Adaptability and stability of black bean genotypes with normal and early cycle

Author:

Ambrósio Moisés1,Santos Raiane Mariani1,Daher Rogério Figueiredo1,Santana Josefa Grasiela Silva1,Vidal Ana Kesia Faria1,Nascimento Maxwel Rodrigues1,Leite Cleudiane Lopes1,Souza Alexandre Gomes1,Freitasa Rafael Souza1,Stida Wanessa Francesconi1,Farias João Esdras Calaça1

Affiliation:

1. State Univ. of North Fluminense Darcy Ribeiro

Abstract

Abstract In the selection process of common bean genotypes with high yield performance associated with high adaptability and stability, accurate statistical procedures should be used, which promote greater precision in the comparison of means. In this context, the study aimed to select black bean genotypes of a normal and early cycle that simultaneously combine high yield, adaptability, and stability via non-parametric methods and mixed models. For this, two simultaneous trials were conducted in 2020 and 2021 in Campos dos Goytacazes - RJ. The first trial consisted of 14 black bean genotypes of the normal cycle; the second trial consisted of 14 black bean genotypes of the early cycle. The experimental design was a randomized block design with 14 normal-cycle and 14 early-cycle genotypes and three replications. After detecting the significant genotype-environment interaction (GxE), the adaptability and phenotypic stability of the genotypes were analyzed by the methods of the harmonic mean of the relative performance of genotypic values (HMRPGV), Annicchiarico (1992), Lin & Binns (1988), and stability index called WAASB (Weighted Average of Absolute Scores). The genotypes that gather adaptability and stability associated with high yield potential, sufficient for a recommendation for the state of Rio de Janeiro, are BRS Esteio, CNFP 19325 belonging to the normal group and BRS Campeiro, CNFP 17445, and CNFP 17466 belonging to the early group. The combined use of mixed model methodologies and non-parameter models enables a more accurate selection of the most promising genotypes.

Publisher

Research Square Platform LLC

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