Lack of water can lead lower chlorophyll concentrations and yields. Based on the hyperspectral reflectance of winter wheat (Triticum aestivum L.), we analyzed the relationship between the canopy hyperspectral reflectance and the water‐stressed winter wheat. The correlation analysis (CA), partial least squares regression (PLSR), and successive progressions algorithm (SPA) were used to extract the important bands. Then the hyperspectral estimation models for chlorophyll density (ChD) by characteristic variables were established. The results showed that the reflectance in the visible regions increased gradually with an increasing water stress. In the near‐infrared (NIR) region, reflectance decreased with stress intensity. We extracted five and seven important waveband regions by CA and PLSR. Then we extracted right and nine important bands through SMLR, and 11 important bands were extracted by the method of SPA. We found that 427, 434, 749, and 814 nm contained important information about ChD of winter wheat after water stress. The model established by CA+SMLR was generally realized, whereas the ChD estimation models established by PLSR+SMLR and SPA with multiple linear regression had better performance, and the performance of the validation model was accurate and robust. The results of this study could provide theoretical basis and practical reference for accurate estimation of ChD in winter wheat after water stress.

中文翻译：

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水分胁迫下冬小麦叶绿素密度的高光谱监测

缺水会导致叶绿素浓度和产量降低。基于冬小麦（Triticum aestivum）的高光谱反射。L.），我们分析了冠层高光谱反射率与水分胁迫的冬小麦之间的关系。相关分析（CA），偏最小二乘回归（PLSR）和连续进行算法（SPA）用于提取重要谱带。利用特征变量建立了叶绿素密度（ChD）的高光谱估计模型。结果表明，可见区的反射率随着水分胁迫的增加而逐渐增加。在近红外（NIR）区域，反射率随应力强度而降低。我们通过CA和PLSR提取了五个和七个重要的波段区域。然后通过SMLR提取正确的和9个重要的带，通过SPA方法提取了11个重要的带。我们发现427、434、749，814 nm处含有水分胁迫后冬小麦ChD的重要信息。总体上实现了CA + SMLR建立的模型，而PLSR + SMLR和SPA建立的具有多元线性回归的ChD估计模型具有更好的性能，验证模型的性能准确，鲁棒。研究结果可为水分胁迫后冬小麦CHD的准确估算提供理论依据和实践参考。