Patrice This

This study identifies a gradient of esca disease susceptibility across 46 grapevine cultivars over seven years, linking it to ecophysiological traits.

This study applies phenomic prediction to grapevine using spectra to predict 15 traits, finding comparable predictive ability to genomic prediction across traits and populations.

This study identifies new QTLs and improves prediction accuracy for multiple grapevine traits using a diverse panel and multi-SNP models.

This study evaluates across-population genomic prediction in grapevine for 15 traits, finding predictive abilities of 0.6 for cross means and 0.26 for individual values, suggesting potential for genomic selection in breeding.

The paper compares genomic prediction and QTL detection methods in grapevine under climate change, finding penalized regression methods like Elastic Net to be effective for prediction and QTL discovery.