Genotype x environment interaction

Artificial intelligence in the selection of common bean genotypes with high phenotypic stability

A. M. Corrêa, Teodoro, P. E., Gonçalves, M. C., Barroso, L. M. A., Nascimento, M., Santos, A., Torres, F. E., Corrêa, A. M., Teodoro, P. E., Gonçalves, M. C., Barroso, L. M. A., Nascimento, M., Santos, A., and Torres, F. E., Artificial intelligence in the selection of common bean genotypes with high phenotypic stability, vol. 15, p. -, 2016.

Artificial neural networks have been used for various purposes in plant breeding, including use in the investigation of genotype x environment interactions. The aim of this study was to use artificial neural networks in the selection of common bean genotypes with high phenotypic adaptability and stability, and to verify their consistency with the Eberhart and Russell method. Six trials were conducted using 13 genotypes of common bean between 2002 and 2006 in the municipalities of Aquidauana and Dourados. The experimental design was a randomized block with three replicates.

Adaptability and phenotypic stability of common bean genotypes through Bayesian inference

A. M. Corrêa, Teodoro, P. E., Gonçalves, M. C., Barroso, L. M. A., Nascimento, M., Santos, A., Torres, F. E., Corrêa, A. M., Teodoro, P. E., Gonçalves, M. C., Barroso, L. M. A., Nascimento, M., Santos, A., Torres, F. E., Corrêa, A. M., Teodoro, P. E., Gonçalves, M. C., Barroso, L. M. A., Nascimento, M., Santos, A., and Torres, F. E., Adaptability and phenotypic stability of common bean genotypes through Bayesian inference, vol. 15, p. -, 2016.

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.

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