Abstract

Bacterial spot, caused by Xanthomonas arboricola pv. pruni, is the most important disease that affects peach production in Okayama Prefecture, Japan. Currently, this disease is managed mainly with copper compounds applied at two stages, before flowering and after harvesting, or with antibiotics applied in May and June. Here we identified the disease risk factors that affect peach at harvest and developed a disease-forecasting model to help growers decide when to apply bactericides. The model was based on parameters for weather data collected for September and October of 2001 through 2012 and for April, May, and June of 2002 through 2013, combined with data on bacterial leaf spot incidence obtained from 28 to 30 fields per year in August from 2001 to 2012 and in May to July from 2002 to 2013. The model, developed using a logistic regression analysis, included the percentage of fields with a bacterial spot incidence (BSI) ≥1 % in mid-August of the previous season and the number of rainy days (≥5 mm/day) during the current June as predictors, and explained 75.0 % of the variability. These results suggest that the previous season’s BSI and weather variables in the present season can be used to predict the risk of bacterial spot.

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