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The purpose of this study was to characterize the genetic variability in 100 genotypes of the Active Germplasm Bank of common bean of the Federal University of Viçosa, by morphological descriptors, classify them in groups of genetic similarity and to identify the degree of relevance of descriptors of genetic divergence. The genotypes were evaluated based on 22 quantitative and qualitative morphological descriptors. The highyielding genotypes V 7936, Gold Gate, LM 95103904, 1829 S 349 Venezuela, and PF 9029975, CNFC 9454 and Fe 732015, with upright growth, have potential for use as parents in common bean breeding programs. By genetic divergence analysis, the genotypes were clustered in eight groups of genetic dissimilarity. By methods of principal components, 9 of the 22 descriptors were eliminated, for being redundant or little variable, suggesting that 10-20 morphological descriptors can be used in studies of characterization of genetic variation. [ABSTRACT FROM AUTHOR]

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We aimed to apply genomic information based on SNP (single nucleotide polymorphism) markers for the genetic evaluation of the traits "stay-green" (SG), plant architecture (PA), grain aspect (GA) and grain yield (GY) in common bean through Bayesian models. These models were compared in terms of prediction accuracy and ability for heritability estimation for each one of the mentioned traits. A total of 80 cultivars were genotyped for 377 SNP markers, whose effects were estimated by five different Bayesian models: Bayes A (BA), B (BB), C (BC), LASSO (BL) e Ridge regression (BRR). Although, prediction accuracies calculated by means of cross-validation have been similar within each trait, the BB model stood out for the trait SG, whereas the BRR was indicated for the remaining traits. The heritability estimates for the traits SG, PA, GA and GY were 0.61, 0.28, 0.32 and 0.29, respectively. In summary, the Bayesian methods applied here were effective and ease to be implemented. The used SNP markers can help in the early selection of promising genotypes, since incorporating genomic information increase the prediction accuracy of the estimated genetic merit. [ABSTRACT FROM AUTHOR]

The objective of this study was to estimate the genetic gain of two recurrent selection cycles in common bean breeding and identify families with the potential to generate superior lines. The base population, cycle zero (C0), was obtained by combining 20 carioca bean parents, populations with favorable phenotypes for several agronomically important traits. The parents were recombined in a circulant diallel scheme, in which each parent participated in two crosses, generating 20 populations. From these populations, families were derived and evaluated for three seasons in the generations F2:3, F2:4 and F2:5. The same procedures of recombination and evaluation in C0 were performed in cycle one (CI). The genetic gain for yield, estimated from the simultaneous evaluation of the 40 best families of each cycle, was 8.6%. Families with potential to generate superior lines to cultivar Pérola were identified, especially among the CI families. [ABSTRACT FROM AUTHOR]

This study was carried out for the purpose of estimating genetic progress after two cycles of recurrent selection in red bean breeding and of obtaining new lines. In cycle zero, F3:5 and F3:6 families were evaluated. In cycle one, the families were extracted in generation F5 and evaluated in generations F5:6 and F5:7. As the families were evaluated in different years and generations, the estimate of genetic progress was obtained by simultaneously evaluating the 30 best lines obtained at the end of each cycle in experiments conducted through three crop seasons. After two cycles of recurrent selection, genetic progress, in the mean value of the crop seasons, was 7.5% for grain yield, 7% for grain appearance, 33.4% for resistance to rust and 13.2% for resistance to angular leaf spot. Lines of red beans were obtained with potential for being included in future Value for Cultivation and Use (VCU) testing for Minas Gerais, Brazil. [ABSTRACT FROM AUTHOR]