 ±0.91 1.21±2.63 6.6±0.91

Difference in means

HIB vs Local 0.24*** 0.24*** 0.21*** 0.26** 0.19 -0.21 0.01

T3: I

nfo

rmat

ion

p

rese

nt

thre

e

tim

es

Local (Hunapu) 6.55±0.57 6.54±0.55 6.63±0.53 6.39±0.67 6.53±0.54 1.34±2.63 6.59±0.59

HIB (Superchiva) 6.76±0.51 6.77±0.51 6.84±0.46 6.57±0.77 6.64±0.96 1.15±2.51 6.64±0.96

Difference in means

HIB vs Local 0.21*** 0.23*** 0.20*** 0.17* 0.11 -0.19 0.06

PR: Mean economic rating of bean varieties

39

Average WTP Premium/Discount

WTP HIB (T1) WTP HIB (T2) WTP HIB (T3) WTP trad (T1) WTP trad (T2) WTP trad (T3) Premium (T1) Premium (T2) Premium (T3)

4.83±0.71 4.96±0.83 4.89±0.76 4.70±0.72 4.67±0.74 4.67±0.71

0.133±0.90 0.289±0.94 0.220±0.81

There’ is not significant differences between the WTP

towards both varieties across the three treatments.

Frequency of information did not have effects

Next Steps

…to finish the described objectives

Muchas gracias!!

Outputs:

Ph.D Thesis (1)

Papers (2)