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Campo DC | Valor | Lengua/Idioma |
---|---|---|
dc.contributor.author | ARAÚJO, M. dos S. | |
dc.contributor.author | CHAVES, S. F. da S. | |
dc.contributor.author | SILVA, K. J. D. e | |
dc.contributor.author | DIAS, L. A. dos S. | |
dc.contributor.author | ROCHA, M. de M. | |
dc.date.accessioned | 2023-03-23T18:51:08Z | - |
dc.date.available | 2023-03-23T18:51:08Z | - |
dc.date.created | 2023-03-23 | |
dc.date.issued | 2023 | |
dc.identifier.citation | Agronomy Journal, p. 1-9, Feb. 2023. On line. | |
dc.identifier.uri | http://www.alice.cnptia.embrapa.br/alice/handle/doc/1152658 | - |
dc.description | In cowpea breeding, multi-environment trials are conducted to select lines withhigh yield. The occurrence of genetic and/or statistical imbalance is common inthese experiments, in addition to the possibility of (co)variance between genetic andnon-genetic effects. We explore the restricted maximum likelihood/best linear unbi-ased prediction features to select the model with the most appropriated covariancestructure and compare the results with the traditional model (homogenous variancesand no covariances). | |
dc.language.iso | eng | |
dc.rights | openAccess | |
dc.subject | Caupi | |
dc.title | Modeling covariance structures for genetic and non-genetic effectsin cowpea multi-environment trials. | |
dc.type | Artigo de periódico | |
dc.subject.thesagro | Melhoramento Genético Vegetal | |
dc.subject.thesagro | Vigna Unguiculata | |
dc.subject.thesagro | Rendimento | |
riaa.ainfo.id | 1152658 | |
riaa.ainfo.lastupdate | 2023-03-23 | |
dc.contributor.institution | MAURÍCIO DOS SANTOS ARAÚJO, UNIVERSIDADE FEDERAL DE VIÇOSA; SAULO FABRÍCIO DA SILVA CHAVES, UNIVERSIDADE FEDERAL DE VIÇOSA; KAESEL JACKSON DAMASCENO E SILVA, CPAMN; LUIZ ANTÔNIO DOS SANTOS DIAS, UNIVERSIDADE FEDERAL DE VIÇOSA; MAURISRAEL DE MOURA ROCHA, CPAMN. | |
Aparece en las colecciones: | Artigo em periódico indexado (CPAMN)![]() ![]() |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | |
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ModelingCovarianceStructuresGeneticNonGeneticEffectsCowpeaAJ2023.pdf | 7.71 MB | Adobe PDF | ![]() Visualizar/Abrir |