Use este identificador para citar ou linkar para este item: http://repositorio.ufla.br/jspui/handle/1/33240
Título: Genetic progress in popcorn recurrent selection by a multivariate mixed-model approach
Título(s) alternativo(s): Progresso genético na seleção recorrente em milho pipoca via abordagem de modelos mistos multivariado
Palavras-chave: Plant breeding
Grain yield
Popping expansion
Melhoramento de plantas
Rendimento de grão
Capacidade de expansão
Data do documento: Abr-2018
Editor: Editora UFLA
Citação: EMATNÉ, H. J. et al. Genetic progress in popcorn recurrent selection by a multivariate mixed-model approach. Ciência e Agrotecnologia, Lavras, v. 42, n. 2, p. 159-167, Mar./Apr. 2018. DOI: 10.1590/1413-70542018422016817.
Resumo: Recurrent selection is a viable alternative for popcorn breeding. However, frequent verification of progress attained is required. The aim of this study was to estimate the genetic progress attained for popping expansion (PE) and grain yield (GY) after four cycles of recurrent selection and to compare this progress with the expected progress estimated at the end of each cycle while considering the genetic relationships between the progenies via univariate and multivariate mixed-model approaches. To estimate the genetic parameters and gains from indirect selection, cycles 1, 2, 3, and 4 of a UFLA population were used. To estimate the genetic gains achieved, the following cycles were used: UFLA (original) and cycles 0, 1, 2, 3, and 4, evaluated in three environments. The multivariate approach provided more accurate estimates than did the univariate approach. There was genetic gain for PE in the recurrent selection program. In contrast, gain was not observed for GY using the different estimation strategies.
URI: http://repositorio.ufla.br/jspui/handle/1/33240
Aparece nas coleções:DBI - Artigos publicados em periódicos

Arquivos associados a este item:
Arquivo Descrição TamanhoFormato 
ARTIGO_Genetic progress in popcorn recurrent selection by a multivariate mixed-model approach.pdf531,39 kBAdobe PDFVisualizar/Abrir


Este item está licenciada sob uma Licença Creative Commons Creative Commons