Al-Ashkar Ibrahim, Sallam Mohammed, Ibrahim Abdullah, Ghazy Abdelhalim, Al-Suhaibani Nasser, Ben Romdhane Walid, Al-Doss Abdullah
Department of Plant Production, College of Food and Agriculture Sciences, King Saud University, Riyadh 11451, Saudi Arabia.
Plants (Basel). 2023 Oct 11;12(20):3540. doi: 10.3390/plants12203540.
Multiple abiotic stresses negatively impact wheat production all over the world. We need to increase productivity by 60% to provide food security to the world population of 9.6 billion by 2050; it is surely time to develop stress-tolerant genotypes with a thorough comprehension of the genetic basis and the plant's capacity to tolerate these stresses and complex environmental reactions. To approach these goals, we used multivariate analysis techniques, the additive main effects and multiplicative interaction (AMMI) model for prediction, linear discriminant analysis (LDA) to enhance the reliability of the classification, multi-trait genotype-ideotype distance index (MGIDI) to detect the ideotype, and the weighted average of absolute scores (WAASB) index to recognize genotypes with stability that are highly productive. Six tolerance multi-indices were used to test twenty wheat genotypes grown under multiple abiotic stresses. The AMMI model showed varying differences with performance indices, which disagreed with the trait and genotype differences used. The G01, G12, G16, and G02 were selected as the appropriate and stable genotypes using the MGIDI with the six tolerance multi-indices. The biplot features the genotypes (G01, G03, G11, G16, G17, G18, and G20) that were most stable and had high tolerance across the environments. The pooled analyses (LDA, MGIDI, and WAASB) showed genotype G01 as the most stable candidate. The genotype (G01) is considered a novel genetic resource for improving productivity and stabilizing wheat programs under multiple abiotic stresses. Hence, these techniques, if used in an integrated manner, strongly support the plant breeders in multi-environment trials.
多种非生物胁迫对全球小麦生产产生负面影响。到2050年，我们需要将生产力提高60%，以保障96亿世界人口的粮食安全；现在确实是时候深入了解遗传基础以及植物耐受这些胁迫和复杂环境反应的能力，从而培育出耐胁迫基因型了。为实现这些目标，我们使用了多变量分析技术、用于预测的加性主效应和乘积交互作用（AMMI）模型、用于提高分类可靠性的线性判别分析（LDA）、用于检测理想型的多性状基因型-理想型距离指数（MGIDI）以及用于识别高产稳定基因型的绝对得分加权平均值（WAASB）指数。使用六个耐逆性多指标对在多种非生物胁迫下种植的20个小麦基因型进行了测试。AMMI模型在性能指标上表现出不同差异，这与所使用的性状和基因型差异不一致。使用MGIDI和六个耐逆性多指标，选择G01、G12、G16和G02作为合适且稳定的基因型。双标图展示了在不同环境中最稳定且耐受性高的基因型（G01、G03、G11、G16、G17、G18和G20）。汇总分析（LDA、MGIDI和WAASB）表明基因型G01是最稳定的候选基因型。基因型（G01）被认为是一种新的遗传资源，可用于提高生产力并在多种非生物胁迫下稳定小麦种植计划。因此，这些技术如果综合使用，将有力支持植物育种者进行多环境试验。
