Yield Stability Analysis in Maize Hybrids of Southwest China under Genotype by Environment Interaction Using GGE Biplot - Chaorui Liu; Chenyu Ma; Jianguo Lü; Zhilan Ye (Agronomy, 2022)
Selecting superior genotypes across different environments is vital for varietal release, crop planting, and commercial use. Therefore, the objectives of this research were to appraise the performance of hybrids approved in recent years in diverse environments, and recommend high-yielding and stable genotypes for wider adaptation. Fourteen single cross maize hybrid genotypes (G), including a check, were implemented across ten environments (E) in two crop seasons (2020 and 2021). The combined analysis of variance revealed that G, E, and their interactive (GEI) significantly (p < 0.01) affected the grain yield. Moreover, the mean grain yield ranged from 9333 kg ha−1 for HH-2 (2021) to 13,195 kg ha−1 for LD-18 (2020). The “which won where” GGE biplot revealed the existence of mega environments with their own best hybrids (LD-18 and LD-29 in 2020; LD-18, LD-19, and YY-1506 in 2021). The “mean vs. stable” GGE biplot suggested that LD-18 and ZY-811, with highest/middle productive and high stability across 10 environments, were closest to the ideal genotype. Furthermore, the “discriminating power vs. representativeness” GGE biplot showed that Xuanwei, Yanshan, Gengma, and Shiling were the most the ideal test environments for hybrid selecting, based on their discriminative ability and representativeness. Therefore, the GGE biplot analysis allowed for an efficient selection of high-yielding and stable maize hybrids to guide ecological planting and commercial use.