Abstract
MARYBLYT and Cougarblight are fire blight forecasters used to identify blossom infection periods for Erwinia amylovora on apple (Malus x domestica) and pear (Pyrus communis). MARYBLYT uses flowering, an index of bacterial population (EIP), a measurement of wetting, and average daily temperature, whereas Cougarblight uses flowering, wetting, a 4-day temperature window, and orchard fire blight history as parameters for predicting blossom infection. Sensitivity analysis was used to evaluate both models for their ability to predict fire blight using historical weather and disease incidence data collected from several regions. The results showed that the two forecasters performed similarly in their ability to predict blossom blight. However, regional differences in predictive ability were evident, with best performance of both forecasters occurring in England. Further analysis is needed to determine the reasons for the regional differences.
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