低温胁迫下冬小麦叶片叶绿素含量的高光谱估算

利用一次寒潮降温过程，以苗期12个品种的冬小麦为研究对象，测定其低温逆境下叶片光谱反射率和SPAD(Soil and Plant Analyzer Development，SPAD)值。以2020年12月28日（最高/最低温为15℃/3℃）的观测值为胁迫前数据，12月31日（最高/最低温为1℃/−9℃）的观测值为低温胁迫后数据，分析低温胁迫前后小麦叶片原始光谱和SPAD值的变化规律。在多种光谱参数中，采用相关分析方法遴选出5个与SPAD值密切相关的特征变量，分别建立低温胁迫前、后以原始光谱数据、一阶光谱导数和三种植被指数为自变量的小麦叶片叶绿素含量反演模型，并进行交互验证，筛选出低温胁迫后小麦叶绿素含量的最优反演模型。结果表明：（1）与胁迫前相比，低温胁迫后小麦叶片SPAD整体呈上升趋势，光谱反射率在叶绿素吸收较好的可见光区域有所降低，叶片表现出受冻特征；（2）构建的低温胁迫前后两种混合模型，交互验证后精度较低，表明常温下小麦叶绿素含量估算模型并不适用于遭受低温胁迫后的小麦叶绿素估算，需单独建立低温胁迫后的估算模型；（3）利用光谱数据构建冬小麦低温胁迫下叶绿素含量反演混合模型中，以一阶光谱导数在694nm处建立的模型估算效果最优，拟合度（R2）为0.694，均方根误差（RMSE）为3.191，说明利用小麦叶片光谱特征波段建立低温胁迫下叶片叶绿素含量反演模型的方法是可行的。研究结果可为多品种冬小麦叶片叶绿素含量无损监测提供参考。

Hyperspectral Estimation of Chlorophyll Content in Winter Wheat Leaves under Low Temperature Stress

For real-time monitoring of chlorophyll content in wheat under low temperature adversity, leaf spectral reflectance and SPAD (Soil and Plant Analyzer Development, SPAD) values were measured in 12 varieties of winter wheat at the seedling stage using a cold wave cooling process. Observations on December 28, 2020 (maximum/minimum temperature of 15℃/3℃) were used as pre-stress data, and observations on December 31 (maximum/minimum temperature of 1℃/−9℃) were used as post-low temperature stress data to analyze the patterns of changes in the raw spectra and SPAD values of wheat leaves before and after low temperature stress. The inverse model of chlorophyll content of wheat leaves before and after low-temperature stress was developed using the original spectral data, first-order spectral derivatives and three vegetation indices as independent variables and cross-validated, respectively. The results showed that: (1) compared with the pre-stress period, the overall SPAD of wheat leaves showed an increasing trend after low temperature stress, the spectral reflectance decreased in the visible light region where chlorophyll absorption was better, and the leaves showed freezing characteristics. (2) The accuracy of the two hybrid models constructed before and after low temperature stress was poor after cross-validation, indicating that the model for estimating chlorophyll content of wheat at room temperature was not applicable to the estimation of chlorophyll content of wheat after low temperature stress. (3) Among the hybrid models constructed using spectral data for the inversion of chlorophyll content in winter wheat under low temperature stress, the model with the first-order spectral derivative at 694 nm was the most effective, with an R2 of 0.694 and a RMSE of 3.191, indicating that the use of the characteristic spectral bands of wheat leaves for the estimation of chlorophyll content under low temperature stress was the most effective. The results can be used as a reference for non-destructive monitoring of chlorophyll content in multiple varieties of winter wheat.