Study On Early Warning System Of Tobacco Brown Spot And Wildfire Diseases

Tobacco is an important economic crop in China,in recent years,the occurrence of tobacco brown spot and wildfire diseases has become increasingly serious,affecting the yield and quality of tobacco.This paper establishes an early warning system for tobacco brown spot and wildfire diseases,which can predict the occurrence of tobacco brown spot and wildfire diseases,and provide a theoretical basis for the prevention and control of diseases and diseases.This article is based on meteorological factors of the occurrence of tobacco brown spot disease and wildfire diseases,established a disease growth model for tobacco brown spot and wildfire diseases,disease prediction model,disease prevention and control indicators,and to complete the early warning system for tobacco brown spot and wildfire diseases by constructing the functional requirements of the model.To use the Gambitz model to establish a disease growth model using the changes in the disease index of tobacco brown spot and wildfire diseases over time.Selecting key meteorological forecasting factors by using empirical selection method and related elimination methods,using key meteorological forecasting factors to establish a prediction model based on support vector regression method.By calculating the allowable loss rate,the loss rate of output value and the allowable level of economic damage,the chemical control indicators for diseases were proposed,the results showed that when the weather conditions are suitable for two kinds of diseases,and the disease index of tobacco brown spot disease reaches 2.4,when the disease index of tobacco wildfire disease reaches 3.1,the chemical control should be carried out immediately.If meteorological conditions are very favorable for the occurrence of both diseases,then before the tobacco brown spot disease index reaches 2.4,the tobacco wildfire disease condition index must reach 3.1 before the start of chemical control.Through computer technology,the established disease growth model,prediction model and prevention and control indicators were deployed to early warning systems for tobacco brown spot disease and wildfire diseases.The system is developed based on the Web platform and compiled in Python language,it is mainly built using the Django framework and uses the MySQL database.A system has been released on the Internet to use the system to test the fit of tobacco blast disease and wildfire disease modeling data,based on the results,the average fit rates for tobacco brown spot disease and wildfire diseases prediction were 88% and 85%,respectively.From a practical point of view,this system can provide scientific guidance for disease prevention and control for tobacco farmers and tobacco related technical personnel.