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首页> 外文期刊>Annual Research & Review in Biology >Application of Physiological Traits Related to Plant Water Status for Predicting Yield Stability in Wheat under Drought Stress Condition
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Application of Physiological Traits Related to Plant Water Status for Predicting Yield Stability in Wheat under Drought Stress Condition

机译:与植物水分状况相关的生理性状在干旱胁迫条件下预测小麦产量稳定性的应用

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The objective of the present study was to model the relationship between yield stability index (YSI) and some physiological traits related to plant water status. Fifteen bread wheat ( Triticum aestivum L.) genotypes with wide range of sensitivity to drought were used in a randomized complete block design with three replications under two different environments (irrigated and rainfed) in 2012-2013 at the experimental farm of College of Agriculture, Razi University, Kermanshah, Iran. The results showed that YSI had positive and significant relationship with relative water protection (RWP, r = 0.858**), relative water content (RWC, r = 0.594*), canopy temperature depression (CTD, r = 0.669**), stomata resistance (SR, r = 0.643**) and evapotranspiration efficiency (ETE, r = 0.818**), and negative significant correlation with relative water loss (RWL, r = – 0.822**) and excised leaf water loss (ELWL, r = – 0.543*) under drought stress condition. Also ETE (0.46*) and RWP (0.806) had the highest direct and indirect effects on YSI, respectively. Multiple linear regression analysis indicated that the predicting model for YSI explained 97.9% of the total variation within the measured traits. The residual plots analysis indicated no problem in the model with selected variables. On the other hand, t-test showed that some of the variables are not important to be present in this model. The results of path and stepwise multiple linear regression analysis indicated that ETE (R2 = 73.5%), RWP (R2 = 11.9%), CTD (R2 = 6.9%) and RWC (R2 = 3%) were the best physiological traits related to water status for modeling of YSI.
机译:本研究的目的是模拟产量稳定指数(YSI)与一些与植物水分状况相关的生理性状之间的关系。在2012-2013年间,在农业学院的实验农场中,采用15种对干旱敏感的基因型小麦,在两个不同环境(灌溉和雨育)下,在三个不同的重复条件下,对干旱进行了广泛的随机区组设计,伊朗克尔曼沙什的拉齐大学。结果表明,YSI与相对水保护(RWP,r = 0.858 **),相对水含量(RWC,r = 0.594 *),冠层温度下降(CTD,r = 0.669 **),气孔有正相关关系。阻力(SR,r = 0.643 **)和蒸散效率(ETE,r = 0.818 **),与相对失水(RWL,r = – 0.822 **)和切叶失水(ELWL,r)负相关= – 0.543 *)在干旱胁迫条件下。 ETE(0.46 *)和RWP(0.806)对YSI的直接和间接影响分别最高。多元线性回归分析表明,YSI的预测模型解释了所测性状内总变异的97.9%。残差图分析表明所选变量在模型中没有问题。另一方面,t检验表明该模型中的某些变量并不重要。路径和逐步多元线性回归分析的结果表明,ETE(R 2 = 73.5%),RWP(R 2 = 11.9%),CTD(R 在YSI模型中,与水分状况相关的最佳生理性状是2 = 6.9%)和RWC(R 2 = 3%)。

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