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dc.contributorSonder, Kaien_US
dc.contributorCairns, Jillen_US
dc.contributorMagorokosho, Cosmosen_US
dc.contributorTarekegn, Amsalen_US
dc.contributorKassie, Girmaen_US
dc.contributorGetaneh, Fiteen_US
dc.contributorAbdoulaye, Tahirouen_US
dc.contributorAbate, Tsedekeen_US
dc.contributorErenstein, Olafen_US
dc.creatorTesfaye, Kindieen_US
dc.date2016-04-27en_US
dc.date.accessioned2017-02-27T13:02:02Z
dc.date.available2017-02-27T13:02:02Z
dc.identifierhttps://mel.cgiar.org/reporting/download/hash/wOOBDXfven_US
dc.identifier.citationKindie Tesfaye, Kai Sonder, Jill Cairns, Cosmos Magorokosho, Amsal Tarekegn, Girma Tesfahun Kassie, Fite Getaneh, Tahirou Abdoulaye, Tsedeke Abate, Olaf Erenstein. (27/4/2016). Targeting Drought-Tolerant Maize Varieties in Southern Africa: A Geospatial Crop Modeling Approach Using Big Data. International Food and Agribusiness Management Review, 19(A), pp. 75-92.en_US
dc.identifier.urihttp://hdl.handle.net/20.500.11766/6037
dc.description.abstractMaize is a major staple food crop in southern Africa and stress tolerant improved varieties have the potential to increase productivity, enhance livelihoods and reduce food insecurity. This study uses big data in refining the geospatial targeting of new drought-tolerant (DT) maize varieties in Malawi, Mozambique, Zambia, and Zimbabwe. Results indicate that more than 1.0 million hectares (Mha) of maize in the study countries is exposed to a seasonal drought frequency exceeding 20% while an additional 1.6 Mha experience a drought occurrence of 10–20%. Spatial modeling indicates that new DT varieties could give a yield advantage of 5–40% over the commercial check variety across drought environments while crop management and input costs are kept equal. Results indicate a huge potential for DT maize seed production and marketing in the study countries. The study demonstrates how big data and analytical tools enhance the targeting and uptake of new agricultural technologies for boosting rural livelihoods, agribusiness development and food security in developing countries.en_US
dc.formatPDFen_US
dc.languageenen_US
dc.publisherInternational Food and Agribusiness Management Association (IFAMA)en_US
dc.rightsCC-BYen_US
dc.sourceInternational Food and Agribusiness Management Review;19,(2016) Pagination 75,92en_US
dc.subjectgeodataen_US
dc.subjectresearch for developmenten_US
dc.subjectcropen_US
dc.subjectmodelingen_US
dc.subjectMaizeen_US
dc.titleTargeting Drought-Tolerant Maize Varieties in Southern Africa: A Geospatial Crop Modeling Approach Using Big Dataen_US
dc.typeJournal Articleen_US
cg.creator.ID0000-0001-7430-4291en_US
cg.creator.ID-typeORCIDen_US
cg.subject.agrovocbreedingen_US
cg.subject.agrovocdroughten_US
cg.subject.agrovocfood securityen_US
cg.subject.agrovoclivelihoodsen_US
cg.subject.agrovocproductivityen_US
cg.contributor.centerInternational Maize and Wheat Improvement Center - CIMMYTen_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.centerInternational Institute of Tropical Agriculture - IITAen_US
cg.contributor.funderInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.projectCommunication and Documentation Information Services (CODIS)en_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.coverage.regionEastern Africaen_US
cg.coverage.countryMWen_US
cg.coverage.countryMZen_US
cg.coverage.countryZMen_US
cg.coverage.countryZWen_US
cg.contactK.tesfayefantaye@cgiar.orgen_US
dc.identifier.statusOpen accessen_US
mel.project.openhttps://mel.cgiar.org/projects/codisen_US


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