利用高光谱扫描技术检测小麦叶片叶绿素含量

利用高光谱扫描技术对小麦叶片进行无损检测试验，探索精确测定小麦叶绿素含量的方法，为农作物生长状况、植物病理诊断等提供科学依据。研究选取90个样本作为校正集，30个样本作为预测集，获取叶片的高光谱反射图像，同时用传统的分光光度计方法测定其叶绿素含量。选取波长491～887 nm范围光谱，用多元散射校正、一阶导数、二阶导数3种方法处理，利用偏最小二乘法和逐步线性回归法分别建立了小麦叶片叶绿素含量与光谱信号间的数学模型。研究发现多元散射校正(MSC)结合二阶导数光谱的多元线性回归(SMLR)模型的效果较优，模型校正集和预测集决定系数分别为0.82和0.79，校正均方根误差和预测均方根误差分别为0.69和0.71。研究结果表明可以利用高光谱扫描技术检测小麦叶片叶绿素含量。

Measurement of Chlorophyll Content in Wheat Leaves Using Hyperspectral Scanning

The objective of the present research was to evaluate the potential of hyperspectral scanning as a way for nondestructive measurement of chlorophyll content in wheat leaves, which can indicates the plant healthy status. One hundred twenty samples were randomly picked from Xiao Tangshan farm. Ninety samples were used as calibration set and others were used for verification set. After capturing hyperspectral image in the range of 400-1 000 nm，the chlorophyll contents of samples were measured immediately. Four different mathematical treatments were used in spectra processing in the wavelength range of 491-887 nm：multiplicative scatter correction (MSC)，first derivative correction，and second derivative correction. Statistical models were developed using partial least square regression (PLSR)，and stepwise multiple linear regression (SMLR) analysis technique. The results showed that the best calibration model was obtained by PLSR analysis，after processing spectra with MSC and second derivate, with a relatively higher coefficient of determination of calibration (0.82) and validation (0.79) respectively, a relatively lower RMSEC value (0.69), and a small difference between RMSEC (0.69) and RMSEP (0.71). The results indicate that it is feasible to use hyperspectral scanning technique for nondestructive measurement of chlorophyll content in wheat leaves.