Effects of leaf wetness duration and temperature on infection of Prunus by Xanthomonas arboricola pv. pruni

Abstract

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.

Mechanistic insights into host adaptation, virulence and epidemiology of the phytopathogenXanthomonas

“…Xanthomonas spp. thrive better on slightly higher temperatures (on average 25-35 • C) and are capable to reach high enough inoculum in the host to allow dispersal (Christiano et al 2009;Morales et al 2018a;2018b). In addition, high humidity was found to be required for epiphytic survival and transmission (Christiano et al 2009).…”

“… 2009 ; Morales et al . 2018a ; 2018b ). In addition, high humidity was found to be required for epiphytic survival and transmission (Christiano et al .…”

Species Richness, rRNA Gene Abundance, and Seasonal Dynamics of Airborne Plant-Pathogenic Oomycetes

“…The inconsistency between the correlations found in our study and the disease forecasting system might be due to different factors, such as the 7-day sampling periods used in this study. Furthermore, although plant infection risk correlates with RH and temperature ( Palmieri et al, 2006 ; Li et al, 2014 ; Morales et al, 2018 ), atmospheric gene abundance of Oomycetes may not. The positive correlation with RH in fall could indicate preferential aerial transport under humid conditions, which is in agreement with previously reviewed dispersal of fungal and Oomycetes pathogens in tropical areas ( Drenth and Guest, 2016 ).…”

Environmental and inoculum effects on epidemiology of bacterial spot disease of stone fruits and development of a disease forecasting system

“…The infection threshold of 10 6 CFU/ml should be included in the forecasting system to link the epiphytic inoculum potential and the infection model. Therefore, the infection model (second component) developed and validated previously (Morales et al 2018) will start working when the inoculum potential predicted by the growth model is high enough to cause infections. Therefore, if the infection model predicts favorable weather conditions for initiating an infection process, the symptom model will run for prediction of disease symptoms appearance on the basis of daily mean temperature and CDD.…”

“…Thus, the combined effects of wetness period duration and temperature on infection of Prunus by X. arboricola pv. pruni were analyzed under controlled environment conditions and an infection risk model was developed (Morales et al 2018). The model was successfully validated under greenhouse conditions and, after field evaluation, it could be used to forecast the X. arboricola pv.…”