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F. R. Francisco

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Open access Jul 2026

Assessing the Role of Marker Density and Minor Allele Frequency on Machine Learning–Driven Genomic Selection Accuracy in Grapevine

The results suggest that compared with traditional GS models that rely on a genomic kinship matrix, ML-based approaches offer greater flexibility in feature reduction, and that GS integration is promising for enhancing breeding efficiency in grapevines.

F. R. Francisco, Geovani Luciano de Oliveira, Guilherme Francio Niederauer et al. · bioRxiv · 0 citations