Accuracy of Genomic Prediction of Yield and Sugar Traits in Saccharum spp. Hybrids

Genomic selection (GS) has been demonstrated to enhance the process in breeding programs. The objectives of this study were experimentally evaluate different GS methods sugarcane hybrids and determine prospect future approaches. Using sugar yield-related trait data from 432 clones 10,435 single nucleotide polymorphisms (SNPs), a was conducted using seven models. While fivefold cross-validated prediction accuracy differed by crop cycle, there only small differences among Prediction on average 0.20 across all traits cycles for tested Utilizing trait-assisted model, we could effectively predict genomic estimated value ratoon crops both SNPs values plant cane crop. We found that plateau be achieved with 4000 5000 SNPs. did not decline decreasing size training population until it reduced below 60% (259) 80% (346) original number clones. Our findings suggest is possibly new direction improving sugarcane.