Puccinia striiformis f. sp. tritici uredospore automatic statistical counting method

Abstract

The invention provides a puccinia striiformis f. sp. tritici uredospore automatic statistical counting method, which can be used for quantitative monitoring and accurate counting of puccinia striiformis f. sp. tritici uredospores in outdoor field air. The method comprises the following steps of collecting a microscopic image of the puccinia striiformis f. sp. tritici uredospores to a computer through a TPBZ3 spore capturer and a research-level microscope; and then performing a K-means clustering algorithm, morphological processing, shape factor and area-based adhered spore judgment, concavity-based adhered contour segmentation and adhered spore contour section fusion and counting, wherein the counting accuracy can reach 98.6%, and automatic statistics and counting of the uredospores are realized. The method is high in counting precision and high in practicality, solves the difficult problem, urgently needed to be solved, of counting of the puccinia striiformis f. sp. tritici uredospores in the outdoor field air, and provides technical support for online development of a puccinia striiformis f. sp. tritici uredospore monitoring device.

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...

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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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