The Study Of The System That Based On The Meteorological Conditions Early Warning Rice Plant Diseases And Insect Pests In The North Cold Area

The subject is based on the test site of Heilongjiang province Shengli farm， according to themeteorological conditions case， research the warning system on the main of diseases and insect pests of rice.Base the biology，ecology and meteorology principle for diseases and insect pests of rice.Use R statisticalanalysis，and intuitive to show the relationship between the diseases and insect pests of rice and meteorologicalfactors by drawing. Forecast simulation based on MATLAB neural network toolbox. Realization thatestablishment of BP network model.Learn The sample data and complete training.Test the model’s predictionusing actual data of Shengli Farm for2012year. Accuracy rate of97%or more. Experimental results show thatthe environmental temperature，environmental humidity，rainfall etc. meteorological conditions plays adecisive role on the occurrence of diseases and insect pests of rice，especially environmental humidity that therainfall is determinant， directly influence the formation， disease and propagation of diseases and insect pestsof rice， in a general way the continuous rainfall period is the peak period of diseases and insect pests of rice.The model based on meteorological conditions is used for the feasibility of pest forecast，it has goodapplication value.The main program written using DELPHI software.User input past meteorological environment in thefuture two days three days to value，or send text messages to the system in accordance with the provisions ofthe format in the main interface.The system can be prediction of the extent of the diseases and insect pests ofrice，and provide expert advice. The user interface is simple and clear，has strong readability and easy tooperate， database using SQL Server2000and data management is very convenient. Development of thissystem not only for the effective control for rice pests，also played a role in promoting for increasing foodproduction.Brought more social，economic and ecological, such as multiple benefits for China.