Envirome-wide associations enhance multi-year genome-based prediction of historical wheat breeding data
Linking high-throughput environmental data (enviromics) to genomic prediction (GP) is a cost-effective strategy for increasing selection intensity under genotype-by-environment interactions (G × E). This study developed a data-driven approach based on Environment-Phenotype Associations (EPA) aimed a...
|Main Authors:||, , , , , , , ,|
Genetics Society of America
|Subjects:||AGRICULTURAL SCIENCES AND BIOTECHNOLOGY, Genomic Selection, Wheat Breeding, Envirotyping, Target Population of Environments, MARKER-ASSISTED SELECTION, CLIMATE CHANGE, WHEAT, BREEDING, ADAPTABILITY, ENVIRONMENT,|
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