Adaptability and phenotypic stability of common bean genotypes through Bayesian inference

Abstract

ABSTRACT. This study used Bayesian inference to investigate the genotype x environment interaction in common bean grown in Mato Grosso do Sul State, and it 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 13 common bean 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 inference was effective for the selection of upright common bean 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. According to Bayesian inference, the EMGOPA-201, BAMBUÍ, CNF 4999, CNF 4129 A 54, and CNFv 8025 genotypes had specific adaptability to favorable environments, while the IAPAR 14 and IAC CARIOCA ETE genotypes had specific adaptability to unfavorable environments.

<b>Adaptability and stability assessment of bean cultivars of the carioca commercial group by a Bayesian approach

“…All genotypes showed values higher than 10 according to the Bayes factor (BF) analysis, indicating that the use of informative priors provides more accurate results (Table 6). These findings are also in agreement with those found by Nascimento et al (2011), Corrêa et al (2015), Couto et al (2015), and Teodoro et al (2015). However, the prior use of seven VCU analyses (Table 2) did not increase the precision of the analysis.…”

“…Cultivar analyses through M2 (weakly informative priors) showed that all cultivars presented wide adaptability, which was consistent with the findings of Nascimento et al (2011), Corrêa et al (2015), Couto et al (2015), and Teodoro et al (2015). Corrêa et al (2015) assessed the adaptability and stability of 13 carioca bean genotypes through the Bayesian approach in the analysis of Eberhart and Russell (1966), and found that when using weakly informative priors, genotypes became adaptable to favorable, unfavorable and wide environments. However, when assessed by weakly informative priors, all genotypes showed wide adaptability, indicating that not using prior information may attribute adaptability and stability to genotypes in several environments.…”

“…The analysis of Eberhart and Russell (1966), using the Bayesian approach, showed greater accuracy for genotype selection when compared to traditional methods such as those used for alfalfa (Nascimento et al, 2011), cowpea (Barroso et al, 2016;Teodoro et al, 2015), popcorn (Couto et al, 2015) and the common bean (Corrêa et al, 2015).…”

“…These experiments are performed in representative locations in a specific region and during periods that represent the region's climate variation to which a cultivar will be exposed (Barili et al, 2015a). Quantification of the genotype x environment (GE) interaction and adaptability and stability analyses have become of great relevance for cultivar recommendation (Carbonell et al, 2004;Torga et al, 2013;Corrêa et al, 2015).…”

Selection of common bean genotypes for the Cerrado/Pantanal ecotone via mixed models and multivariate analysis

“…In recent years, new approaches have been employed for quantifying GxE interactions, for example pattern analysis (Corrêa et al, 2016a), Bayesian statistics (Corrêa et al, 2016b), and computational intelligence (Corrêa et al, 2016c). However, one of the conditions for the use of these approaches is availability of data from a large number of environments (locations and/or times).…”