Research On A Short-term Classification Early Warning System For Rice Diseases Based On Meteorological Conditions

Rice disease is the main biological disaster in the process of grain production in China,and it has a variety of species,a large range of encroachment,and a rapid outbreak,which is one of the most important factors affecting our food safety in our country.With the development of rice disease early warning research,it is of great significance to improve the universality of early warning methods and the timeliness of early warning results for the improvement of rice yield and quality.Meteorological factors are the main factors affecting the host of rice pathogen infection and the occurrence of rice disease,based on the theory of fuzzy mathematics and the relationship between rice disease and meteorological factors,this paper studies a short-term grading warning system for rice diseases based on meteorological conditions.This project aims at thirteen diseases that seriously endanger rice growth,takes the short-term graded early warning method of rice disease under microclimate environment as the research object,and selects the environmental temperature and air relative humidity of rice growth as the main meteorological factors of early warning.Based on Mamdani model,the fuzzy inference dynamic prediction model of multiple input single output rice disease was designed for different invasive and latent periods of rice diseases,and using Delphi to develop a short-term grading warning application system for rice diseases based on fuzzy reasoning early warning model.The main research work of this paper is as follows:(1)First of all,the fuzzy reasoning algorithm in fuzzy mathematics theory is studied,and introduces the basic principle,working structure and algorithm steps of the algorithm in detail.In addition,the theoretical relationship between the occurrence of rice disease and meteorological factors was determined based on the professional data.Through comparative analysis,the environmental temperature and air relative humidity were selected as the main meteorological factors for early warning,which provided theoretical basis for the follow-up research.(2)Acquisition of meteorological data of rice growing environment and establishment of database.Field real-time and historical meteorological data were collected by intelligent agricultural field environment acquisition equipment.In addition,python crawler data acquisition technology and multiple linear regression method were adopted to capture and predict future meteorological data,and a complete data storage system and calling method were established,which provide a solid data foundation for system development and application.(3)Construction of short-term grading warning model for rice diseases based on fuzzy inference algorithm.Early warning model was designed based on the mathematical principle of fuzzy inference algorithm.A fuzzy inference early warning model for multiple-input and single-output rice diseases based on Mamdani,the establishment and simulation of the early warning model was realized by fuzzy logic toolbox of MATLAB and Simulink simulation tool.The relationship between meteorological data and early warning system was established.Which provides reliable algorithm support for system development and application.(4)Development and application of short-term grading early warning system for rice diseases.Software development and application test of early warning system client based on Delphi + MySQL + Object Pascal,the research results show that early warning system data shows clear and accurate,the operation is simple,and the early warning results are time-sensitive,which has positive guiding significance for rice disease prevention and control.