Method and device for diagnosing disease severity of wheat head blight in field environment

Abstract

The invention particularly relates to a method for diagnosing the disease severity of wheat scab in a field environment, comprising the following steps: (A) collecting a 45-degree angle image of infected wheat scab ears in a wheat field; (B) using a field wheat ear segmentation model Segment the disease image to obtain the wheat ear area; use the wheat head blight segmentation model to segment the disease image to obtain the diseased spot area; (C) use the concave point matching method to segment the adhesion area between the wheat ear and the diseased spot, and obtain the area of ​​each wheat ear in the wheat field and scab area; (D) calculate the ratio R of the scab area and the ear area of ​​each ear of wheat, judge whether R is greater than the set threshold, if R is greater than the set threshold, then judge that the ear of wheat is the sick ear; (E) Calculate the ratio X of the number of diseased ears to the total number of ears in the wheat field, and classify the disease according to the ratio X; and disclose the corresponding detection device. The method can realize the diagnosis of wheat scab disease in the field environment, and the diagnosis speed is fast and the accuracy is high.

Description

technical field [0001] The invention relates to the technical field of detection of wheat scab, in particular to a method and device for diagnosing the disease severity of wheat scab in a field environment. Background technique [0002] As a traditional agricultural country, wheat occupies a very important position in my country's food security. As one of the main diseases of wheat, head blight is particularly serious in the Jianghuai River Basin in my country. Due to the inability to accurately judge the severity of the disease, it often leads to excessive application of pesticides, which causes great harm to the agricultural ecological environment and seriously affects the national grain. Safety and food safety, therefore, it is particularly important to study wheat scab disease classification methods and diagnostic devices. [0003] At present, the diagnosis of wheat head blight mostly adopts artificial visual judgment, spectral diagnosis, conventional image processing an...

AI Technical Summary

Problems solved by technology

As one of the main diseases of wheat, head blight is particularly serious in the Jianghuai River Basin in my country. Due to the inability to accurately judge the severity of the disease, it often leads to excessive application of pesticides, which causes great harm to the agricultural ecological environment and seriously affects the national grain. Safety and food safety, therefore, it is particularly important to study wheat scab disease classification methods and diagnostic devices

[0003] At present, the diagnosis of wheat head blight mostly adopts artificial visual judgment, spectral diagnosis, conventional image processing and other methods. These methods have some shortcomings: artificial visual judgment is greatly affected by human subjectivity; The requirements are relatively high, which is not suitable for ordinary plant protection personnel or farmers; conventional image processing techniques for diagnosing wheat head blight are few and most of them are traditional methods, and most of them are in the theoretical stage and have not been applied in the field

More importantly, most of the current detection methods for scab are based on destructive collection of wheat ears. This detection method is inefficient, and there is currently no good detection method for field groups of wheat ears.

Images