Walter Guerra

WISER improves breeding value estimation by addressing population structure and genotype-environment confounding through spectral whitening, outperforming LS-means and BLUP across multiple species and traits.

WISER improves phenotype estimation in omics studies by correcting population structure, outperforming LS and BLUP across multiple species and datasets.

This study applies statistical and deep learning models to multi-environmental genomic prediction in apple, showing improved predictive ability for certain traits.

This study examines the genetic architecture and genomic prediction accuracy of 30 apple quantitative traits across six European locations, identifying novel associations and demonstrating the impact of genotype by environment interactions.

This paper uses genomic selection to predict apple fruit texture traits, achieving high accuracy by optimizing the training set size and composition.