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Prediction Strategies For Leveraging Information Of Associated Traits Under Single- And Multi-Trait Approaches In Soybeans, Reyna Persa, Arthur Bernardeli, Diego Jarquin

Department of Agronomy and Horticulture: Faculty Publications

The availability of molecular markers has revolutionized conventional ways to improve genotypes in plant and animal breeding through genome-based predictions. Several models and methods have been developed to leverage the genomic information in the prediction context to allow more efficient ways to screen and select superior genotypes. In plant breeding, usually, grain yield (yield) is the main trait to drive the selection of superior genotypes; however, in many cases, the information of associated traits is also routinely collected and it can potentially be used to enhance the selection. In this research, we considered different prediction strategies to leverage the information …