Rahmati Salim, Azizi-Nezhad Reza, Pour-Aboughadareh Alireza, Etminan Alireza, Shooshtari Lia
Department of Plant Breeding and Biotechnology, Science and Research Branch, Islamic Azad University, Tehran, 14778-93855, Iran.
Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, P.O. Box 31587-77871, Iran.
Heliyon. 2024 Sep 19;10(18):e38131. doi: 10.1016/j.heliyon.2024.e38131. eCollection 2024 Sep 30.
Genotype-by-environment interaction (GEI) analysis play a key role in any breeding program involving the development of new varieties for cultivation across various environments or in a specific region. The additive main effects and multiplicative interaction (AMMI) method and the GGE biplot are the two main statistical tools that have emerged to analyze GEI in multi-environment trials (METs). The main goal of the present study was to identify the best-performing and stable barley genotypes for the warm regions of Iran. For this purpose, 18 new advanced barley genotypes were investigated in five warm locations in Iran during two cropping seasons (2021-2023). In all experiments, test genotypes were evaluated in a randomized complete block design (RCBD) with three replications. Based on results, grain yield was significantly dependent on environments (E), genotypes (G), and GEI. The GEI effect was further divided into three principal component axes (IPCAs). The AMMI method identified genotypes G3, G9, G10, and G14 as ideal genotypes due to their low IPCA scores and high performances. In the GGE biplot analysis, the initial two PCAs accounted for 49.36 % of the total variation of grain yield, including both G and GEI effects. Based on averaged two-year data, genotypes G3, G4, G10, and G14 showed particular adaptability in the Zabol and Moghan regions. Moreover, the ranking of test environments showed good discriminatory and representative abilities for the Zabol and Moghan regions, so these environments constituted a mega-environment in Iran's warm climate. The genotype ranking indicated G3, G10 and G14 genotypes as the superior genotypes with the highest grain yield and stability in different test environments. Moreover, these results were confirmed by the results obtained by WAASB and WAASBY biplots. In conclusion, genotypes G3, G10 and G14 can be suggested for commercial usage and cultivation in various regions in Iran's warm climate.
基因型与环境互作（GEI）分析在任何旨在培育适合在不同环境或特定区域种植的新品种的育种计划中都起着关键作用。加性主效应和乘积互作（AMMI）方法以及GGE双标图是在多环境试验（METs）中用于分析GEI的两种主要统计工具。本研究的主要目标是确定伊朗温暖地区表现最佳且稳定的大麦基因型。为此，在2021 - 2023年的两个种植季节中，在伊朗的五个温暖地点对18个新的先进大麦基因型进行了研究。在所有试验中，测试基因型采用随机完全区组设计（RCBD），重复三次。结果表明，籽粒产量显著依赖于环境（E）、基因型（G）和GEI。GEI效应进一步分为三个主成分轴（IPCA）。AMMI方法将基因型G3、G9、G10和G14鉴定为理想基因型，因其IPCA得分低且表现优异。在GGE双标图分析中，前两个主成分占籽粒产量总变异的49.36%，包括G和GEI效应。基于两年的平均数据，基因型G3、G4、G10和G14在扎博勒和莫加恩地区表现出特别的适应性。此外，测试环境的排名显示出对扎博勒和莫加恩地区具有良好的区分和代表性能力，因此这些环境构成了伊朗温暖气候下的一个 mega - 环境。基因型排名表明，基因型G3、G10和G14是在不同测试环境中籽粒产量最高且稳定性最好的优良基因型。此外，这些结果得到了WAASB和WAASBY双标图结果的证实。总之，基因型G3、G10和G14可推荐用于伊朗温暖气候下不同地区的商业种植。
