title: Bayesian approach increases accuracy when selecting cowpea genotypes with high adaptability and phenotypic stability.
abstract: 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.
authors.affiliation: Departamento de Estatística, Universidade Federal de Viçosa, Viçosa, MG, Brasil.
authors.forename: L M A
authors.initials: LM
authors.lastname: Barroso
authors.affiliation: Departamento de Fitotecnia, Universidade Estadual de Mato Grosso do Sul, Aquidauana, MS, Brasil.
authors.forename: P E
authors.initials: PE
authors.lastname: Teodoro
authors.affiliation: Departamento de Estatística, Universidade Federal de Viçosa, Viçosa, MG, Brasil.
authors.forename: M
authors.initials: M
authors.lastname: Nascimento
authors.affiliation: Departamento de Fitotecnia, Universidade Estadual de Mato Grosso do Sul, Aquidauana, MS, Brasil.
authors.forename: F E
authors.initials: FE
authors.lastname: Torres
authors.affiliation: Departamento de Melhoramento Genético, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos dos Goytacazes, RJ, Brasil.
authors.forename: A
authors.initials: A
authors.lastname: Dos Santos
authors.affiliation: Departamento de Fitotecnia, Universidade Estadual de Mato Grosso do Sul, Aquidauana, MS, Brasil.
authors.forename: A M
authors.initials: AM
authors.lastname: Corrêa
authors.affiliation: Embrapa Meio-Norte, Teresina, PI, Brasil.
authors.forename: E
authors.initials: E
authors.lastname: Sagrilo
authors.affiliation: Departamento de Fitotecnia, Universidade Estadual de Mato Grosso do Sul, Aquidauana, MS, Brasil.
authors.forename: C C G
authors.initials: CC
authors.lastname: Corrêa
authors.affiliation: Departamento de Fitotecnia, Universidade Estadual de Mato Grosso do Sul, Aquidauana, MS, Brasil.
authors.forename: F A
authors.initials: FA
authors.lastname: Silva
authors.affiliation: Embrapa Agropecuária-Oeste, Dourados, MS, Brasil.
authors.forename: G
authors.initials: G
authors.lastname: Ceccon
mesh_terms: D000222:Adaptation, Physiological; D001499:Bayes Theorem; D059647:Gene-Environment Interaction; D005838:Genotype; D000070658:Vigna / Q000235:genetics* / Q000502:physiology