Remote sensing monitoring of crop diseases plays a crucial role in food security in terms of the precision management of chemical fungicides and the efficient assessment of crop losses.Spectroscopic detection of disease infection has been investigated for numerous crop diseases individually.However,it remains unclear how biochemical and spectral variations differ in response to divergent diseases given the distinct symptoms caused by different pathogens.This study aimed to determine the pathological mechanism and specificity of the spectral responses of two types of fungal diseases by comparing their specific spectral signatures and disease monitoring performance.The biotrophic Wheat Powdery Mildew(WPM)and the semi-biotrophic Rice Leaf Blast(RLB)diseases were used as examples for the comparison.With the reflectance measurements of infected leaves and radiative transfer modeling,a comparative analysis for these two diseases was conducted in terms of spectral responses,leaf biochemical and structural parameters.Additionally,we assessed the specificity of various disease-related spectral features,which were proposed in previous studies for the monitoring of WPM or RLB,by accuracy comparison in the detection of diseased leaves and the estimation of Leaf Lesion Proportion(LLP).The results showed significant differences in the intensity of spectral responses to the two diseases despite the similarity observed in the general trend in spectral variations.In addition,distinct variations appeared in the spectral shape at the green peak and near-infrared plateau between WPM and RLB.Moreover,the pigment variations in response to two infections were generally similar,whereas the response was more pronounced for RLB.Notably,the leaf water content and structural parameter displayed significant changes only in relation to the severity of RLB.In disease detection,the spectral features developed for WPM or RLB generated higher accuracy in detection of the target disease than the other disease.Wavelet features of WF3820 and WF5866 displayed the highest accuracy and specificity for WPM and RLB,respectively.Regarding the severity quantification,most spectral features exhibited higher sensitivity to the LLP of RLB than to that of WPM.Specifically,a variat of rice blast index(RIBIred)and the Photochemical Reflectance Index(PRI)demonstrated the highest accuracy and specificity in the LLP estimation of WPM and RLB,respectively.Among the WPM-or RLB-related spectral features,RIBIred showed the optimal monitoring performance and specificity in both disease detection and severity estimation(Overall accuracy=0.74,R2=0.58).Our findings provide solid evidence and new insights into disease-specific spectroscopic monitoring by associating spectral responses with pathogenesis of two types of fungal diseases.This study offers significant contributions to the understanding of disease monitoring mechanisms and the identification of multiple diseases with hyperspectral remote sensing.
维普
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