Selection of maize hybrids: an approach with multi-trait, multi-environment, and ideotype-design

Peixoto, Marco Antônio; Coelho, Igor Ferreira; Evangelista, Jeniffer Santana Pinto Coelho; Santos, Suellen Sales de Oliveira; Alves, Rodrigo Silva; Pinto, Jefferson Fernando Naves; Reis, Edésio Fialho dos

doi:10.1590/1984-70332021v21n2a31

Cited by 2 publications

(5 citation statements)

References 28 publications

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“…The higher the commonality is, the more informative the variable is for the factor and, therefore, the factor in which it is inserted represents it. The average commonality is equivalent to the accumulated variance for the factors (Cruz et al., 2014; Peixoto et al., 2021; Rocha et al., 2018). The good association between the characteristics of the factors associated with high correlation and in the desirable sense, already mentioned, once again signal the efficiency in the selection by the FAI‐BLUP.…”

Section: Discussionmentioning

confidence: 99%

“…Although proposed only recently, the FAI‐BLUP index has already been used efficiently in (i) the evaluation and selection of sorghum hybrids for biomass increase and energy cogeneration (Oliveira et al., 2019; Silva et al., 2018); (ii) soybean selection for biodiesel production (Woyann et al., 2020); (iii) selection of superior common bean progenies (Rocha et al., 2019); (iv) selection of Jatropha curcas L. genotypes for bioenergetic purposes (Rodrigues et al., 2020); (v) selection of superior pumpkin genotypes with smaller size and higher seed yield for oil production (Oliveira et al., 2020); (vi) combined selection in maize (Peixoto et al., 2021); (vii) simultaneous selection of mangaba based on eleven agronomic traits (Almeida et al., 2021); (viii) selection of early soybean progenies that are more erect and have higher grain yield potential (Volpato et al., 2021); (ix) and selection of superior wheat genotypes for grain yield, tiller number and grain weight per plant (Meier et al., 2021).…”

Section: Discussionmentioning

confidence: 99%

“…The higher the commonality, the more informative the variable is for the factor and, therefore, the factor in which it is inserted represents it. The average commonality is equivalent to the accumulated variance for the factors (Cruz et al., 2014; Peixoto et al., 2021; Rocha et al., 2018).…”

Section: Methodsmentioning

confidence: 99%

“…The efficiency of this selection index has been reported for the improvement of different crops (Almeida et al, 2021;Meier et al, 2021;Oliveira et al, 2019Oliveira et al, , 2021Peixoto et al, 2021;Rocha et al, 2019;Silva et al, 2018;Volpato et al, 2021;Woyann et al, 2020). However, no references were found for the use of the FAI-BLUP index in the genetic improvement of grapevines.…”

Section: Crop Sciencementioning

confidence: 99%

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Multitrait selection in seedless grape hybrids in semiarid regions of Brazil

Carvalho

Pio

et al. 2023

Crop Science

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The absence of seeds has been one of the most valued traits in grapes (Vitis spp.) for fresh consumption. However, the simultaneous selection of superior genotypes for multiple traits is complex. The objective of this study was to select genotypes of superior seedless table grapes in semiarid regions of Brazil. Multiple traits were considered by using the factor analysis and genotype–ideotype best linear unbiased prediction (FAI‐BLUP) selection index. A total of 110 grape progenies from 24 crosses were evaluated for traits of agronomic interest. Each hybrid was represented by a single vine plant, without experimental design or repetition. The mixed‐model methodology was used to predict the breeding values. The FAI‐BLUP index was used to select superior genotypes based on factor analysis and the genotype–ideotype distance. Four factors explained the 11 characteristics studied, with a variability of 81.84%. Desirable gains were observed for 10 of the 11 traits evaluated. The FAI‐BLUP index allowed the selection of superior seedless table grape hybrids, which can be used in the genetic improvement of grapevines. In conclusion, we report the selection of seedless table grape hybrids for our study to advance in the table grape breeding program in Brazilian semiarid regions.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Crop Sciencementioning

confidence: 99%

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Multitrait selection in seedless grape hybrids in semiarid regions of Brazil

Carvalho

Pio

et al. 2023

Crop Science

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“…In that perspective, a novel multi-trait genotype-ideotype distance index (MGIDI) was proposed to select genotypes with desirable mean performances of multiple traits that overcome the fragility of classical linear indices (Olivoto and Nardino, 2021). A few previous attempts at multiple traits in the selection of maize hybrids with multi-environment data have been reported (Langner et al, 2019;Olivoto et al, 2021;Oliveira et al, 2020;Singamsetti et al, 2021;Peixoto et al, 2021;Shojaei et al, 2022;Yue et al, 2022c). The purpose of this research was mainly to select the promising maize hybrids based on multiple traits suitable for different moisture regimes including drought, waterlogging, and optimal conditions and across all moisture conditions.…”

Section: Introductionmentioning

confidence: 99%

Genetic gains in tropical maize hybrids across moisture regimes with multi-trait-based index selection

et al. 2023

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Unpredictable weather vagaries in the Asian tropics often increase the risk of a series of abiotic stresses in maize-growing areas, hindering the efforts to reach the projected demands. Breeding climate-resilient maize hybrids with a cross-tolerance to drought and waterlogging is necessary yet challenging because of the presence of genotype-by-environment interaction (GEI) and the lack of an efficient multi-trait-based selection technique. The present study aimed at estimating the variance components, genetic parameters, inter-trait relations, and expected selection gains (SGs) across the soil moisture regimes through genotype selection obtained based on the novel multi-trait genotype–ideotype distance index (MGIDI) for a set of 75 tropical pre-released maize hybrids. Twelve traits including grain yield and other secondary characteristics for experimental maize hybrids were studied at two locations. Positive and negative SGs were estimated across moisture regimes, including drought, waterlogging, and optimal moisture conditions. Hybrid, moisture condition, and hybrid-by-moisture condition interaction effects were significant (p ≤ 0.001) for most of the traits studied. Eleven genotypes were selected in each moisture condition through MGIDI by assuming 15% selection intensity where two hybrids, viz., ZH161289 and ZH161303, were found to be common across all the moisture regimes, indicating their moisture stress resilience, a unique potential for broader adaptation in rainfed stress-vulnerable ecologies. The selected hybrids showed desired genetic gains such as positive gains for grain yield (almost 11% in optimal and drought; 22% in waterlogging) and negative gains in flowering traits. The view on strengths and weaknesses as depicted by the MGIDI assists the breeders to develop maize hybrids with desired traits, such as grain yield and other yield contributors under specific stress conditions. The MGIDI would be a robust and easy-to-handle multi-trait selection process under various test environments with minimal multicollinearity issues. It was found to be a powerful tool in developing better selection strategies and optimizing the breeding scheme, thus contributing to the development of climate-resilient maize hybrids.

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Selection of maize hybrids: an approach with multi-trait, multi-environment, and ideotype-design

Cited by 2 publications

References 28 publications

Multitrait selection in seedless grape hybrids in semiarid regions of Brazil

Multitrait selection in seedless grape hybrids in semiarid regions of Brazil

Genetic gains in tropical maize hybrids across moisture regimes with multi-trait-based index selection

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