Empirical Comparison of Tropical Maize Hybrids Selected Through Genomic and Phenotypic Selections - Beyene, Yoseph; Gowda, Manje; Olsen, Michael; Robbins, Kelly R.; Pérez-Rodríguez, Paulino; Alvarado, Gregorio; Dreher, Kate; Gao, Star Yanxin; Mugo, Stephen; Prasanna, Boddupalli M.; Crossa, Jose (Frontiers in Plant Science, 2019)
Genomic selection predicts the genomic estimated breeding values (GEBVs) of individuals not previously phenotyped. The main objectives of this study were to (1) empirically compare the performance of tropical maize hybrids selected through phenotypic selection (PS) and genomic selection (GS) under well-watered (WW) and managed drought stress (WS) conditions, and (2) compare the cost-benefit analysis of GS and PS. We used two experimental maize data sets (stage I and stage II yield trials). The stage I data set consisted of 1492 doubled haploid (DH) lines genotyped with rAmpSeq SNPs. A subset of these lines (855) representing various DH populations within the stage I cohort was crossed with a single-cross tester and were evaluated under WW and WS conditions for grain yield and other agronomic traits, while the remaining 637 DH lines were predicted using the 855 lines as a training set. The second data set consists of 346 DH lines that had above average GEBVs (172 lines) and phenotypic value (176 lines) from the first date set. Each of the 348 DH lines were crossed with three common testers and the resulting 1042 testcross hybrids and six commercial checks were evaluated in 4-5 WW locations and one WS conditions. For stage I trials, the cross-validated prediction accuracy for grain yield was 0.67 and 0.65 under WW and WS conditions, respectively. We found similar responses to selection using PS and GS for grain yield other agronomic traits under WW and WS conditions. The top 15% of hybrids advanced through GS and PS gave 21-23% higher grain yield under WW and 51-52% more grain yield under WS than the mean of the checks. The GS reduced the cost by 32% over the PS with similar selection gains. We concluded that the use of GS for yield under WW and WS conditions in maize can produce selection candidates with similar performance as those generated from conventional PS, but at a lower cost, and therefore, should be incorporated into maize breeding pipelines to increase breeding program efficiency.