Plant disease recognition and early warning method and device

Abstract

The invention provides a plant disease recognition and early warning method and device, and relates to the technical field of agricultural plant protection. According to the method and device, a colored image to be recognized is acquired, wherein the image to be recognized comprises corresponding spectrum-texture features; the acquired image to be recognized is input into a trained deep learning recognition model for recognition and classification, and the disease variety and the severity of diseases are obtained through the deep learning recognition model according to the spectrum-texture features of the image to be recognized; a corresponding early warning hint is given out according to the severity. According to the scheme, manpower and material resources for recognizing the plant diseases can be reduced, and the accuracy and recognition speed of plant disease recognition can be increased; in addition, according to the scheme, the severity of the plant diseases can be obtained, thecorresponding early warning hint can be given out according to the severity, and related personnel are helped to prevent and control the plant diseases in time.

Description

technical field [0001] The invention relates to the technical field of agricultural plant protection, in particular to a plant disease identification and early warning method and device. Background technique [0002] Plant disease identification and prevention is an important part of agricultural production. For example, the maturity of the corresponding pathogenic bacteria can be obtained by grading the pathogens of plants, and the severity of diseases can be obtained according to the classification of plant diseases. In the prior art, forecasting personnel are usually required to conduct manual investigations in the field, and different forecasting personnel have large differences in grading standards during investigations. At the same time, there are many types of diseases, which requires high professional ability of forecasting technicians. In most cases, forecasting technicians need to identify in combination with books, atlases, morphological feature descriptions, etc...

AI Technical Summary

Problems solved by technology

In the existing technology, forecasting personnel are usually required to conduct manual investigations in the field, and different forecasting personnel have large differences in grading standards during investigations. At the same time, there are many types of diseases, which requires high professional ability of forecasting technicians

In most cases, forecasting technicians need to identify in combination with books, atlases, morphological feature descriptions, etc., but manual identification is prone to errors, and the identification efficiency is low, and human factors interfere greatly, which cannot meet the needs of accurate and rapid identification of plant disease types and severity requirements

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