Model-based forecasting of twig canker incidence of bacterial spot of peach in Fukushima Prefecture

Bacterial spot caused by Xanthomonas arboricola pv. pruni ( Xap ) is the most important disease that affects peach production. A disease-forecasting model was developed to help growers decide when to apply bactericides and remove diseased, last-year twigs. To predict the incidence of “spring cankers”, peach twigs damaged by Xap , we used 12 years (2009–2020) of data from Fukushima Prefecture to develop a forecasting system using a hierarchical Bayesian model (HBM). The model included the number of fields with a bacterial spot incidence (BSI) on leaves ≥ 10% in late September of the previous season and the number of days with rain (≥ 10 mm/day) and maximum wind speed (≥ 5 m/s) during the previous October as predictors. Using a best-fit cutoff value based on a receiver operating characteristic (ROC) curve, the model achieved a 0.836 accuracy, 0.804 sensitivity, 0.847 specificity, 0.847 precision, and 0.712 F -measure. The model was validated using a fourfold cross-validation (CV) procedure and achieved an average accuracy of 0.847. Thus, the model explained 65.7% of the variability compared to observed frequencies with predicted probabilities of twig canker incidence (TCI) ≥ 2% from April to May 2009 to 2020 in Fukushima Prefecture. These results suggest that this disease-forecasting model using HBM based on 12 years of historical data can be used to predict the risk of twig cankers of bacterial spot of peach.