Genomic Prediction of Hybrid Combinations in the Early Stages of a Maize Hybrid

2 0 Prediction of single-cross hybrid performance has been a major goal of plant breeders since the 2 1 beginning of hybrid breeding. Genomic prediction has shown to be a promising approach, but 2 2 only limited studies have examined the accuracy of predicting single cross performance. Most of 2 3 the studies rather focused on predicting top cross performance using single tester to determine 2 4 the inbred parent's worth in hybrid combinations. Moreover, no studies have examined the 2 5 potential of predicting single crosses made among random progenies derived from a series of 2 6 biparental families, which resembles the structure of germplasm comprising the initial stages of a 2 7 hybrid maize breeding pipeline. The main objective of this study was to evaluate the potential of 2 8 genomic prediction for identifying superior single crosses early in the breeding pipeline and 2 9 optimize its application. To accomplish these objectives, we designed and analyzed a novel 3 4 depending on the number of tested parents of the single crosses. The genomic estimated general 3 5 and specific combining abilities showed a clear advantage over the use of genomic covariances 3 6 among single crosses, especially when one or both parents of the single cross were untested in 3 7 hybrid combinations. Overall, our results suggest that genomic prediction of the performance of 3 8 single crosses made using random progenies from the early stages of the breeding pipeline holds 3 9 great potential to redesign hybrid breeding and increase its efficiency.