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Sustainable recommendation domains for scaling agricultural technologies in Tanzania

dc.contributor.authorMuthoni, Francis K.
dc.contributor.authorGuo, Zhe
dc.contributor.authorBekunda, Mateete A.
dc.contributor.authorSseguya, Haroon
dc.contributor.authorKizito, Fred
dc.contributor.authorBaijukya, Frederick P.
dc.contributor.authorHoeschle-Zeledon, Irmgard
dc.date.accessioned2019-12-04T11:08:33Z
dc.date.available2019-12-04T11:08:33Z
dc.date.issued2017-07-01
dc.identifier.citationMuthoni, Francis K.; Guo, Zhe; Bekunda, Mateete; Sseguya, Haroon; Kizito, Fred; Baijukya, Frederick; Hoeschle-Zeledon, Irmgard. 2017. Sustainable recommendation domains for scaling agricultural technologies in Tanzania . Land Use Policy 66: 34-48.
dc.identifier.issn0264-8377
dc.identifier.urihttps://hdl.handle.net/20.500.12478/1854
dc.description.abstractLow adoption of sustainable intensification technologies hinders achievement of their potential impacts on increasing agricultural productivity. Proper targeting of locations to scale-out particular technologies is a key determinant of the rate of adoption. Targeting locations with similar biophysical and socio-economic characteristics significantly increases the probability of adoption. Areas with similar biophysical and socio-economic characteristics are referred to as recommendation domains (RDs). This study used geospatial analysis to delineate sustainable recommendation domains (SRDs) for scaling improved crop varieties and good agronomic practices in Tanzania. The study uses K-means clustering to identify relatively similar clusters from grid raster’s representing biophysical and socio-economic environments. Critical ecosystems are masked-out from the clusters to generate the SRDs. The potential impacts of scaling technologies in the generated SRDs were assessed and a spatial targeting index developed. Results identify 20 SRDs and the bio-socio-economic gradients that delineate them. This study proposes an Impact Based Spatial Targeting Index (IBSTI) as an objective tool for priority setting when scaling agricultural technologies. IBSTI identified priority areas within each SRD that should be targeted to maximize potential impacts of a scaling intervention. The data-driven clustering method is recommended for regions with limited technology trials. Results demonstrate the potential of geospatial tools in generating evidence-based policies on scaling of sustainable intensification technologies.
dc.description.sponsorshipUnited States Agency for International Development
dc.format.extent66: 34-48
dc.language.isoen
dc.subjectSpatial Information
dc.subjectInformación Espacial
dc.subjectGeographical Information Systems
dc.subjectSistemas De Información Geográfica
dc.titleSustainable recommendation domains for scaling agricultural technologies in Tanzania
dc.typeJournal Article
dc.description.versionPeer Review
cg.contributor.crpWater, Land and Ecosystems
cg.contributor.affiliationInternational Institute of Tropical Agriculture
cg.contributor.affiliationInternational Food Policy Research Institute
cg.contributor.affiliationInternational Center for Tropical Agriculture
cg.coverage.regionAfrica
cg.coverage.regionEast Africa
cg.coverage.regionSouthern Africa
cg.coverage.countryTanzania
cg.creator.identifierFred Kizito: 0000-0002-7488-2582
cg.isijournalISI Journal
cg.journalLand Use Policy
cg.howpublishedFormally Published
cg.accessibilitystatusOpen Access
local.dspaceid83354
cg.targetaudienceScientists
cg.identifier.doihttp://dx.doi.org/10.1016/j.landusepol.2017.04.028


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