To estimate potential impact of climate change on wheat fusarium ear blight, simulated weather for the A1B climate change scenario was imported into a model for estimating fusarium ear blight in central China. In this work, a logistic weather-based regression model for estimating incidence of wheat fusarium ear blight in central China was developed, using up to 10 years (2001-2010) of disease, anthesis date and weather data available for 10 locations in Anhui and Hubei provinces. In the model, the weather variables were defined with respect to the anthesis date for each location in each year. The model suggested that incidence of fusarium ear blight is related to number of days of rainfall in a 30-day period after anthesis and that high temperatures before anthesis increase the incidence of disease. Validation was done to test whether this relationship was satisfied for another five locations in Anhui province with fusarium ear blight data for 4 to 5 years but no nearby weather data, using weather data generated by the regional climate modelling system PRECIS. How climate change may affect wheat anthesis date and fusarium ear blight in central China was investigated for period 2020-2050 using wheat growth model Sirius and climate data generated by PRECIS. The projection suggested that wheat anthesis dates will generally be earlier and fusarium ear blight incidence will increase substantially for most locations

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