Development of an automatic grading system of wheat stripe rust severity based on image processing
Stripe(yellow)rust caused by Puccinia striiformis f.sp.tritici is a devastating disease on wheat,which seriously affects the security production of wheat.Correct severity assessment is essential for disease fore-casting and adopting effective disease management measures to reduce wheat yield losses.To realize accurately assess the severity of wheat stripe rust,in this study,the methods for the severity assessment of wheat stripe rust were investigated based on image processing and an automatic grading system of wheat stripe rust severity was developed.Based on the acquired disease images of single leaves of wheat stripe rust,manual disease image seg-mentation operations and pixel statistics operations were performed successively with an image processing soft-ware,and the segmented leaf region and lesion region images and the pixel numbers of the corresponding whole leaf regions and lesion regions were obtained.According to the obtained pixel numbers,the actual percentages of lesion areas in the areas of the corresponding whole diseased leaves were calculated.Based on image processing technology,four image segmentation methods were utilized to implement automatic segmentation to obtain leaf region images and lesion region images.Then,the results obtained by using the four automatic segmentation methods were compared with those obtained by using the manual segmentation method via the image processing software,and the optimal automatic segmentation method was achieved.Subsequently,based on the percentages of lesion areas in the areas of the corresponding whole diseased leaves obtained by using the optimal automatic segmentation method,the severity of each diseased leaf was assessed according to the midpoint-of-two-adjacent-means-based actual percentage reference range and the 99％reference range of the actual percentages for each severity class of wheat stripe rust,respectively.The results showed that the assessment method based on the 99％reference range of the actual percentages for each severity class of wheat stripe rust was the optimal,with the average accuracy of 88.19％.Finally,by using the optimal automatic image segmentation method and the optimal severity assessment method,in combination with the PyQt5 library,Qt Designer,and PyUIC5 design tools,an automatic grading system of wheat stripe rust severity was developed with the Python language.This study pro-vided a basis for the automatic assessment of wheat stripe rust severity based on image processing technology,and provided methods and ideas for the severity assessments of other plant diseases.
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