Osval Antonio Montesinos-López

A novel matrix multiplication framework for modeling genotype-by-environment interaction in genomic prediction

This paper introduces a matrix multiplication framework for genotype-by-environment interaction in genomic prediction, showing improved accuracy over traditional methods.

ENVIROME-WIDE ASSOCIATIONS ENHANCE MULTI-YEAR GENOME-BASED PREDICTION OF HISTORICAL WHEAT BREEDING DATA

This paper enhances multi-year genomic prediction of wheat breeding data by integrating environmental associations (EPA) to improve genotype-by-environment interaction predictions.

Enviromic-based Kernels Optimize Resource Allocation with Multi-trait Multi-environment Genomic Prediction for Tropical Maize

The paper optimizes genomic prediction training sets using enviromic data and genetic algorithms, increasing genetic gains by 142% per dollar invested.

Use of Hyperspectral Reflectance-Derived Relationship Matrices for Genomic Prediction of Grain Yield in Wheat

This study uses hyperspectral reflectance-derived relationship matrices in genomic selection to predict grain yield in wheat, showing improved accuracy when combined with marker and pedigree data.