Strategic risk analysis for the selection of stable and high-potential maize genotypes in multi-environment trials

Plant breeders are increasingly utilizing stability parameters as valuable tools for selecting cultivars in the context of genotype × environment interaction (GEI). Neglecting GEI in multi-environment trials (MET) can significantly heighten the risk of making inaccurate cultivar recommendations to farmers. Consequently, breeders must strive to find an optimal balance between yield and stability, favoring varieties that minimize the risk of extremely low yields. Recent advancements in probability theory, along with specialized software packages, have made the decision-making process more efficient for identifying suitable candidates across diverse environments. Under this scenario, a study was conducted to evaluate 15 promising maize hybrids alongside one control commercial hybrid (hybrid No. 16). The research employed a randomized complete block design with four replications across eight diverse locations over two consecutive years. The hybrids evaluated resulted from crosses involving temperate × temperate and tropical/subtropical × temperate. The objectives of this research included estimating the stability of these hybrids and assessing the associated risks related to their release, as well as evaluating the success and potential of lines derived from subtropical and tropical materials. A Bayesian approach was applied to estimate the probability that each genotype outperformed its competitors. The variance component estimates indicated that “location” was the most significant factor influencing overall variability, with values of 0.756 for genotype, 11.304 for location, and 0.621 for genotype × location effects. To enhance the mean grain yield within the selection panel, a selection intensity of 20% was implemented based on computed probabilities of superior performance and stability among selected candidates. Hybrid H2 exhibited the highest probability of superior performance (0.99), closely followed by Hybrid H5 with 0.97 of probability of belonging to the top subset. Hybrid H2 outperformed hybrid H16 (check hybrid) in all cases across tested environments; however, it demonstrated lower stability in 55% of comparisons. This finding suggests that the hypothesis asserting H2’s superiority over H16 in both stability and performance was not supported. H5 was the only hybrids common to both the top-performing (H2, H5, H4, H3) and most stable (H13, H15, H5, H7) groups. It is essential for breeders to jointly consider the probabilities of superior performance and stability when determining optimal genotypes. Considering the joint probability of superior performance and yield stability, the hybrids H5, H4, H15 and H2 stand out. High-performing and stable hybrids like H5 and H2 reduce cultivar introduction risks. Overall, these results indicated that employing a risk/probability analysis approach can significantly enhance decision-making accuracy for cultivar recommendations in METs.