Humberto Fanelli Carvalho

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

This study shows that reducing genotyping marker density in cross-pollinated crops decreases predictive accuracy over generations, suggesting that higher marker density is better for long-term breeding.

EnvRtype provides a software toolkit for integrating enviromics data into quantitative genomics to improve whole-genome prediction accuracy across different environments.