阿米
双标图
象形文字
耐旱性
基因-环境相互作用
选择(遗传算法)
生物
农学
产量(工程)
普通大麦
基因型
粮食产量
索引(排版)
适应性
生物技术
作物
禾本科
生态学
计算机科学
遗传学
冶金
材料科学
万维网
人工智能
基因
作者
Habibollah Ghazvini,Alireza Pour‐Aboughadareh,Seyed Shahriyar Jasemi,Mehrdad Chaichi,Hamid Tajali,Jan Bocianowski
标识
DOI:10.1007/s10343-024-00981-1
摘要
Drought stress is one of the major environmental stresses that dramatically reduces agricultural production around the world. Barley (Hordeum vulgare L.) plays an important role in both food and feed security. The objective of this study was to identify the superior drought-tolerant genotypes using grain yield and several yield-based indices of tolerance and susceptibility by applying various multivariate selection models. To achieve this objective, a set of promising new barley genotypes was evaluated in three drought-prone regions of Iran (Mashhad, Karaj, and Hamadan) during two consecutive growing seasons (2019–2020 and 2020–2021). The results of additive main effect and multiplicative interaction (AMMI) analysis showed significant effects for genotypes (G), environments (E), and their interaction (G × E). Based on the AMMI model, G3, G7, G9, and G13 were identified as the four highest-ranked genotypes in terms of grain yield. Based on the Smith-Hazel, factor analysis and genotype-ideotype distance index (FAI), and genotype–ideotype distance index (MGIDI) selection models, genotypes G4 and G13 showed the greatest tolerance to drought stress conditions in the three regions. Moreover, the most significant selection gain was found for the stress tolerance index, yield index, and grain yield under drought stress conditions (Ys). The results of the genotype (G) + genotype × environment (GGE) biplot analysis coincided with those obtained, in which the G4 and G13 genotypes showed specific adaptability in drought environments. In addition, among the environments tested, the Karaj region was selected as an ideal target environment with significant discriminatory power and representative ability. In conclusion, the collective analysis using the AMMI, GGE biplot, and multi-index selection models identified genotypes G4 and G13 as superior genotypes. Consequently, these genotypes may be candidates for commercial introduction.
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