Timothée Flutre

The paper develops a UAV-based imaging pipeline to predict plant density in wheat and pea crops, showing high heritability across diverse intercropping scenarios.

The paper develops a quantitative genetic model to analyze direct and social genetic effects in mono- and intercropped species, providing software for implementation and demonstrating its effectiveness through simulations.

This study investigates maize-bean intercropping through on-farm surveys and field assays, finding competition dominates over cooperation, primarily affecting bean yield and gene expression.

This study uses genomic prediction methods to improve grapevine breeding efficiency by identifying superior individuals for specific traits across two breeding programs.

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.

The paper assesses genetic diversity and structure of wild and cultivated chestnut in France, finding high diversity and evidence of admixture between French and Iberian populations.