Research advances of HarvestPlus socioeconomic studies in LAC
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Research advances of HarvestPlus socioeconomic studies in LAC

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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 ...

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.

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  • En paréntesis la desviación estantadar <br /> La significancia esta medida por la estrella * al 10% **al 5% ***al 1% <br /> *si p>0.05 no es estadisticamente significativo por tanto no hay diferencias significativas en el tamaño del hogar entre los departamentos, es decir, el departamento no influye sobre el tamaño del hogar <br />
  • Solo incluye el 25% de los datos <br />
  • H+ was lounched in 2004. Its coordinated by ifpri and ciat <br /> Conventional breeding is used
  • H+ was lounched in 2004. Its coordinated by ifpri and ciat <br /> Conventional breeding is used
  • H+ was lounched in 2004. Its coordinated by ifpri and ciat <br /> Conventional breeding is used
  • H+ was lounched in 2004. Its coordinated by ifpri and ciat <br /> Conventional breeding is used
  • H+ was lounched in 2004. Its coordinated by ifpri and ciat <br /> Conventional breeding is used
  • H+ was lounched in 2004. Its coordinated by ifpri and ciat <br /> Conventional breeding is used
  • H+ was lounched in 2004. Its coordinated by ifpri and ciat <br /> Conventional breeding is used
  • H+ was lounched in 2004. Its coordinated by ifpri and ciat <br /> Conventional breeding is used

Research advances of HarvestPlus socioeconomic studies in LACResearch advances of HarvestPlus socioeconomic studies in LAC Presentation Transcript

  • 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, Moursi Mourad
  • 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
  • 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
  • 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 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
  • 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
  • Micronutrients - Results: 𝑩𝒊𝒐𝒇𝒐𝒓𝒕𝒊𝒇𝒊𝒄𝒂𝒕𝒊𝒐𝒏 𝑷𝒓𝒊𝒐𝒓𝒊𝒕𝒚 𝑰𝒏𝒅𝒆𝒙 𝑩𝑷𝑰 = 𝑀𝑖𝑐𝑟𝑜𝑛𝑢𝑡𝑟𝑖𝑒𝑛𝑡 𝐷𝑒𝑓𝑖𝑐𝑖𝑒𝑛𝑐𝑦 𝐼𝑛𝑑𝑒𝑥 ∗ 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝐼𝑛𝑑𝑒𝑥 ∗ 𝐶𝑜𝑛𝑠𝑢𝑚𝑝𝑡𝑖𝑜𝑛 𝐼𝑛𝑑𝑒𝑥 BPI:
  • 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
  • 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
  • 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
  • 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
  • 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.
  • 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) If bid ≥ random price “WIN” If bid < random price “LOSE” Pay price Don’t Pay
  • 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 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
  • 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)