The Climate Background And Early Dynamic Warning Research Of Rice Planthopper And Wheat Powdery Mildew

Based on the national occurrence area, occurrence degree data of rice planthopper andwheat powdery mildew from1971to2010,74kinds of atmospheric circulationcharacteristics from1970to2010, North Pacific SST data from1969to2010, using factorpuffing, correlation analysis, optimization process, relevant stability test, factor independencetest and stepwise regression, construct level indications and regression forecast model of riceplanthopper and wheat powdery mildew occurrence level. Based on daily meteorological dataand rice planthopper occurrence degree data in Guangxi and wheat powdery mildewoccurrence degree data in Hebei, fisher discriminant analysis was used to construct the Guilinrice planthopper, Hebei wheat powdery mildew early dynamic warning model ofmeteorological conditions.The level indications have good regularity and show significantly differences amongranks of rice planthopper and wheat powdery mildew. When observed value of positive levelindications is higher than average value, rice planthopper and wheat powdery mildew becomeserious. When observed value of positive level indications is lower than average value,riceplanthopper and wheat powdery mildew become light. The result of forecast with historicdata is relatively good.The rice planthopper occurrence rate of atmospheric circulation model level evaluationaccuracy achieves77.5%，North Pacific SST model level evaluation accuracy achieves82.5%,North Pacific SST model evaluation accuracy is better than that of atmospheric circulationmodel slightly. The rice planthopper occurrence degree of atmospheric circulation modellevel evaluation accuracy achieves97.5%, North Pacific SST model level evaluationaccuracy achieves82.5%, the atmospheric circulation model evaluation accuracy is muchbetter than that of North Pacific SST model. The wheat powdery mildew occurrence rate of atmospheric circulation model level evaluation accuracy achieves82.5%, North Pacific SSTmodel level evaluation accuracy achieves80%, the atmospheric circulation model evaluationaccuracy is better than that of North Pacific SST model slightly.Early dynamic warning model prediction accuracy based on fisher discriminant analysisof rice planthopper occurrence degree in Guangxi Guilin and wheat powdery mildew ofHebei region is relatively good. The level evaluation basically accuracy of rice planthoppermodel in Guilin is84.6%, predicting basically accuracy rate is88.2%. The level evaluationbasically accuracy of Wheat powdery mildew model in Hebei achieves97.8%, predictingbasically accuracy rate achieves95.0%.