Combined analysis of genotype × environment interaction by fixed and mixed effect models in the selection of stable and productive maize (Zea mays L.) inbreds

Abstract

Assessment of genotype × environment interaction for stability and the performance of yield and its attributes of inbred lines across the environments serve as an important pre-breeding step in maize for selection of parental lines. A set of 70 inbred lines was evaluated for grain yield and other yield traits in multi-location trials under diverse environments to analyze Additive Main Effects and Multiplicative Interaction Effects, genotype and genotype × environment (GGE) biplots and best linear unbiased predictor (BLUP). A joint analysis of variance revealed significant differences across environments for the studied traits. The biplot analysis revealed that inbred lines, UMI 1260 and UMI 1266 performed well in Coimbatore (E1) and Bhavanisagar (E2), whereas IMR 108200 and UMI 1257 performed well in Vagarai (E3). GGE and WAASBY biplot analysis showed that Coimbatore and Vagarai environments were found discriminative and may be suitable for selecting genotypes for specific adaptation, while Bhavanisagar is ideal for selecting genotypes with broad adaptability. Multiple stability indices, such as yield stability index (YSI), the harmonic mean of the relative performance of genetic values, and the weighted average of absolute scores of BLUPs (WAASBY) facilitated the selection of stable inbred lines in terms of grain yield, while multi-trait selection index aided in the selection of genotypes based on multiple traits. Positive selection gains were observed for yield and related traits, whereas negative gains were observed for plant height and ear height. The coincidence index at 20% selection intensity revealed a high level of coincidence between WAASBY and HMRPGV, indicating selection efficiency when either of the indices was used. Inbred lines, UMI 1286, UMI 1276, and UMI 1266 ranked consistently across all the stability indices and hence can serve well as potential inbred lines in hybrid breeding. The use of multiple stability indices enhances the accuracy of selecting inbreds or genotypes by compensating for the limitations of individual indices, providing a more balanced and reliable evaluation.