Water is one of the major limiting factors for wheat production. Mult-environmental evaluation is necessary to identify stable drought tolerant wheat genotypes. To identify stable drought tolerant wheat genotypes and reliable phenotypic and/or spectral markers for drought tolerance. One hundred ninety-six diverse wheat genotypes were evaluated at three different locations in India for two years (E1 to E12). Drought was imposed at the heading stage (Z59) by withholding irrigation until the moisture content reached <45% as compared to the control (100%). Various Morpho-physiological and phenological traits: Days to flowering (DTF) and maturity (DTM), plant height (PH), grain yield (GY), NDVI, canopy temperature depression (CTD), and chlorophyll readings were recorded. Different stress indices and stability models (AMMI - Additive Main Effects and Multiplicative Interaction; WAASB - Weighted Average of Absolute Scores from the singular value decomposition of the matrix of BLUPs; and MTSI - Multi-Trait Stability Index) were used to identify the stable and tolerant genotypes. In addition, discriminate function analysis (DFA) was performed to identify drought tolerant genotypes. Genotype performance reduced significantly under drought for all traits in all environments. Overall, GY was reduced by 35% under drought compared to control. Pooled ANOVA showed that 81% of the variation in grain yield was due to the environment and 10.6% due to its interaction with genotypes. MTSI and WAASBY identified 11 common genotypes with stable performance across all environments. Further, 29 stable genotypes selected by MTSI (with 15% selection intensity) had higher selection differential than other stability models. Further, NDVI at maturity showed a positive and significant correlation [r = 0.41** in E2 and 0.36** in E4) with the GY specifically under drought for two years. MTSI is an effective method for selecting stable wheat genotypes under drought conditions. NDVI may be a high throughput screening tool for drought tolerance. MTSI may be used to identify stable genotypes, while DFA is useful in selecting drought tolerant genotypes. Further, NDVI can be used in addition to yield traits to screen wheat genotypes for drought tolerance.

中文翻译：

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小麦干旱适应的时空评估揭示了 NDVI 和 MTSI 是选择耐受基因型的有力工具

水是小麦生产的主要限制因素之一。多环境评估对于鉴定稳定的耐旱小麦基因型是必要的。鉴定稳定的耐旱小麦基因型和可靠的耐旱表型和/或光谱标记。在印度三个不同地点对一百九十六种不同的小麦基因型进行了为期两年的评估（E1 至 E12）。在抽穗期（Z59）通过停止灌溉来施加干旱，直到与对照（100％）相比含水量达到<45％。各种形态生理和物候性状：记录开花天数（DTF）和成熟天数（DTM）、株高（PH）、谷物产量（GY）、归一化植被指数（NDVI）、冠层温度降低（CTD）和叶绿素读数。使用不同的应力指数和稳定性模型（AMMI - 加性主效应和乘性相互作用；WAASB - BLUP 矩阵奇异值分解的绝对分数加权平均值；以及 MTSI - 多性状稳定性指数）来识别稳定和稳定的模型。耐受基因型。此外，还进行了判别函数分析（DFA）来鉴定耐旱基因型。在干旱条件下，所有环境中所有性状的基因型表现均显着降低。总体而言，与对照相比，干旱条件下 GY 减少了 35%。汇总方差分析显示，谷物产量的变化 81% 是由环境造成的，10.6% 是由环境与基因型的相互作用造成的。 MTSI 和 WAASBY 确定了 11 种常见基因型，在所有环境中均具有稳定的性能。此外，MTSI 选择的 29 个稳定基因型（选择强度为 15%）比其他稳定性模型具有更高的选择差异。此外，成熟时的 NDVI 显示出与 GY（特别是在连续两年的干旱条件下）呈正相关且显着的相关性（E2 中 r = 0.41**，E4 中 r = 0.36**）。 MTSI是选择干旱条件下稳定小麦基因型的有效方法。 NDVI 可能是抗旱性的高通量筛选工具。 MTSI 可用于鉴定稳定的基因型，而 DFA 可用于选择耐旱基因型。此外，除了产量性状外，NDVI 还可用于筛选小麦耐旱基因型。