Integrating predictive models and GWAS to identify candidate loci and genes for agronomic traits in rice
Rice is a staple crop whose improvement relies on breeding advances; precision agriculture demands predictive loci/genes for agronomic traits to innovate rice production. To cut experimental costs and boost efficiency, this study built predictive models using seedling leaf metabolomes to forecast rice agronomic traits...