Bayesian approach increases accuracy when selecting cowpea genotypes with high adaptability and phenotypic stability

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ABSTRACT. The aim of this study was to select erect cowpea (Vigna unguiculata L.) genotypes simultaneously for high adaptability, stability, and yield grain in Mato Grosso do Sul, Brazil using mixed models. We conducted six trials of different cowpea genotypes in 2005 and 2006 in Aquidauana, Chapadão do Sul, Dourados, and Primavera do Leste. The experimental design was randomized complete blocks with four replications and 20 genotypes. Genetic parameters were estimated by restricted maximum likelihood/best linear unbiased prediction, and selection was based on the harmonic mean of the relative performance of genetic values method using three strategies: selection based on the predicted breeding value, having considered the performance mean of the genotypes in all environments (no interaction effect); the performance in each environment (with an interaction effect); and the simultaneous selection for grain yield, stability, and adaptability. The MNC99542F-5 and MNC99-537F-4 genotypes could be grown in various environments, as they exhibited high grain yield, adaptability, and stability. The average heritability of the genotypes was moderate to high and the selective accuracy was 82%, indicating an excellent potential for selection.

Section: Resultssupporting

confidence: 77%

Simultaneous selection for cowpea (Vigna unguiculata L.) genotypes with adaptability and yield stability using mixed models

Fe¹,

Teodoro

Rodrigues

et al. 2016

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“…These results indicated that the use of informative a priori distributions provided more accurate results. Even though the a priori information for each genotype was based on a single study, similar results were found in studies that evaluated the adaptability and phenotypic stability of the dry matter yield of alfalfa genotypes (Nascimento et al, 2011), popcorn grain yield (Couto et al, 2015), and cowpea grain yield (Teodoro et al, 2015;Barroso et al, 2016). Therefore, it is expected that the results will be more precise in studies examining the stability and adaptability of other crops with more available information for meta-analysis.…”

Section: (Equation 25)mentioning

confidence: 53%

Adaptability and phenotypic stability of common bean genotypes through Bayesian inference

Correa¹,

Teodoro²,

Gonçalves³

et al. 2016

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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.

“…Several studies have already demonstrated the productive potential of cowpea in the Cerrado-Pantanal ecotone region (Santos et al, 2014b(Santos et al, ,c, 2015Teodoro et al, 2015a,b;Torres et al, 2015aTorres et al, ,b, 2016Barroso et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Genetic parameters and path analysis in cowpea genotypes grown in the Cerrado/Pantanal ecotone

Lopes¹,

Teodoro²,

Silva³

et al. 2017

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ABSTRACT. Estimating genetic parameters in plant breeding allows us to know the population potential for selecting and designing strategies that can maximize the achievement of superior genotypes. The objective of this study was to evaluate the genetic potential of a population of 20 cowpea genotypes by estimating genetic parameters and path analysis among the traits to guide the selection strategies. The trial was conducted in randomized block design with four replications. Its morphophysiological components, components of green grain production and dry grain yield were estimated from genetic use and correlations between the traits. Phenotypic correlations were deployed through path analysis into direct and indirect effects of morphophysiological traits and yield components on dry grain yield. There were significant differences (P < 0.01) between the genotypes 2 K.V. Lopes et al. Genetics and Molecular Research 16 (2): gmr16029559 for most the traits, indicating the presence of genetic variability in the population and the possibility of practicing selection. The population presents the potential for future genetic breeding studies and is highly promising for the selection of traits dry grain yield, the number of grains per pod, and hundred grains mass. A number of grains per green pod is the main determinant trait of dry grain yield that is also influenced by the cultivar cycle and that the selection for the dry grain yield can be made indirectly by selecting the green pod mass and green pod length.