Post on 17-May-2018
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)