Shiri Mohammadreza, Moharramnejad Sajjad, Estakhr Afshar, Fareghi Sharareh, Najafinezhad Hamid, Khorasani Saeed Khavari, Afarinesh Aziz, Eshraghi-Nejad Morteza
Department of Maize and Forage Crops Research, Seed and Plant Improvement Institute, Agricultural Research Education and Extension Organization (AREEO), Karj, Iran.
Crop and Horticultural Science Research Department, Ardabil Agricultural and Natural Resources Research and Education Center, AREEO, Moghan, Iran.
PLoS One. 2025 Jun 6;20(6):e0325454. doi: 10.1371/journal.pone.0325454. eCollection 2025.
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.
在基因型×环境互作(GEI)背景下,植物育种者越来越多地将稳定性参数作为选择品种的重要工具。在多环境试验(MET)中忽视GEI会显著增加向农民推荐不准确品种的风险。因此,育种者必须努力在产量和稳定性之间找到最佳平衡,倾向于将极低产量风险降至最低的品种。概率论的最新进展以及专门的软件包使决策过程在识别不同环境中的合适候选品种时更加高效。在此背景下,开展了一项研究,评估15个有前景的玉米杂交种以及一个对照商业杂交种(杂交种16)。该研究采用随机完全区组设计,连续两年在八个不同地点进行四次重复试验。所评估的杂交种来自温带×温带以及热带/亚热带×温带的杂交组合。本研究的目的包括估计这些杂交种的稳定性,评估与它们发布相关的风险,以及评估源自亚热带和热带材料的品系的成功情况和潜力。采用贝叶斯方法估计每个基因型优于其竞争对手的概率。方差分量估计表明,“地点”是影响总体变异性的最重要因素,基因型的方差分量值为0.756,地点的方差分量值为11.304,基因型×地点效应的方差分量值为0.621。为了提高选择群体内的平均籽粒产量,根据所选候选品种中表现优异和稳定的计算概率,实施了20%的选择强度。杂交种H2表现优异的概率最高(0.99),紧随其后的是杂交种H5,属于顶级子集的概率为0.97。在所有测试环境中,杂交种H2在所有情况下均优于杂交种H16(对照杂交种);然而,在55%的比较中它表现出较低的稳定性。这一发现表明,声称H2在稳定性和性能方面优于H16的假设未得到支持。H5是表现最佳的组(H2、H5、H4、H3)和最稳定的组(H13、H15、H5、H7)中唯一共同的杂交种。育种者在确定最佳基因型时共同考虑表现优异和稳定的概率至关重要。考虑到表现优异和产量稳定性的联合概率,杂交种H5、H4、H15和H2脱颖而出。像H5和H2这样表现优异且稳定的杂交种降低了品种引入风险。总体而言,这些结果表明,采用风险/概率分析方法可以显著提高MET中品种推荐的决策准确性。