Enhancing prediction accuracy of key biomass partitioning traits in wheat using multi-kernel genomic prediction models integrating secondary traits and environmental covariates.

Abstract excerpt

Achieving significant genetic gains in grain yield (GY) in wheat (Triticum aestivum L.) requires optimization of the key biomass partitioning traits such as spike partitioning index (SPI) and fruiting efficiency (FE). However, traditional manual phenotyping of these traits is labor-intensive and destructive, making it unsuitable for evaluating large germplasm panels. This study developed genomic prediction models...

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