Two logistic regression models for wheat fusarium ear blight in central China were developed,based on up to 10 years (2001-2010) of disease data and weather data for 10 sites in Anhui and Hubei provinces. It is shown that pre-harvest incidence of fusarium ear blight (％ spikes affected) is closely related to weather factors, especially rainfall and temperature. In the first model, the weather variables are defined with respect to the first day of April since wheat anthesis generally occurs in April in that region of China. The model suggests that rainfall before anthesis increases subsequent incidence of fusarium ear blight and that high temperature after the month of anthesis decreases the incidence of disease. In the second model, the weather variables are defined with respect to the anthesis date for each site in each year. The model suggests that incidence of fusarium ear blight is related to the number of days of rainfall in the first month after anthesis and that high temperatures before anthesis increase the incidence of disease.
disease incidence-severity relationship food security logistic regression model sustainable agriculture weather-based disease forecasting wheat fusarium head blight
Xu Zhang Julia Halder Rodger P White David J Hughes Shengyi Liu Zhiqiang Ye Binjie Gan Rongqin Xu Bruce D L Fitt
Rothamsted Research,Harpenden, Herts. AL5 2JQ UK;Elementary Education College, Chongqing Normal Univ Rothamsted Research,Harpenden, Herts. AL5 2JQ UK Oil Crop Research Institute, China Academy of Agricultural Science,Wuhan, Hubei, 430000, China Elementary Education College, Chongqing Normal University,Chongqing,400700, China Crop Research Institute,Anhui Academy of Agricultural Science,Hefei, 230000, China Hubei Plant Protection Station, Wuhan,430070,China