Development and Preliminary Application of the Forecasting Model System for Fruit-borer Based on Web
|School||Agricultural University of Hebei|
|Keywords||Fruit-borer Forecast Model Web|
The fruit borer is a class of frequently occurring and severe pest in fruitproduction. There are more than10common species. In general they damage pear,peach, apple, plum, cherry, loquat and hawthorn. They are of long generation, strongfertility and concealment and there are large differences around the occurrence places,so it is very difficult to forecast and control.The study derives from the national nonprofit sector (agriculture) special fundsresearch program “Study and Demonstration on the New Technologies of Monitoringand Controlling Fruit Boreron Fruit Trees in Northern China”. Due to the lack of amature and effective database management system and forecasting system in fruitborer forecasting work around the plant protection department, this system will utilizeexisting information technology to achieve some functions such as the data collection,statistics, query, analysis, forecasting, decision analysis, publish forecast informationabout fruit borer, in order to improve the prediction efficiency and level of fruit borer,provide the basis for the prediction of other fruit pests.The system collects several traditional insect forecasting models, such aspredicting the various instars date of fruit borer by the model of developmentalprogress, predicting the dynamic of fruit borer in a given period by the phenologyprediction method, predicting the peak of fruit borer adult by the effectiveaccumulated temperature method. Combined with the characteristics of each model’spredictions, the system uses PHP, MySQL database and Apache server to create a fruitborer forecasting system. The system can effectively manage and retrieve querymeteorological data over the years and fruit borer monitoring data, sum up the law ofthe fruit borer occurrence through the analysis of such data. On the basis, combinedwith the traditional forecasting model, the system built a knowledge base of fruitborer forecasting to forecast effectively.The system contains four modules such as user module, forecasting data module,model module and prediction module. The user module implements user registration,login, modify, permission setting and other functions. The forecasting data moduleimplements the monitoring data management and import, monitoring equipmentmanagement and meteorological data management. Local plant protection officersinvestigate the occurrence information of pests in the field and enter into the system,the user can manage the monitoring data through the monitoring data module.Meteorological data is transmitted by the field meteorological monitoring equipment developed by China Agriculture University IPMist laboratory. The model module isdivided into the dynamic model and the static model. The dynamic model allows userto enter the model formula, custom variables and correlation coefficients. The staticmodel is expressed by PHP, the user can simply modify the coefficients of thevariables according to the model used by the different fields. According to the fruitpests forecasting method, the module uses some common methods. The progress ofthe development of prediction method, phenology prediction method, effectiveaccumulated temperature method and interval prediction method use the static model,Mathematical statistics method uses the dynamic model. The prediction moduleprovides users with the predicted results. Actual operating results show that theoperability of the system, the predicted results are reliable and intuitive.