Diallel analysis to choose parents for black bean (Phaseolus vulgaris L.) breeding

Moura, Luciana Coelho de; Carneiro, P. C. S.; Vale, Naine Martins do; Barili, Leiri Daiane; Silva, Luzimar Campos da; Carneiro, José Eustáquio Souza; Cruz, Cosme Damião

doi:10.4238/gmr.15038574

Cited by 5 publications

(5 citation statements)

References 29 publications

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“…The significant effect of populations by the deviance analysis suggests that the variability among populations, for both characters, originates from the genetic difference between the parents. These results corroborate those of Moura et al (2016), who found a significant difference between the two groups of parents for grain yield and plant architecture in a diallel analysis study. Common bean plants with a desirable architecture are positively correlated with higher HD values.…”

Section: Deviance Analysis and Genetic Parameters Estimationsupporting

confidence: 90%

Selecting common bean breeding populations via mixed models

Paula¹,

Paula²,

Carneiro³

et al. 2019

Biosci. J.

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Choosing breeding populations in a common bean (Phaseolus vulgaris L.) breeding program via recurrent selection is a crucial step since it maximizes the effort to find superior inbred lines. The application of the mixed models methodology (REML/BLUP) in predicting breeding values has shown good results in animal and perennial crops breeding programs. Conversely, studies on the application of this methodology to annual crops are still scarce. The present work aimed to use the REML/BLUP methodology to select breeding populations of a common bean breeding program via recurrent selection. Thirty-five F 3 populations were evaluated. Individual plants data were assessed for grain yield and hypocotyl diameter, and the genetic potential of the population was estimated via the mixed models and the Jinks and Pooni's methodologies. A selection index was applied to the selection among and within population, considering both characters simultaneously, using the population and individual BLUP means. REML/BLUP has shown to be a feasible methodology to predict and select the potential of breeding populations, considering more than one character. Selecting individual plants within population provides positive genetic gain estimates for both characters. BLUP breeding values are fundamental to the choice of the number of populations and single plants to be conducted in a common bean breeding program via recurrent selection.

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Section: Deviance Analysis and Genetic Parameters Estimationsupporting

confidence: 90%

Selecting common bean breeding populations via mixed models

Paula¹,

Paula²,

Carneiro³

et al. 2019

Biosci. J.

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show abstract

“…This fact is relevant because the higher the coefficient of kinship between populations, the more difficult it is to discriminate them. For traits controlled by fewer genes, such as disease resistance, plant architecture, and grain appearance (Batista et al, 2017;Moura et al, 2016;Silva et al, 2013), lower variability between populations is expected because they share the same alleles from the common parent. Thus, all the variability between populations is conditioned to the noncommon parent.…”

Section: Discussion Genetic Effects Of the Modelmentioning

confidence: 99%

Selection of Superior Inbred Progenies toward the Common Bean Ideotype

Rocha¹,

Nunes²,

Carneiro³

et al. 2019

Agronomy Journal

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Core Ideas Partitioning of the progenies effect within populations has several advantages. FAI‐BLUP index capitalizes the progenies × growth seasons interaction. The selected inbreed progenies showed favorable genotypes for the target traits. Genetic breeding towards the common bean ideotype can accelerate the cultivar release. ABSTRACTThe goal of breeding programs is selection toward the ideal plant type. In this study, field experiments were performed to select common bean inbred progenies that maximize the probability of extracting superior lines. A total of 124 inbred progenies of three consecutive generations (F2:3, F2:4, and F2:5) were conducted in field experiments over three different environments (one generation in each environment). Seven different traits, related to disease severity, commercial acceptance grain, and yield, were evaluated by best linear unbiased prediction. This work underscored the importance of incorporating population information into the statistical model as a means of comparing progenies from different populations with higher efficacy, even when kinship information between populations is not available. Toward the common bean ideotype, 20 inbred progenies of greater potential were selected using the factor analysis and genotype‐ideotype distance (FAI‐BLUP) index. This index is based on the structural equation models by joining the factor analysis technique (exploratory factor analysis) with the ideotype design (confirmatory factor analysis). The predicted genetic gain was increased for all the traits in all generations. Selection strategies that capture the multitrait information capitalize the progenies × growth season interactions and are based on the ideotype, such as as the FAI‐BLUP index, have the potential for use in genetic breeding toward the common bean ideotype and can accelerate the release of more adapted cultivars.

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“…Therefore, the higher the F ST is, more important the population merit is for a given trait. Higher values of F ST of the populations for plant architecture and grain yield are associated with the genetic divergence among genitors, in which well‐yielded genitors were crossed with upright genitors in order to start a recurrent program for black beans (Moura et al., 2016). Despite the genitors being divergent for grain appearance, genetic variability among populations decreases after early selection for this trait, making the F ST the lowest.…”

Section: Discussionmentioning

confidence: 99%

Multipopulation recurrent selection: An approach with generation and population effects in selection of self‐pollinated progenies

et al. 2020

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Correlated information from different genetic sources is absent in most of annual self-pollinated crops using the recurrent selection strategy, which is a breeding strategy that improves crop traits consistently over years. In common bean (Phaseolus vulgaris L.) breeding programs, progenies coming from multiple biparental populations are evaluated across generations of inbred plants with the assumption that the data are not correlated. In this paper, in addition to the effects of progeny, we evaluate the effects of populations and generations and provide information for the selection process in a self-pollinated recurrent selection breeding program. Nineteen progenies were extracted from 20 breeding populations and evaluated at different sowing times across F 3:4 and F 3:5 generations. The evaluated traits were plant architecture, angular leaf spot resistance, grain appearance, and grain yield. Progenies were selected using three methods: means of progenies regardless of generation and population effects; the multigeneration index (MI), which considered the generation effect; and the selection index with parents, populations, progenies, and generations (SIPPPG). We showed that adding variation among progenies correctly weighted for different generations as well as variation among populations yield for an increase in genetic gain. Therefore, selection accuracies of the SIPPPG were the highest for all traits compared with those of MI and when generation and population effects were not considered.

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Diallel analysis to choose parents for black bean (Phaseolus vulgaris L.) breeding

Cited by 5 publications

References 29 publications

Selecting common bean breeding populations via mixed models

Selecting common bean breeding populations via mixed models

Selection of Superior Inbred Progenies toward the Common Bean Ideotype

Multipopulation recurrent selection: An approach with generation and population effects in selection of self‐pollinated progenies

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