Show simple item record

Accounting for correlation among environmental covariates improves delineation of extrapolation suitability index for agronomic technological packages

dc.contributor.authorMuthoni, Francis K.
dc.contributor.authorBaijukya, Frederick P.
dc.contributor.authorBekunda, Mateete A.
dc.contributor.authorSseguya, H.
dc.contributor.authorKimaro, Anthony A.
dc.contributor.authorAlabi, T.
dc.contributor.authorMruma, S.
dc.contributor.authorHoeschle-Zeledon, Irmgard
dc.date.accessioned2019-12-04T11:11:28Z
dc.date.available2019-12-04T11:11:28Z
dc.date.issued2017
dc.identifier.citationMuthoni, F.K., Baijukya, F., Bekunda, M., Sseguya, H., Kimaro, A., Alabi, T., ... and Hoeschle-Zeledon, I. 2017. Accounting for correlation among environmental covariates improves delineation of extrapolation suitability index for agronomic technological packages. Geocarto International, 1-23.
dc.identifier.issn1010-6049
dc.identifier.urihttps://hdl.handle.net/20.500.12478/2435
dc.descriptionArticle purchased; Published online: 01 Dec 2017
dc.description.abstractThis paper generates an extrapolation suitability index (ESI) to guide scaling-out of improved maize varieties and inorganic fertilizers. The best-bet technology packages were selected based on yield gap data from trial sites in Tanzania. A modified extrapolation detection algorithm was used to generate maps on two types of dissimilarities between environmental conditions at the reference sites and the outlying projection domain. The two dissimilarity maps were intersected to generate ESI. Accounting for correlation structure among covariates improved estimate of risk of extrapolating technologies. The covariate that highly limited the suitability of specific technology package in each pixel was identified. The impact based spatial targeting index (IBSTI) identified zones that should be prioritized to maximize the potential impacts of scaling-out technology packages. The proposed indices will guide extension agencies in targeting technology packages to suitable environments with high potential impact to increase probability of adoption and reduce risk of failure.
dc.description.sponsorshipUnited States Agency for International Development
dc.format.extent1-23
dc.language.isoen
dc.subjectMaize
dc.subjectFood Security
dc.subjectSustainable Agriculture
dc.subjectBig Data
dc.subjectNovel Correlation
dc.subjectPriority Setting
dc.subjectRisk Of Failure
dc.subjectSpatial Targeting
dc.titleAccounting for correlation among environmental covariates improves delineation of extrapolation suitability index for agronomic technological packages
dc.typeJournal Article
dc.description.versionPeer Review
cg.contributor.crpMaize
cg.contributor.crpGrain Legumes
cg.contributor.crpIntegrated Systems for the Humid Tropics
cg.contributor.crpWater, Land and Ecosystems
cg.contributor.affiliationInternational Institute of Tropical Agriculture
cg.contributor.affiliationWorld Agroforestry Centre
cg.contributor.affiliationACDI/VOCA
cg.coverage.regionAfrica
cg.coverage.regionEast Africa
cg.coverage.countryTanzania
cg.isijournalISI Journal
cg.authorship.typesCGIAR and advanced research institute
cg.iitasubjectAgronomy
cg.iitasubjectFood Security
cg.iitasubjectMaize
cg.iitasubjectValue Chains
cg.journalGeocarto International
cg.howpublishedFormally Published
cg.accessibilitystatusOpen Access
local.dspaceid93002
cg.targetaudienceScientists
cg.identifier.doihttp://dx.doi.org/10.1080/10106049.2017.1404144


Files in this item

Thumbnail
Name:
U17ArtMuthoniAccountingInthomN ...
Size:
4.227Mb
Format:
PDF
View/Open

This item appears in the following Collection(s)

Show simple item record