Genotype selection for grain yield and quality based on multiple traits of common wheat (Triticum aestivum L.)

Tsenov, N.; Gubatov, T.; Yanchev, I.

doi:10.1007/s42976-020-00080-7

Cited by 11 publications

(7 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This method is comprehensive and effective, as it ranks genotypes graphically based on the combined grain yield and the level of various evaluated agronomic traits, while showing the strengths and weaknesses of the tested genotypes. Because it does not involve subjective weights and cutting points, the analysis result of the GYT biplot is objective [23,45]. Among summer maize, high-yielding and stable maize genotypes are the first choice for farmers.…”

Section: Correspondence Among the Stability Indexesmentioning

confidence: 99%

A Study on Genotype-by-Environment Interaction Analysis for Agronomic Traits of Maize Genotypes Across Huang-Huai-Hai Region in China

Yue¹,

Wei²,

Xie³

et al. 2022

Phyton

View full text Add to dashboard Cite

Facing the trend of increasing population, how to increase maize grain yield is a very important issue to ensure food security. In this study, 28 nationally approved maize hybrids were evaluated across 24 different climatic conditions for two consecutive years (2018)(2019). The purpose of this study was to select high-yield with stable genotypes and identify important agronomic traits for maize breeding program improvement. The results of this study showed that the genotype Â environment interaction effects of the 12 evaluated agronomic traits was highly significant (P < 0.001). We introduced a novel multi-trait genotype-ideotype distance index (MGIDI) to select genotypes based on multiple agronomic traits. The selection process exhibited by this method is unique and easy to understand, so the MGIDI index will have more and more important applications in future multi-environment trials (METs) research. The genotypes selected by the MGIDI index were G22, G10, G12 and G1 as the high yielding and stable genotypes. The parents of these selected genotypes have the ability to play a greater role as the basic germplasm in the breeding process. A new form of genotype (G) main effects and genotype (G) -by-environment (E) interaction (GGE) technician, genotype Ã yield Ã trait (GYT) biplot, based on multiple traits for genotypes selection was also applied in this study. The GYT biplot ranked genotypes by combining grain yield with other evaluated agronomic traits, and displayed the distribution of their traits, namely strengths and weaknesses.

show abstract

Section: Correspondence Among the Stability Indexesmentioning

confidence: 99%

A Study on Genotype-by-Environment Interaction Analysis for Agronomic Traits of Maize Genotypes Across Huang-Huai-Hai Region in China

Yue¹,

Wei²,

Xie³

et al. 2022

Phyton

View full text Add to dashboard Cite

show abstract

“…The GYT biplot approach has been adopted in multi-trait selection for various crops (Boureima and Abdoua, 2019 ; de Oliveira et al, 2019 ; Hamid et al, 2019 ; Mohammadi, 2019 ; Gouveia et al, 2020 ; Mahmoud et al, 2020 ; Merrick et al, 2020 ; Badu-Apraku et al, 2021 ; Sofi et al, 2021 ; Tsenov et al, 2021 ; Xu et al, 2021 ).…”

Section: Selection For Multiple Traitsmentioning

confidence: 99%

A Systematic Narration of Some Key Concepts and Procedures in Plant Breeding

Yan

2021

Front. Plant Sci.

View full text Add to dashboard Cite

The goal of a plant breeding program is to develop new cultivars of a crop kind with improved yield and quality for a target region and end-use. Improved yield across locations and years means better adaptation to the climatic, soil, and management conditions in the target region. Improved or maintained quality renders and adds value to the improved yield. Both yield and quality must be considered simultaneously, which constitutes the greatest challenge to successful cultivar development. Cultivar development consists of two stages: the development of a promising breeding population and the selection of the best genotypes out of it. A complete breeder's equation was presented to cover both stages, which consists of three key parameters for a trait of interest: the population mean (μ), the population variability (σG), and the achieved heritability (h2 or H), under the multi-location, multi-year framework. Population development is to maximize μσG and progeny selection is to improve H. Approaches to improve H include identifying and utilizing repeatable genotype by environment interaction (GE) through mega-environment analysis, accommodating unrepeatable GE through adequate testing, and reducing experimental error via replication and spatial analysis. Related concepts and procedures were critically reviewed, including GGE (genotypic main effect plus genotype by environment interaction) biplot analysis, GGE + GGL (genotypic main effect plus genotype by location interaction) biplot analysis, LG (location-grouping) biplot analysis, stability analysis, spatial analysis, adequate testing, and optimum replication. Selection on multiple traits includes independent culling and index selection, for the latter GYT (genotype by yield*trait) biplot analysis was recommended. Genomic selection may provide an alternative and potentially more effective approach in all these aspects. Efforts were made to organize and comment on these concepts and procedures in a systematic manner.

show abstract

“…Similarly, the recently proposed genotype × yield × trait (GYT) biplots (Yan and Freǵeau-Reid, 2018) offer an effective and comprehensive analysis method for the evaluation of genotypes based on the combined grain yield and various evaluated agronomic traits. However, the method determines the influencing factors from yield-trait combinations by a classical linear multivariate model under diversified environments, but it does not involve any subjective weights and cutting points that provide a better picture of the strengths and weaknesses of test genotypes (Yan and Freǵeau-Reid, 2018;Kendal, 2019;Nikolay et al, 2020;Singamsetti et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2023

View full text Add to dashboard Cite

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.

show abstract

Genotype selection for grain yield and quality based on multiple traits of common wheat (Triticum aestivum L.)

Cited by 11 publications

References 29 publications

A Study on Genotype-by-Environment Interaction Analysis for Agronomic Traits of Maize Genotypes Across Huang-Huai-Hai Region in China

A Study on Genotype-by-Environment Interaction Analysis for Agronomic Traits of Maize Genotypes Across Huang-Huai-Hai Region in China

A Systematic Narration of Some Key Concepts and Procedures in Plant Breeding

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

Contact Info

Product

Resources

About