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Agro-Physiological Indices and Multidimensional Analyses for Detecting Heat Tolerance in Wheat Genotypes

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Increasing atmospheric temperature can significantly reduce global wheat productivity; despite a mounting demand for wheat grain supplies. Developing genotypes with superior performance under current and future hot climates is a key challenge for wheat breeders. Multidimensional tools have supported plant breeders in increasing the genetic stability rate of agro-physiological indices that influence wheat productivity. We used 25 agro-physiological indices to classify 20 bread wheat genotypes for their heat stress tolerance. Agro-physiological indices and multidimensional analyses to identify differences in genetic and phenotypic were used, combining these analyses to reach selection criteria of accurate and credible. The 25 studied indices reflected high genotypic and environmental variations. We used 16 indices, which have brought together high heritability and genetic gain as indicators for screening heat-tolerant genotypes. Based on the seven principal comprehensive indices of (D value), wheat genotypes were classified into three highly heat-tolerant, four heat-tolerant, six moderately heat-tolerant, five heat-sensitive, and two highly heat-sensitive wheat genotypes. Based on four critical indices [grain yield (GY), grain-filling duration (GFD), spike length (SL) and canopy temperature (CT)] obtained from stepwise multiple linear regression (SMLR), the genotypes were grouped as four genotypes highly heat-tolerant, six heat-tolerant, two moderately heat-tolerant, four heat-sensitive and four highly heat-sensitive. The classification D value and SMLR distances were significantly correlated based on the Mantel test, with a perfect match in nine genotypes. SMLR indicated that a mathematical equation for the evaluation of wheat heat tolerance was established: GY = 0.670 + 0.504 × GFD + 0.334 × SL − 0.466 × CT (R2 = 0.739; average prediction accuracy of 94.12%). SMLR-based classification of wheat genotypes for heat tolerance was further verified through discriminant analysis, which showed that prior and posterior classification was identical in eighteen genotypes. Cross-validation showed that prior and posterior classification was identical in thirteen genotypes. Based on this study, we can recommend tolerated new wheat lines (DHL25, DHL05, DHL23 and DHL08) and cultivar Pavone-76 as a promising genetic source for heat-tolerant breeding programs.
Title: Agro-Physiological Indices and Multidimensional Analyses for Detecting Heat Tolerance in Wheat Genotypes
Description:
Increasing atmospheric temperature can significantly reduce global wheat productivity; despite a mounting demand for wheat grain supplies.
Developing genotypes with superior performance under current and future hot climates is a key challenge for wheat breeders.
Multidimensional tools have supported plant breeders in increasing the genetic stability rate of agro-physiological indices that influence wheat productivity.
We used 25 agro-physiological indices to classify 20 bread wheat genotypes for their heat stress tolerance.
Agro-physiological indices and multidimensional analyses to identify differences in genetic and phenotypic were used, combining these analyses to reach selection criteria of accurate and credible.
The 25 studied indices reflected high genotypic and environmental variations.
We used 16 indices, which have brought together high heritability and genetic gain as indicators for screening heat-tolerant genotypes.
Based on the seven principal comprehensive indices of (D value), wheat genotypes were classified into three highly heat-tolerant, four heat-tolerant, six moderately heat-tolerant, five heat-sensitive, and two highly heat-sensitive wheat genotypes.
Based on four critical indices [grain yield (GY), grain-filling duration (GFD), spike length (SL) and canopy temperature (CT)] obtained from stepwise multiple linear regression (SMLR), the genotypes were grouped as four genotypes highly heat-tolerant, six heat-tolerant, two moderately heat-tolerant, four heat-sensitive and four highly heat-sensitive.
The classification D value and SMLR distances were significantly correlated based on the Mantel test, with a perfect match in nine genotypes.
SMLR indicated that a mathematical equation for the evaluation of wheat heat tolerance was established: GY = 0.
670 + 0.
504 × GFD + 0.
334 × SL − 0.
466 × CT (R2 = 0.
739; average prediction accuracy of 94.
12%).
SMLR-based classification of wheat genotypes for heat tolerance was further verified through discriminant analysis, which showed that prior and posterior classification was identical in eighteen genotypes.
Cross-validation showed that prior and posterior classification was identical in thirteen genotypes.
Based on this study, we can recommend tolerated new wheat lines (DHL25, DHL05, DHL23 and DHL08) and cultivar Pavone-76 as a promising genetic source for heat-tolerant breeding programs.

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