Abstract: Abstract: Rice blast is one of the important diseases in rice production. Identification and classification of rice blast is mainly completed by visual observation according to image contrast or literal description currently, however, these methods are subjective and inefficient, besides requiring workers with high professional knowledge. In order to quickly and accurately evaluate the disease level of rice leaf blast, a grading method of rice leaf blast based on hyperspectral imaging technology was proposed. Hyperspectral images of leaf blast at different levels were captured with a HyperSIS hyperspectral system. The logical AND operation was conducted by using the original image and mask image (single leaf image) to remove the background information and a hyperspectral image of a single leaf was obtained. Based on a whole leaf scale, the principal component analysis (PCA) method was used, but the operation results showed that principal component images (PCI) cannot significantly reflect the difference between brown disease spots and gray disease spots. To solve the above problem, a 2-D scatter chart analysis with two sensitive bands (550nm and 680nm) was used to extract hyperspectral images which contained only disease spots (brown disease spots and gray disease spots) through analyzing spectral features of leaf blast areas and normal areas. Based on a disease spots scale, the second principal component image was obtained to identify brown disease spots and gray disease spots by using a PCA method. On this basis, gray disease spots were efficiently identified using an Otsu method. And disease levels of grade 1or 2 and above grade 3 were classified based on whether there existed gray disease spots. Combined with two parameters (elongation and infestation rate), the disease level above grade 3 of rice leaf blast was classified. Through calculating the elongation of a set of 30 spindle disease spots, the elongation of 0.3 was selected as the threshold to distinguish grade 3 and 4. If elongation≥0.3, the disease level was grade 3. If 0