Effectiveness of breeding selection for grain quality in common bean

Abstract

The aims of this study were to investigate the genetic variability and the genotype × environment interaction for quality and yield traits in common bean (Phaseolus vulgaris L.), to evaluate the degree of informativeness of the evaluations of grain quality in only one environment, to estimate genetic parameters for grain quality traits, and to select lines with superior grain quality. We evaluated 81 carioca common bean lines in preliminary line trials in several environments for nutritional, technological, and commercial quality and selected the 20 superior lines, which were evaluated in validation trials in nine environments. Individual and combined ANOVAs were performed for all the traits. Correlations were estimated between Fe and Zn concentrations and yield; adaptability and phenotypic stability were analyzed; and superior genotypes were selected based on the Mulamba & Mock index. It is possible to increase the Fe, Zn, and crude protein concentrations and reduce cooking time; however, increasing crude fiber is a challenge. Preliminary evaluation of the quality traits in only one environment was effective and sufficient for selection of genotypes superior in Fe concentration, crude fiber, crude protein, and cooking time; and genetic gains can be obtained from selection for these traits. Genetic and phenotypic correlations were observed between Fe and Zn concentrations. The lines CNFC 16627, CNFC 16518, CNFC 16602, CNFC 16615, and CNFC 16520 are superior based on the selection index and are recommended for breeding for grain quality in carioca common bean.

Selection strategies for identifying fast cooking, mineral-biofortified bean cultivars with high agronomic performance

“…Therefore, for none of the economic weights associated with the ranksum index was it possible to obtain favorable genetic gains in the selection of all evaluated traits, confirming previous results described for the selection of superior common bean cultivars (Ribeiro et al, 2019a, b;Ribeiro and Mezzomo, 2020). The rank-sum index was also used for ranking the common bean genotypes regarding the traits analyzed (Dias et al, 2020;Silva et al, 2018;Zanottti et al, 2020). The genotypes classified in the first positions were not superior for all the determined traits, which constituted a limitation in the use of the rank-sum index for simultaneous selection in commonbean breeding programs.…”

“…A significant G × E interaction was observed for all traits, except for the number of pods per plant and potassium concentration, which showed a significant genotype effect (Table 1). A significant G × E interaction had been previously reported for agronomic traits (Dias et al, 2020;Maziero et al, 2015;Ribeiro et al, 2018Ribeiro et al, , 2019a, cooking time (Arns et al, 2018;Dias et al, 2020; Steckling et al, 2017) and mineral concentration (Hossain et al, 2013;Steckling et al, 2017) in experiments with common bean genotypes. Thus, there is genetic variability in agronomic traits, cooking time and mineral concentration, which indicates the possibility of selecting superior common bean genotypes.…”

“…This is because direct selection allowed for a high genetic gain for traits analyzed individually, but caused undesirable changes in other important traits for selection (Jost et al, 2012;Maziero et al, 2015). Selection indices, in turn, allowed for the identification of superior common bean cultivars for several traits (Arns et al, 2018;Bertoldo et al, 2010;Dias et al, 2020;Gomes et al, 2018;Jost et al, 2012;Maziero et al, 2015;Ribeiro et al, 2019a;Silva et al, 2018;Zanotti et al, 2020), thereby enhancing the efficiency of breeding programs.…”

Multivariate genomic analysis and optimal contributions selection predicts high genetic gains in cooking time, iron, zinc, and grain yield in common beans in East Africa

“…(2014) identified some genotypes with superior GY and Fe despite a weak negative correlation between these traits. Phenotypic and genetic correlations of GY with Fe and Zn thus appear to be specific to experimental populations and environments (Dias et al., 2021; Ribeiro, Jost et al., 2014), and phenotypic correlations are not fully translated into genotypic correlations (Searle, 1961) as we observed in our study (Table 3).…”

“…(2015) also reported a positive correlation between Zn and GY, but a negative correlation between Fe and GY. Other studies report weak negative correlation or no correlation between Fe or Zn with GY (Dias et al., 2021; Jost et al., 2013; Ribeiro, Jost et al, 2014). Ribeiro, Jost et al.…”