Genomic prediction in a large African maize population

dc.creatorEdriss, V.
dc.creatorYanxin Gao
dc.creatorZhang, X.
dc.creatorJumbo, M.B.
dc.creatorMakumbi, D.
dc.creatorOlsen, M.
dc.creatorCrossa, J.
dc.creatorPackard, K.C.
dc.creatorJannink, J.L.
dc.date2017-12-18T18:34:58Z
dc.date2017-12-18T18:34:58Z
dc.date2017
dc.date.accessioned2023-07-17T20:01:49Z
dc.date.available2023-07-17T20:01:49Z
dc.identifierhttp://hdl.handle.net/10883/19104
dc.identifier10.2135/cropsci2016.08.0715
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7511026
dc.descriptionGenomic prediction (GP) combines genomewide marker data with phenotypic data in a training population to predict the genomic estimated breeding values of untested individuals in a relevant testing population. Our objective was to evaluate the effects of p
dc.description2361-2371
dc.formatPDF
dc.languageEnglish
dc.publisherCrop Science Society of America (CSSA)
dc.relationhttps://dl.sciencesocieties.org/publications/cs/supplements/57/2361-supplement1.pdf
dc.rightsCIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, p
dc.rightsOpen Access
dc.source57
dc.sourceCrop Science
dc.subjectAGRICULTURAL SCIENCES AND BIOTECHNOLOGY
dc.subjectMAIZE
dc.subjectGENOMICS
dc.subjectFORECASTING
dc.subjectPOPULATION STRUCTURE
dc.titleGenomic prediction in a large African maize population
dc.typeArticle
dc.coverageUSA


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