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Provedor de dados:  124
País:  Brazil
Título:  Genetic improvement of silage maize: predicting genetic gain using selection indexes and best linear unbiased prediction
Autores:  Crevelari,Jocarla Ambrosim
Pereira,Messias Gonzaga
Azevedo,Flávio Henrique Vidal
Vieira,Ricardo Augusto Mendonça
Data:  2019-06-01
Ano:  2019
Palavras-chave:  Topcrosses
Tester
Hybrids
Yield
Resumo:  ABSTRACT The objective of this study was to evaluate four selection indexes and best linear unbiased prediction (BLUP) for predicting genetic gain in maize hybrids used for silage. The genetic gain was compared between four selection indexes and BLUP. Nineteen topcross hybrids and five controls were evaluated using a completely randomized block design with four replicates in two areas located in Campos dos Goytacazes and Itaocara, Rio de Janeiro, Brazil, in the growing season 2013-2014. Plant height, first ear height, average stem diameter, grain yield at the silage stage, and green mass yield were evaluated. The genetic gain was predicted using the selection indexes proposed by Pesek and Baker, Smith and Hazel, Mulamba and Mock, Willians, and BLUP. The index of Mulamba and Mock provided higher gain estimates for selecting hybrids. BLUP was efficient and selected hybrids with higher performance than hybrids obtained using the four selection indexes. Hybrids UENF-2205, UENF-2208, UENF-2209, and UENF-2210 presented better performance, indicating the high potential of these dent hybrids for silage production in the north and northwest regions of Rio de Janeiro.
Tipo:  Info:eu-repo/semantics/article
Idioma:  Inglês
Identificador:  http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902019000200197
Editor:  Universidade Federal do Ceará
Relação:  10.5935/1806-6690.20190023
Formato:  text/html
Fonte:  Revista Ciência Agronômica v.50 n.2 2019
Direitos:  info:eu-repo/semantics/openAccess
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