Grain crop pest diagnosis and treatment expert system

Abstract

The invention discloses a grain crop pest diagnosis and treatment expert system. The system comprises a basic information module, auxiliary function modules and a management module, wherein 181 diseases, pests and weeds occurring to grain crops are set in the basic information module and divided into four parts including corn diseases and pests, rice diseases and pests, other grain crop diseases and pests and farmland weeds; the auxiliary function modules comprise the expert answering module, the visiting message board module and the contact module, and users can communicate with experts through the contact module to directly consult the experts, so that more direct and good-quality services are obtained, advices and suggestions of the users can be collected, and the system can be improved; by inputting manager passwords, the management module enters an editing mode to update and add a knowledge base. The image identification type expert system is used and also has a query function and a browsing function, the capacity of the system is moderate, the design is scientific and reasonable, and the system is dynamic and can be updated in real time.

Description

technical field [0001] The invention relates to the field of agriculture, in particular to an expert system for diagnosis and treatment of food crop pests. Background technique [0002] According to the relevant agricultural expert systems that have been reported, there are three kinds of expert systems involved in the diagnosis and treatment of cultivated plant pests: query browsing system, image identification system and rule-based diagnosis and treatment system. [0003] At present, only "vegetable pest and disease auxiliary diagnosis and control system" has entered the practical stage and is similar to it, which has the following objective shortcomings: 1. The knowledge base is huge. Including 2167 pests and diseases of 103 kinds of vegetables in 15 categories such as melons and solanaceous fruits, each pest has 5-30 images and a large amount of text information. Such a huge database takes up a lot of space, and it is also not conducive to the rapid diagnosis and treatm...

AI Technical Summary

Problems solved by technology

[0003] At present, only "vegetable pest and disease auxiliary diagnosis and control system" has entered the practical stage and is similar to it, which has the following objective shortcomings: 1. The knowledge base is huge

Such a huge database takes up a lot of space, and it is not conducive to users to quickly diagnose and treat harmful organisms

2. Images and text information are redundant, and users are not very targeted

All collected images and text information are used and put on the same page, so that various users such as agricultural technicians, farmers, plant protection researchers and professional technicians cannot quickly find the knowledge points they need

3. The threshold is high

The content cannot be updated at any time according to changes in production diseases, insect pests and pesticides used

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