An automatic statistical counting method for uredia spores of wheat stripe rust

Abstract

The invention provides an automatic statistical counting method for the uredia spores of the wheat stripe rust fungus, which can be used for quantitative monitoring and accurate counting of the uredia spores of the wheat stripe rust fungus in the field air in the field. The method comprises the following steps: collecting microscopic images of ureterospores of wheat stripe rust bacterium into a computer through a TPBZ3 type spore capture instrument and a research-grade microscope; The accuracy rate of the counting accuracy can reach 98.6%, and the automatic counting and counting of the uredia can be realized through the discrimination of the adhesion spore, the segmentation of the adhesion contour based on the concavity, and the fusion and counting of the contour segment of the adhesion spore. The method of the invention has high counting precision and strong practicability, and solves the urgent problem of counting the uredia spores of the wheat stripe rust fungus in the field air. Provide technical support for the development of online wheat stripe rust uredia spore monitoring equipment.

Description

technical field [0001] The invention belongs to the technical field of agricultural image processing, in particular to an automatic counting method for uredia spores of wheat stripe rust. Background technique [0002] Wheat stripe rust caused by Puccinia striiformis f.sp.tritici is an important disease of wheat in winter wheat regions such as Northwest, Southwest, North China and Huaibei and spring wheat regions in Northwest my country, and it can reduce wheat yield by 10% in general epidemic years. % to 20%, and the year of the epidemic can cause a 50% to 60% reduction in wheat production, which poses a major threat to my country's food safety production. Wheat stripe rust is an airborne disease, and the pathogen mainly transmits uredospores to wheat with the airflow to complete the annual infection cycle. Therefore, the number of uredospores in the field air is closely related to the prevalence of wheat stripe rust. Quantitative monitoring and accurate counting of uredia s...

AI Technical Summary

Problems solved by technology

However, factors such as noise in the image, structural features, and subtle grayscale changes on the spore surface can easily lead to too many minimum points and inaccurate segmentation positions, resulting in over-segmentation

Zhang Rongbiao et al. proposed a rapid detection method for the concentration of Azotobacter rotundum by image processing and support vector machine, but the method is only suitable for simple cases where the Azotobacter rotundus adheres to each other less

In addition, among the above methods, most of the methods can count unattached spores very well, but the problem of dividing and counting multi-spore adhesions that often occurs has not been solved

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