Wheat blast, caused by the fungus Magnaporthe oryzae Triticum pathotype (MoT), is a serious disease capable of causing severe losses, especially during warm and humid weather conditions. Although the pathogen attacks all aboveground parts, infection of the wheat spikes is of major concern. In this work we developed and evaluated a prediction model based on the analysis of historical epidemics and weather series in the northern Paraná state, Brazil (Apucarana, Maringá and Londrina) and available epidemiological knowledge. The disease and weather datasets (hourly scale) examined encompassed the 2001-2012 period. A specific database management application (agroDb) helped to visualize and identify patterns in weather variables during two major outbreaks (2004 and 2009). Specifically, uncommonly humid and warm weather for most locations during a 60-day period preceding wheat heading during years of major outbreaks were considered key drivers of inoculum build up and airborne spores from regional inoculum sources in the surroundings. An inoculum potential (IP) and a spore cloud (SPOR) variable were estimated from models adapted from literature to predict inoculum build-up and availability. A day favoring infection (DFI) was conditioned to rules relating temperature and relative humidity for the day derived from the epidemic analysis. Successful daily infection (INF) during a DFI was conditioned to IP > 30 and SPOR >0.4. To test the model, a wheat model simulated heading date for 10 planting dates, spaced 5 days apart, within a year, totaling 320 simulations. The model described well epidemic and non-epidemics conditions for the historical dataset, and was able to correctly predict epidemic (2015) and non-epidemic (2016) years not analyzed to build the model. An interactive risk-mapping tool that collects real-time weather data was developed for the target area to warn potential outbreaks.The system can be adapted to other regions where the disease is endemic or to asses the epidemic potential in regions where the disease is not present.

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