Bayesian approach increases accuracy when selecting cowpea genotypes with high adaptability and phenotypic stability
This study aimed to verify that a Bayesian approach could be used for the selection of upright cowpea genotypes with high adaptability and phenotypic stability, and the study also evaluated the efficiency of using informative and minimally informative a priori distributions. Six trials were conducte...
| Autores: | , , , , , , , , , |
|---|---|
| Tipo de documento: | artigo |
| Estado: | Versão publicada |
| Data de publicação: | 2016 |
| País: | Brasil |
| Recursos: | Universidade Federal de Viçosa (UFV) |
| Repositório: | LOCUS Repositório Institucional da UFV |
| Idioma: | inglês |
| OAI Identifier: | oai:locus.ufv.br:123456789/12023 |
| Acesso em linha: | http://dx.doi.org/10.4238/gmr.15017625 http://www.locus.ufv.br/handle/123456789/12023 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Vigna unguiculata L. Bayes factor Informative prior Genotype x environment interaction |
| Resumo: | This study aimed to verify that a Bayesian approach could be used for the selection of upright cowpea genotypes with high adaptability and phenotypic stability, and the study also evaluated the efficiency of using informative and minimally informative a priori distributions. Six trials were conducted in randomized blocks, and the grain yield of 17 upright cowpea genotypes was assessed. To represent the minimally informative a priori distributions, a probability distribution with high variance was used, and a meta-analysis concept was adopted to represent the informative a priori distributions. Bayes factors were used to conduct comparisons between the a priori distributions. The Bayesian approach was effective for selection of upright cowpea genotypes with high adaptability and phenotypic stability using the Eberhart and Russell method. Bayes factors indicated that the use of informative a priori distributions provided more accurate results than minimally informative a priori distributions. |
|---|