Seed systems for African food security: linking molecular genetics and cultivator knowledge in West Africa

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dc.contributor.authorRichards, P.
dc.contributor.authorDeBruin, H.M.
dc.contributor.authorHughes, S.G.
dc.contributor.authorKudadjie-Freeman, C.
dc.contributor.authorOffei, S.K.
dc.contributor.authorStruik, P.C.
dc.date.accessioned2012-05-24T10:57:26Z
dc.date.accessioned2017-10-14T11:55:40Z
dc.date.available2012-05-24T10:57:26Z
dc.date.available2017-10-14T11:55:40Z
dc.date.issued2009
dc.description.abstractA challenge for African countries is how to integrate new sources of knowledge on plant genetics with knowledge from farmer practice to help improve food security. This paper considers the knowledge content of farmer seed systems in the light of a distinction drawn in artificial intelligence research between supervised and unsupervised learning. Supervised learning applied to seed systems performance has a poor record in Africa. The paper discusses an alternative – unsupervised learning supported by functional genomic analysis. Recent work in West Africa on sorghum, African rice and white yam is described. Requirements for laboratory-based analytical support are outlined. A science-backed ‘farmer first’ approach – while feasible – will require a shift in policy and funding by major investors.en_US
dc.identifier.citationInternational Journal of Technology Management 45(1-2): 196-214en_US
dc.identifier.urihttp://197.255.68.203/handle/123456789/1624
dc.language.isoenen_US
dc.publisherInternational Journal of Technology Managementen_US
dc.subjectSeed Systemen_US
dc.subjectFunctional Genomicen_US
dc.subjectFood Securityen_US
dc.subjectAfrican Riceen_US
dc.subjectActor Networksen_US
dc.subjectFarmer Knowledgeen_US
dc.subjectSupervised Learningen_US
dc.subjectUnsupervised Learningen_US
dc.subjectWest Africaen_US
dc.titleSeed systems for African food security: linking molecular genetics and cultivator knowledge in West Africaen_US
dc.typeArticleen_US

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