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| MORAIS JÚNIOR, O. P.; DUARTE, J. B.; BRESEGHELLO, F.; COELHO, A. S. G.; BORBA, T. C. O.; AGUIAR, J. T.; NEVES, P. C. F.; MORAIS, O. P.. |
| In genomic recurrent selection programs of self-pollinated crops, additive genetic effects (breeding values) are effectively relevant for selection of superior progenies as new parents. However, considering additive and nonadditive genetic effects can improve the prediction of genome-enhanced breeding values (GEBV) of progenies, for quantitative traits. In this study, we assessed the magnitude of additive and nonadditive genetic variances for eight key traits in a rice population under recurrent selection, using marker-based relationship matrices. We then assessed the goodness-to-fit, bias, stability and accuracy of prediction for breeding values and total (additive plus nonadditive) genetic values, in five genomic best linear unbiased prediction (GBLUP)... |
| Tipo: Artigo em periódico indexado (ALICE) |
Palavras-chave: Quantitative traits; Genetic architecture; Predictive accuracy; GBLUP models; Arroz; Oryza sativa; Melhoramento genético vegetal; Seleção recorrente; Rice; Plant breeding; Variance components. |
| Ano: 2017 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1086472 |
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