| Citrus huanglongbing (HLB) is the world's most devastating diseases of citrus production. It has caused tremendous loss to growers and related industries. Taking citrus leaves as the carrier, we collected hyper spectral images of citrus leaf surface with hyper spectral imaging technology, analyzed the image with ENVI4.7 to extract the region of interest
(ROI), and counted average spectral of ROI. It operated vegetation plants related to, and finally identified and classify
through PLS-DA (Partial Least Squares Discrimination Analysis) discriminant method. The results showed that three types of
citrus leaves could be identified by PLSDA discriminant model based on the average spectral values and vegetation indices.
Sensitivity of healthy citrus leaf samples was 100%, the specificity was 100% and accuracy was 100%; identification of zinc citrus leaf samples sensitivity was80.6%, specificity was 91.7%, accuracy was 88.9%; identification HLB leaf sensitivity was 89.3%, specificity was 88.3% and accuracy was 88.9%. For PLSDA model based on vegetation index, sensitivity of healthy citrus leaf samples was 100%, specificity was 100% and accuracy was 100%; sensitivity of zinc citrus leaf samples was 92.5%, specificity was 89.3%, accuracy was 90.1%;sensitivity of HLB leaves was 86.4%, specificity was 95.3% and accuracy was 90.1%. The correct identified rate was high. It indicates that using high-spectrum for classification of citrus huanglongbing is feasible. |
