Monitoring Physiological Activity And Photosynthetic Parameters Of Winter Wheat Leaf Under Drought Stress Using Hyperspectral Technology

To predict the physiological enzyme activity and photosynthetic parameters of winter wheat under drought stress by using the hyperspectral remote sensing, the canopy spectra, physical activity (POD, SOD, MDA) and photosynthetic parameters (Pn, Gs, Ci) were measured at the main growth stage of winter wheat. Moreover, spectral characteristic bands of physiological parameters were extracted with the method of SPA and their predictive models were constructed based on the extracted wavelengths with the method of MLR. The results showed that:1.The canopy spectral curves of winter wheat under different drought stress during growth stages were basically similar. The reflectance increased at the visible region and decreased in the near infrared region with the degree of drought stress. The "red shift" phenomenon also occurred at the same time.2. The POD content of winter wheat gradually increased from jointing stage to grain filling stage, while there were an adverse performance for the SOD and MDA content. At the same growth stage, the content of POD, SOD and MDA gradually improved with the drought stress aggravated.3. The Photosynthetic parameters of Pn and Gs increased first and then gradually decreased from jointing stage to filling stage. At same growth stage, the Pn and Gs gradually decreased with drought stress aggravated, while there was an adverse performance for Photosynthetic parameters of Ci.4. The sensitive bands extracted by using SPA were widely distributed in the whole spectrum region. The sensitive bands of biological enzyme activity were mainly distributed in near infrared (44.83%) and short-wave infrared (44.83%) area, and only 10.34% of sensitive wavebands were distributed in the visible region. Moreover,50% of the sensitive bands for photosynthetic parameters were selected in short-wave infrared area, and 26.67% and 23.33% were located in visible and near infrared region, respectively.5. The models based on the origin spectral reflectance performed best after the calibration and validation for the physical activity parameters of POD(R2=0.77, RMSE=48.5, RPD=2.1), SOD(R2=0.576, RMSE=16.7, RPD=1.55), MDA(R2=0.603, RMSE=8.917×10-3,RPD=1.596). however, the SG method had better performance in constructing the optimal models for the photosynthetic parameters of Pn (R2=0.634, RMSE= 2.77, RPD=1.66) and Gs(R2=0.65, RMSE=23.04, RPD=1.7). The models for Ci had a bad prediction and application as the RPD was lower than 1.4.