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

Ribeiro, Nerinéia Dalfollo; Maziero, Sandra Maria; Santos, Guilherme Godoy dos; Santos, Greice Godoy dos

doi:10.1590/1678-992x-2021-0160

Cited by 3 publications

(2 citation statements)

References 22 publications

(46 reference statements)

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“…A significant genotype effect was observed for nine of the 17 traits evaluated (Table 1), evidencing the existence of genetic variability between the common bean lines and cultivars for most of the agronomic traits. Broad genetic variability for plant architecture and yield traits has been described for common bean genotypes (Arteaga et al, 2019;Boros et al, 2014;Delfini et al, 2017;Moura et al, 2013;Nadeem et al, 2020;Ribeiro et al, 2022;Soltani et al, 2016). However, ten traits exhibited a significant genotype × environment interaction effect, which evidences that the common bean genotypes showed variation for most plant architecture and yield traits when grown in different environments, thereby confirming previously published results (Arteaga et al, 2019;Boros et al, 2014;Delfini et al, 2017;Moura et al, 2013;Nadeem et al, 2020;Ribeiro et al, 2018Ribeiro et al, , 2022Soltani et al, 2016).…”

Section: Analysis Of Variance and Multicollinearity Diagnosticssupporting

confidence: 84%

“…Broad genetic variability for plant architecture and yield traits has been described for common bean genotypes (Arteaga et al, 2019;Boros et al, 2014;Delfini et al, 2017;Moura et al, 2013;Nadeem et al, 2020;Ribeiro et al, 2022;Soltani et al, 2016). However, ten traits exhibited a significant genotype × environment interaction effect, which evidences that the common bean genotypes showed variation for most plant architecture and yield traits when grown in different environments, thereby confirming previously published results (Arteaga et al, 2019;Boros et al, 2014;Delfini et al, 2017;Moura et al, 2013;Nadeem et al, 2020;Ribeiro et al, 2018Ribeiro et al, , 2022Soltani et al, 2016). These results suggest that taking into consideration the environmental variability between growing seasons and years in the exact location where the experiments were conducted can increase the efficiency of indirect selection for grain yield in common bean lines.…”

Section: Analysis Of Variance and Multicollinearity Diagnosticsmentioning

confidence: 99%

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Environmental variability in indirect selection for grain yield in common bean lines

Ribeiro

Maziero

2023

Sci. agric. (Piracicaba, Braz.)

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An approach to the number of experiments that should be used in correlation analyses aimed at increasing efficiency in indirect selection for grain yield is unprecedented for common bean (Phaseolus vulgaris L.). We hypothesize that trait correlation estimates vary in response to the growing environment. This study was undertaken to investigate the correlations between plant architecture and yield traits in common bean lines and to determine the minimum number of experiments required by Pearson's linear correlation analysis to increase efficiency in indirect selection for grain yield. Seventeen common bean genotypes were evaluated for 17 agronomic traits in four experiments. Pearson's linear correlation analyses were carried out using data from individual experiments and different combinations of growing seasons and years. Ten out of the 17 agronomic traits showed a significant genotype × environment interaction effect, meaning that common bean genotypes exhibited variation for most of the traits evaluated in different growing seasons and years, which resulted in changes in the correlation estimates between these traits. Pearson's linear correlation estimates obtained between plant architecture and yield traits varied in significance, magnitude, and sign when data from individual experiments and combinations of growing seasons and years were considered. The number of grains per pod is the most promising agronomic trait used in indirect selection for grain yield in common bean lines. Data from at least three experiments should be used in Pearson's linear correlation analysis to achieve greater efficiency in indirect selection for grain yield in common bean lines.

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Section: Analysis Of Variance and Multicollinearity Diagnosticssupporting

confidence: 84%

Section: Analysis Of Variance and Multicollinearity Diagnosticsmentioning

confidence: 99%

Environmental variability in indirect selection for grain yield in common bean lines

Ribeiro

Maziero

2023

Sci. agric. (Piracicaba, Braz.)

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Genetic gain for mineral concentration in common bean cultivars released by the Southern Brazilian Common-Bean Network

Ribeiro,

Maziero

2024

Euphytica

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Simultaneous selection for architectural and yield traits in common bean lines considering environmental variability

Ribeiro

Maziero

2023

Rev. Caatinga

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Simultaneous selection for plant architecture and yield traits will be more efficient if a minimum number of experiments is established, but no such definition has been made for common bean. The objectives of this study were to select superior common bean lines for several plant architecture and yield traits and identify the minimum number of experiments that provide greater efficiency in simultaneous selection for agronomic traits. Twelve plant architecture and five yield traits of common bean lines were evaluated in four experiments. Analysis of variance and selection index (multiplicative) were carried out using data from individual experiments I (2016 rainy), II (2017 dry), III (2017 rainy), and IV (2018 dry-season crops), or data from two (I and II), three (I, II, and III), and four (I, II, III, and IV) experiments. Most agronomic traits showed a significant genotype × experiment interaction effect. The use of data from individual experiments resulted in variable heritability and genetic gain estimates and in the selection of different common bean genotypes for each growing environment. However, data from three or four experiments allowed 100% of coincidence in the selection of four superior common bean genotypes: LP 09-33, BRS Valente, Pérola, and Carioca. Data from at least three experiments should be used to select superior common bean lines for plant architecture and yield traits to increase the efficiency of simultaneous selection.

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

Cited by 3 publications

References 22 publications

Environmental variability in indirect selection for grain yield in common bean lines

Environmental variability in indirect selection for grain yield in common bean lines

Genetic gain for mineral concentration in common bean cultivars released by the Southern Brazilian Common-Bean Network

Simultaneous selection for architectural and yield traits in common bean lines considering environmental variability

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