Genomic selection was used to improve rice breeding by combining data from multiple generations and locations. The study aimed to enhance prediction models for selecting the best rice plants while reducing the need for extensive testing. By testing different scenarios and models, researchers found that including data from multiple locations and generations improved predictions for most traits. This approach could help breeders select better rice plants more quickly, leading to faster breeding cycles and economic benefits for the program.