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dc.contributor.authorOLIVEIRA, T. R. A. de
dc.contributor.authorCARVALHO, H. W. L. de
dc.contributor.authorNASCIMENTO, M.
dc.contributor.authorSUELA, M. M.
dc.contributor.authorCARDOSO, M. J.
dc.contributor.authorOLIVEIRA, G. H. F.
dc.date.accessioned2023-11-27T18:46:41Z-
dc.date.available2023-11-27T18:46:41Z-
dc.date.created2023-11-27
dc.date.issued2023
dc.identifier.citationCrop Breeding and Applied Biotechnology, v. 23, n. 3, e44692334, 2023.
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1158738-
dc.descriptionAlthough maize is one of the main crops in the Northeast region, yield is still considered low when compared to other regions. One of the main solutions to increasing yield is the selection of cultivars adapted to the conditions of the Northeast region. Thus, the present study aims to use the Bayesian segmented regression model to evaluate the adaptability and stability of maize.
dc.language.isoeng
dc.rightsopenAccess
dc.subjectFator de Bayes
dc.subjectInteração genótipo x ambiente
dc.titleBayesian segmented regression model to evaluate the adaptability and stability of maize in Northeastern Brazil.
dc.typeArtigo de periódico
dc.subject.thesagroZea Mays
riaa.ainfo.id1158738
riaa.ainfo.lastupdate2023-11-27
dc.contributor.institutionTÂMARA REBECCA ALBUQUERQUE DE OLIVEIRA, UNIVERSIDADE ESTADUAL DO NORTE FLUMINENSE DARCY RIBEIRO; HELIO WILSON LEMOS DE CARVALHO, CPATC; MOYSES NASCIMENTO, UNIVERSIDADE FEDERAL DE VIÇOSA; MATHEUS MASSARIOL SUELA, UNIVERSIDADE FEDERAL DE VIÇOSA; MILTON JOSE CARDOSO, CPAMN; GUSTAVO HUGO FERREIRA OLIVEIRA UNIVERSIDADE FEDERAL DE SERGIPE, UNIVERSIDADE FEDERAL DE SERGIPE.
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