A two-step modeling approach was used for predicting the effect of temperature on the growth of Xanthomonas arboricola pv. pruni, causal agent of bacterial spot disease of stone fruit. The in vitro growth of seven strains was monitored at temperatures from 5 to 35°C with a Bioscreen C system, and a calibrating equation was generated for converting optical densities to viable counts. In primary modeling, Baranyi, Buchanan, and modified Gompertz equations were fitted to viable count growth curves over the entire temperature range. The modified Gompertz model showed the best fit to the data, and it was selected to estimate the bacterial growth parameters at each temperature. Secondary modeling of maximum specific growth rate as a function of temperature was performed by using the Ratkowsky model and its variations. The modified Ratkowsky model showed the best goodness of fit to maximum specific growth rate estimates, and it was validated successfully for the seven strains at four additional temperatures. The model generated in this work will be used for predicting temperature-based Xanthomonas arboricola pv. pruni growth rate and derived potential daily doublings, and included as the inoculum potential component of a bacterial spot of stone fruit disease forecaster.

Xanthomonas arboricola pv. pruni is the causal agent of bacterial spot disease of stone fruits and almond. The bacterium is distributed throughout the major stone-fruit-producing areas of the World and is considered a quarantine organism in the European Union according to the Council Directive 2000/29/EC, and by the European and Mediterranean Plant Protection Organization. The effect of leaf wetness duration and temperature on infection of Prunus by X. arboricola pv. pruni was determined in controlled environment experiments. Potted plants of the peach-almond hybrid GF-677 were inoculated with bacterial suspensions and exposed to combinations of six leaf wetness durations (from 0 to 24 h) and seven fixed temperatures (from 5 to 35°C) during the infection period. Then, plants were transferred to a biosafety greenhouse, removed from bags, and incubated at optimal conditions for disease development. Although leaf wetness was required for infection of Prunus by X. arboricola pv. pruni, temperature had a greater effect than leaf wetness duration on disease severity. The combined effect of wetness duration and temperature on disease severity was quantified using a modification of the Weibull equation proposed by Duthie. The reduced-form of Duthie’s model obtained by nonlinear regression analysis fitted well to data (R = 0.87 and R2adj = 0.85), and all parameters were significantly different from 0. The estimated optimal temperature for infection by X. arboricola pv. pruni was 28.9°C. Wetness periods longer than 10 h at temperatures close to 20°C, or 5 h at temperatures between 25 and 35°C were necessary to cause high disease severity. The predictive capacity of the model was evaluated using an additional set of data obtained from new wetness duration-temperature combinations. In 92% of the events the observed severity agreed with the predicted level of infection risk. The risk chart derived from the reduced form of Duthie’s model can be used to estimate the potential risk for infection of Prunus by X. arboricola pv. pruni based on observed or forecasted temperature and wetness duration.

Xanthomonas arboricola pv. pruni (Xap) is the causal agent of bacterial spot disease of stone fruits and almond. The bacterium is considered a quarantine pathogen in Europe and it has become a new and emerging threat for European crops. As the disease is strongly influenced by the weather, a forecasting model that predicts Xap infections based on climatic conditions could be implemented in stone fruit integrated pest management. The objective of this work was to constrain the basis for the development of a predictive model of Xap growth and infections, determining the effects of pathogen, host and climatic parameters on infection and disease development. A non-pathogenic specialization of Xap and cross-infection among host species was observed, although strains isolated from peach were the most virulent in peach leaves. Xap was able to infect unwounded leaves and it was observed that the presence of wounds on the leave surface did not favour Xap penetration in peach leaves. Otherwise, the water condition of plants played an important role in Xap infections and disease development in peach. The presence of water congestion and leaf wetness 48 h before inoculation favoured Xap infections and the duration of leaf wetness after inoculation was directly correlated to disease severity. Temperature and leaf age had a significant effect on Xap infections. Temperatures above 20°C favoured Xap infections, which were basically produced in young leaves; whereas severity was significantly lower at temperatures below 15°C and in mature leaves.

Bacterial spot disease of stone fruits, caused by Xanthomonas arboricola pv. pruni, is of high economic importance in the major stone-fruit-producing areas worldwide. A better understanding of disease epidemiology can be valuable in developing disease management strategies. The effects of weather variables (temperature and wet/dry period) on epiphytic growth of X. arboricola pv. pruni on Prunus leaves were analyzed, and the relationship between inoculum density and temperature on disease development was determined and modeled. The information generated in this study, performed under controlled environmental conditions, will be useful to develop a forecasting system for X. arboricola pv. pruni. Optimal temperature for growth of epiphytic populations ranged from 20 to 30°C under leaf wetness. In contrast, multiplication of epiphytic populations was not only interrupted under low relative humidity (RH) (< 40%) at 25°C, but also resulted in cell inactivation, with only 0.001% initial cells recovered after 72 h incubation. A significant effect of inoculum density on disease severity was observed and 10 6 CFU/ml was determined as the minimal infective dose for X. arboricola pv. pruni on Prunus. Infections occurred at temperatures from 15 to 35°C, but incubation at 25 and 30°C gave the shortest incubation periods (7.7 and 5.9 days respectively). A model for predicting disease symptom development was generated and successfully evaluated, based on the relationship between disease severity and the accumulated heat expressed in cumulative degree day (CDD). Incubation periods of 150, 175 and 280 CDD were required for 5, 10 and 50% of disease severity, respectively.