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为探讨基于Dualex植物多酚-叶绿素仪和高光谱遥感技术反演小麦叶绿素含量的可行性，利用Dualex植物多酚-叶绿素仪，测定不同生育时期冬小麦叶片叶绿素含量（Chl），同时进行叶片光谱测定，以对Chl敏感的1个一阶导数波段、3个三边参数和3个植被指数作为自变量，利用偏最小二乘法（PLS）和支持向量回归（SVR）构建估测模型，并利用验证样本对各生育时期估测模型进行精度检验，同时与传统的单因素模型进行了比较。结果表明，冬小麦反射光谱曲线在不同生育时期有所不同，且随着叶绿素含量的增加，可见光波段的光谱反射率不断降低；在以一阶导数光谱敏感波段、三边参数以及植被指数构建的冬小麦Chl单因素估算模型中，基于各生育时期显著相关的植被指数构建的模型精度最优；以7个参数作为自变量，利用偏最小二乘法（PLS）和支持向量回归（SVR）构建的模型在各生育时期均表现出较好的拟合性及预测精度，尤其利用SVR建立的模型建模决定系数在0.8以上，预测决定系数在0.7以上，是进行冬小麦叶片Chl估测的最优模型。

英文摘要:

To explore the feasibility of inverting wheat chlorophyll content based on Dualex plant polyphenol-chlorophyll meter and hyperspectral remote sensing technology, the chlorophyll content(Chl) of winter wheat leaves at different growth stages was determined by Dualex plant polyphenol-chlorophyll meter, and the leaf spectrum was measured at the same time. Using a first-order derivative band, three trilateral parameters and three vegetation indices sensitive to Chl as the independent variables, the partial least squares(PLS) and support vector regression(SVR) were used to construct the estimation model. The verification samples were used to verify the accuracy of each growth period estimation model, and compared with the traditional single factor model. The results showed that the reflectance curve of winter wheat is different at different growth stages, and the spectral reflectance of visible light band decreased with the increase of chlorophyll content. In the single-factor estimation model of winter wheat Chl constructed by first-order derivative spectral sensitivity band, trilateral parameter and vegetation index, the accuracy of model constructed based on the vegetation index significantly correlated with each growth period is the best. With seven parameters as independent variables, the model constructed by partial least squares(PLS) and support vector regression(SVR) showed good fitting and prediction accuracy in each growth period. In particular, the modeling coefficient determined by SVR is above 0.8, and the prediction coefficient is above 0.7, indicating that it is the optimal model for estimating the Chl content of winter wheat leaves.

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