The socioeconomic area of HarvestPlus LAC seeks to generate information to guide the decision related to biofortified crops in the region. The idea of this seminar is to present advances made in three socioeconomic studies: a. Potential departments/regions for an intervention with biofortified crops (cassava, rice, beans and maize) in Colombia; b. Adoption, consumption and ommercialization of improved rice varieties in Bolivia and c. Preliminary results of a consumer acceptance of a High Iron Bean variety (Super Chiva) in Guatemala.

1. 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

2. 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

3. 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

4. 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

5. COLOMBIA BPI
José Funes, Carolina González, Salomón Perez,
Alexander Buritica, Ekin Birol, Manfred Zeller, Moursi
Mourad

6. 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.
Asare-Marfo et al. (2013) www.harvestplus.org/content/prioritizing-countries-
biofortification-interventions-using-country-level-data

7. 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
7

8. 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

9. 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.

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

11. Micronutrients:
Vitamin A micronutrient deficiency index
– Micronutrient Index (Vitamin A) = ½*Serum Retinol <0.7 µmol/l +
½*(100 - proportion of consumption by food groups fruits).
Iron micronutrient deficiency index
– Micronutrient Index (Iron) = ½*ferritin < 12 g/dl + ½*(100 - proportion
of consumption by food groups meats and eggs)
Zinc micronutrient deficiency index
– Micronutrient Index (Zinc) = ½*Inadequate Zinc + ½*Stunting
prevalence

12. Micronutrients - Results:
𝑩𝒊𝒐𝒇𝒐𝒓𝒕𝒊𝒇𝒊𝒄𝒂𝒕𝒊𝒐𝒏 𝑷𝒓𝒊𝒐𝒓𝒊𝒕𝒚 𝑰𝒏𝒅𝒆𝒙 𝑩𝑷𝑰
= 𝑀𝑖𝑐𝑟𝑜𝑛𝑢𝑡𝑟𝑖𝑒𝑛𝑡 𝐷𝑒𝑓𝑖𝑐𝑖𝑒𝑛𝑐𝑦 𝐼𝑛𝑑𝑒𝑥 ∗ 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝐼𝑛𝑑𝑒𝑥 ∗ 𝐶𝑜𝑛𝑠𝑢𝑚𝑝𝑡𝑖𝑜𝑛 𝐼𝑛𝑑𝑒𝑥
BPI:

13. Rice
Department
Rank_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

14. Beans
Candidate sites for
biofortification with iron: beans
Department
Rank_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

15. Cassava
Department
Rank_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

16. Maize
Department
Rank_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

17. 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.

18. Diana Lopera, Ricardo Labarta, Victor Zuluaga, José María
Martinez, Roger Taboada and Carolina Gonzalez
Rice in Bolivia

19. 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

20. 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

21. 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

22. 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)

23. 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)

24. 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)

25. 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

26. 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

27. 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)

28. 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

29. 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)

30. Next Steps
Identification of the rice
varieties in Bolivia (farmers’
identification vs. molecular
markers).
Finish the analysis..
Outputs
Master Thesis
Papers (2)

31. Consumer Acceptance of a HIB variety
(super chiva) in Guatemala
Salomón Perez, Carolina González, Ekin Birol, Manfred
Zeller – ICTA- U. Hohenheim

32. 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

33. 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

34. Data Collection
Location: Municipality of San Sebastian
Huehuetenango (North-West of Guatemala)
34

35. 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)

36. 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)
If bid ≥ random price “WIN”
If bid < random price “LOSE”
Pay
price
Don’t
Pay

37. 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***

38. 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
Control(T1):No
Information
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:
Information
presentonce
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:Information
presentthree
times
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

39. 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

40. Next Steps
…to finish the described objectives
Muchas gracias!!
Outputs:
Ph.D Thesis (1)
Papers (2)