AFSSA (Transforming Agrifood Systems in South Asia), a CGIAR Regional Integrated Initiative, addresses food system challenges by delivering actionable evidence and scalable innovations in South Asia. This brief provides an overview of TAFSSA’s study on "Characterizing the rural food environments in South Asia”. The evidence generated from this study would promote reshaping of rural food environments to improve access to affordable nutritious foods in rural South Asia

Bi, Afrin Zainab

Choudhury, Samira

Srivastava, Amit

Veettil, Prakashan Chellattan

Yeggina, Pavan Kumar

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BACKGROUNDSouth Asia’s agricultural systems aredominated by millions of smallholderfarming households (Devendra et al.2002). Most are unable to participate inmarkets due to diseconomies of scale,weak market linkages, unsustainablesupply chains, and high pricefluctuations, which lead to low farmdiversification and compromised farmerincomes. At the consumer level, TAFSSAfocuses on improving access to healthyfood for the poor through changes infood retail environments (Lytle et al. 2017; Ver Ploeg et al. 2018).Above: Informal street markets in Nalanda, Bihar.Photo Credit: Anirban Kumar and Tanweer AlamCharacterizing rural food environments in South AsiaResearch Note 2, Work Package 3 December 2022ABOUT THIS NOTETAFSSA (Transforming Agrifood Systems in South Asia), a CGIAR Regional IntegratedInitiative, addresses food system challenges by delivering actionable evidence andscalable innovations in South Asia. This brief provides an overview of TAFSSA’s studyon\Characterizing the rural food environments in South Asia”. The evidence generatedfrom this study would promote reshaping of rural food environments to improve accessto affordable nutritious foods in rural South Asia.BROAD RESEARCH QUESTIONS1. What factors in the food environment influence access to and purchase of nutritious food?2. How can food environments be improved in rural South Asia?1RESEARCH AIMSThe research aims to identify whichfactors in the rural food environmentinfluence access to and purchase ofnutritious food for poor consumers, andhow these environments can beimproved. This study examines twospecific types of food environments inthree countries in rural South Asia(Bangladesh, India and Nepal): (1)traditional markets (mandis or haats) forfruits and vegetables and other farmproduce including livestock, eggs, fishand grains, and (2) small village retail orgrocery shops or food outlets(restaurants, tea stalls, food vendors).While there may be other outlets wherepeople acquire food from, these twotypes are considered the most popularand would therefore be most likely toinfluence local diets.The traditional mandis or haats operateprimarily on a periodic (most oftenweekly) basis and are where mosthouseholds conduct their weeklygrocery shopping (Nuthalapati et al.2020). They offer a greater diversity offresh food (including fruits, vegetables,fish and meat), often at a moreaffordable price. In contrast, village retailshops typically offer relatively fewer freshfoods and are more focused on sales ofpackaged foods and everyday householditems. The data collected will be used todescribe these food environments interms of the availability of different foodsand their prices.OBJECTIVESThe objective of this study is to conducta market census and survey of themarket and retail food environment,involving the following:1) geospatial mapping of traditionalmarkets, rural retail shops andassociated clusters of habitation2) collecting information fromtraditional markets such asmandis/haats and small village retailor grocery shops or food outlets, onvarious market functionalitydimensions affecting the foodenvironment (e.g. assortment ofessential goods, viability, price,resilience of supply chains,competition, infrastructure, services,food quality, access and protection)(WFP 2020).3) developing tools for food retail designto increase the purchase ofsustainably produced and nutritiousfoods2Figure 1: Object based image segmentation hierarchical flowMAPPING OF HABITAT-RURALMARKET CLUSTERSEarth Observation data, in particular veryhigh temporal resolution Cartosal-2 and3 satellite imagery (1.1m) and Googleearth imageries (0.5 m) were used tocreate habitat segments. We broughttogether information from habitatdistribution clusters, road densitymodels, Market spatial locations andfood accessibility maps to assign habitattypes to these segments in a rule-basedapproach. The habitat clustering modelsused in the assignment procedure weredeveloped in an integrated approachesderived from the Object basedsegmentation of multi resolutionsatellite images derived from Cartosat-2& 3 (1.1m), Google earth images (0.5m)and other ancillary datasets.The Object based segmentation wasperformed in eCognition environmentfor pre-processing and detailedclassification of habitats clusters usingdecision rules implementation (Kohli etal, 2016) and the subsequent translationof these classes to cluster classes are alsodescribed. The first step towardsidentifying the habitats using ObjectBased Image Analysis (OBIA) is togenerate segments, i.e., an automaticdivision of an image into coherentgroups of pixels (segments, objects) andthe criteria used to segment an image isa degree of homogeneity within eachparticular object and heterogeneityamong neighboring objects. It was doneby using Multi resolution segmentationalgorithm using Estimating ScaleParameter (ESP) tool. The segmentationused all image layers, as OBIA is capableof using multiple data types duringanalysis to create meaningful segments.Segmentation is an important steppreceding the classification of imageobjects. The classification process caninclude a variety of information, rangingfrom spectral mean values for eachobject, to measures of texture, contextand shape.3Figure 2: Conceptual flow diagram to design market-oriented habitatsGrid based Road density maps arederived based on the intersection of theroads/streets and road types which havewell connectivity with food marketlocations , transportation and foodaccessibility.MARKET CENSUSA census of all markets in 200 clusters inBangladesh, India and Nepal was doneusing Kobo questionnaire. We collectedinformation from all the organized andinformal markets, retail shops and foodoutlets from all these clusters. Inaddition, we collected information fromcity markets selling different types offood products. The listing of thesemarkets, managers and vendors alongwith information on importantcharacteristics such as type of market,mobility, etc. allowed for stratifiedrandom sampling in the detailed marketsurvey.MARKET SURVEYMarket survey questionnaires have beengrouped into observation-based andinterview-based surveys. Modules onvarious market functionality dimensionshave been adapted from WFP’sResearch, Assessment & Monitoring andSupply Chain divisions.WFP the Market Functionality Index(MFI) is a quantitative measure tobenchmark market functionality alongthe following nine dimensions: 1)assortment of essential goods, 2)availability, 3) price, 4) resilience ofsupply chains, 5) Competition, 6)infrastructure, 7) services, 8) food quality,and 9) access and protection (WFP2020). The survey will also collect prices(minimum, maximum and modal(disaggregated) of foods in the retail andtraditional markets in the studylocations (a total of 200 clusters in SouthAsia).4Figure 3: Villages and road intersections in Nalanda, Bihar (left) and urban habitat clusters classification output (right)Above: Market survey. Photo Credit: Faijul KabirModulesInterviewObservationRetail & store information √ √Assortment of essential goods √ √Customer and sales √Infrastructure √Service √ √Food quality & hygiene √Marketing and promotion √ √Availability √Prices √ √Resilience of supply chain √Competition √Food wastage and management √ √Food sourcing (supply) √Table 1. Modules in the TAFSSAMarket surveySAMPLINGBased on GIS information, initially thedensity of different types of traditionalmarkets and village retail shops (habitatclustering, road density and marketspread using geospatial analytics) will beobtained, followed by a census ofmarkets in these habitats as well as in-depth interviews of the sample vendors,village shop retailers and marketmanagers in the same locality.Building on TAFSSA’s local food systemassessment (Methods Note 1), marketsurvey identified 5 locations (districts) inSouth Asia to initiate the survey in 2022 –Nalanda in Bihar, Rangpur and Rajshahiin Bangladesh, Surkhet and Banke inNepal. Using PPS method, villages wereidentified where household and villagesurveys (a total of 200 villages - 50 eachin Nalanda, Rangpur, Rajshahi and 25each in Surkhet and Banke) will beconducted. Using these villages, marketclusters are developed using habitatclustering approach as described in theprevious session on mapping of ruralmarkets.Depending on availability, a stratifiedrandom sample of maximum 15 retailshops or food outlets or vendors, villageand city markets per cluster, and amaximum of five large wholesale market(mandis) per district are chosen fordetailed data collection. Respondentswill be vendors, market managers (fortraditional organized markets such ashaats, market yards etc.) and villageshop retailers (for local retail shops orfood outlets). The study will targetsampling of 15 retail or food outlets orvendors, village and city markets percluster, and a maximum of five largewholesale market (mandis) per district.5Above: A retail shop in Nalanda, Bihar. Photo Credit: Shailendra KumarEXPECTED OUTPUTSMapping of rural markets and differenttypes of food outlets and linking thehousehold's diet to market are twoprimary aims of this characterization ofrural food environment work in SouthAsia. Along with this, we aim to track thefood supply and identify rural foodsheds, if available. Several outputs areexpected from this work:1. A toolkit to characterize rural marketsusing habitat clustering, which canbe used in similar settings elsewhere.2. Local food market maps and marketresilience in South Asia.3. Mapping consumer access tosentinel foods as well as farm gateprices of agricultural products withmarket prices in different context ofhabitat clusters.4. Multistakeholder dialogues onmarket resilience and delivery ofnutritious foods.5. Scientific papers and reports.REFERENCESDevendra, C., Thomas, D., 2002. Smallholderfarming systems in Asia. AgriculturalSystems 71, 17–25.https://doi.org/10.1016/S0308-521X(01)00033-6Kohli, D., Sliuzas, R., Stein, A. 2016. Urban slumdetection using texture and spatial metricsderived from satellite imagery, Journal ofSpatial Science, 61:2, 405-426.https://doi.org/10.1080/14498596.2016.1138247Lytle, L.A., Sokol, R.L., 2017. Measures of thefood environment: A systematic review of thefield, 2007–2015. Health & Place 44, 18–34.https://doi.org/10.1016/j.healthplace.2016.12.007Nuthalapati, C.S.R., Sutradhar, R., Reardon, T.,Qaim, M., 2020. Supermarket procurementand farmgate prices in India. WorldDevelopment 134, 105034.https://doi.org/10.1016/j.worlddev.2020.105034Ver Ploeg, M., Wilde, P.E., 2018. How do foodretail choices vary within and between foodretail environments? Food Policy 79, 300–308.https://doi.org/10.1016/j.foodpol.2018.03.005WFP, 2020. Market Functionality Index (MFI).Rome.https://www.wfp.org/publications/market-functionality-index-mfi6Figure 4: TAFSSA learning locations and market survey locations highlighted in the map of South Asia showing the density of rural poorABOUT TAFSSATAFSSA is CGIAR regional integrated initiative to support actions that improve equitable access to sustainable healthy diets, improve farmers’ livelihoods and resilience, and conserve land, air, and water resources in South Asia.CGIAR is a global research partnership for a  food secure future. Visit https://www.cgiar.org/research/cgiar-portfolio to learn more about the initiatives in the CGIAR research portfolioABOUT CGIARSUGGESTED CITATIONChoudhury, S., Srivastava, A., Afrin, Z.B., Yeggina, P.K., and Veettil, P.C., 2022. Characterizing rural food environments in South Asia. Work Package 3, Research Note 2. CGIAR research initiative on Transforming Agrifood Systems In South Asia (TAFSSA). International Rice Research Institute. Delhi, India.AUTHORS Samira Choudhury, Scientist – Market and Food environment, IRRIAmit Srivastava, Scientist - GIS and Remote Sensing, IRRIAfrin Zainab Bi, Assistant Scientist – Markets, IRRIPavan Kumar Yeggina, Associate Scientist – GIS and Remote Sensing, IRRIPrakashan Chellattan Veettil, Senior Scientist –Agricultural and Behavioural Economics, IRRIFUNDING ACKNOWLEDGEMENTWe would like to thank all funders who supported this research through their contributions to the CGIAR Trust Fund: https://www.cgiar.org/funders/To learn more, please contact: pc.veettil@irri.orgTo learn more about TAFSSA, please contact:t.krupnik@cgiar.org; p.menon@cgiar.orgResponsibility for editing, proofreading, and layout, opinions expressed, and any possible errors lies with the authors and not the institutions involved. The boundaries and names shown, and the designations used on maps do not imply official endorsement or acceptance by IRRI, the CGIAR, our partner institutions, or donors.DISCLAIMER

Characterizing rural food environments in South Asia

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Characterizing rural food environments in South Asia

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