CP25128The prediction of genetic values of chickpea genotypes in F4 generation by REML/BLUP and FAI–BLUP from mixed analysis models and feature importance ranking by boruta–random forest model
This paper presents a comprehensive review of the use of mixed analysis models in selection of chickpea genotypes. To determine feature importance and to select superior genotypes, mixed analysis models including REML/BLUP, PCA, boruta–random forest, FAI–BLUP and Ward’s clustering by coding in R and Python software were effective. These models offer alternatives to classical predictions of genetic values in plant breeding studies. These models may have a wide range of applications and may contribute to plant breeding.
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