The rapid increase in the availability of genomic data has transformed plant breeding by enabling the prediction of complex traits directly from DNA markers. Genomic prediction provides a means to accelerate selection decisions, reduce phenotyping costs and shorten breeding cycles. Despite its promise, the practical implementation of genomic prediction remains challenging because prediction accuracy varies across datasets, populations and traits. Researchers must often evaluate multiple statistical and machine-learning approaches to identify the most suitable model, requiring substantial expertise and computational effort.
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