Resistance to Fluopicolide and Propamocarb and Baseline Sensitivity to Ethaboxam Among Isolates of Pseudoperonospora cubensis From the Eastern United States

Chemical control is currently the most effective method for controlling cucurbit downy mildew (CDM) caused by Pseudoperonospora cubensis. Most commercial cucurbit cultivars, with the exception of a few new cucumber cultivars, lack adequate disease resistance. Fluopicolide and propamocarb were among the most effective fungicides against CDM in the United States between 2006 and 2009. Since then, reduced efficacy of these two fungicides under field conditions was reported starting around 2013 but occurrence of resistance to fluopicolide and propamocarb in field isolates of P. cubensis had not been established. Thirty-one isolates collected from cucurbits in the eastern United States were tested for their sensitivity to fluopicolide and propamocarb using a leaf disc assay. This same set of isolates and four additional isolates (i.e., 35 isolates) were also used to establish the baseline sensitivity of P. cubensis to ethaboxam, an ethylamino-thiazole-carboxamide fungicide, which was recently granted registration to control CDM in the United States. About 65% of the isolates tested were resistant to fluopicolide with at least one resistant isolate being present in samples collected from 12 of the 13 states in the eastern United States. About 74% of the isolates tested were sensitive to propamocarb with at least one resistant isolate being among samples collected from 8 of the 12 states in the study. The frequency of resistance to fluopicolide and propamocarb was high among isolates collected from cucumber, while the frequency was low among isolates collected from other cucurbit host types. All isolates tested were found to be sensitive to ethaboxam and EC₅₀ values ranged from 0.18 to 3.08 mg a.i./liter with a median of 1.55 mg a.i./liter. The ratio of EC₅₀ values for the least sensitive and the most sensitive isolate was 17.1, indicating that P. cubensis isolates were highly sensitive to ethaboxam. The most sensitive isolates to ethaboxam were collected from New York, North Carolina, and Ohio, while the least sensitive isolates were collected from Georgia, Michigan, and New Jersey. These results show that ethaboxam could be a viable addition to fungicide programs used to control CDM in the United States.

Predicting the risk of cucurbit downy mildew in the eastern United States using an integrated aerobiological model

Cucurbit downy mildew caused by the obligate oomycete, Pseudoperonospora cubensis, is considered one of the most economically important diseases of cucurbits worldwide. In the continental United States, the pathogen overwinters in southern Florida and along the coast of the Gulf of Mexico. Outbreaks of the disease in northern states occur annually via long-distance aerial transport of sporangia from infected source fields. An integrated aerobiological modeling system has been developed to predict the risk of disease occurrence and to facilitate timely use of fungicides for disease management. The forecasting system, which combines information on known inoculum sources, long-distance atmospheric spore transport and spore deposition modules, was tested to determine its accuracy in predicting risk of disease outbreak. Rainwater samples at disease monitoring sites in Alabama, Georgia, Louisiana, New York, North Carolina, Ohio, Pennsylvania and South Carolina were collected weekly from planting to the first appearance of symptoms at the field sites during the 2013, 2014, and 2015 growing seasons. A conventional PCR assay with primers specific to P. cubensis was used to detect the presence of sporangia in rain water samples. Disease forecasts were monitored and recorded for each site after each rain event until initial disease symptoms appeared. The pathogen was detected in 38 of the 187 rainwater samples collected during the study period. The forecasting system correctly predicted the risk of disease outbreak based on the presence of sporangia or appearance of initial disease symptoms with an overall accuracy rate of 66 and 75%, respectively. In addition, the probability that the forecasting system correctly classified the presence or absence of disease was ≥ 73%. The true skill statistic calculated based on the appearance of disease symptoms in cucurbit field plantings ranged from 0.42 to 0.58, indicating that the disease forecasting system had an acceptable to good performance in predicting the risk of cucurbit downy mildew outbreak in the eastern United States.

Interactive Effects of Temperature and Leaf Wetness Duration on Sporangia Germination and Infection of Cucurbit Hosts by Pseudoperonospora cubensis

Outbreaks of cucurbit downy mildew caused by Pseudoperonospora cubensis are dependent on the weather but effects of temperature and leaf wetness duration on infection have not been studied for different cucurbits. To determine the effects of these two weather variables on sporangia germination and infection of cucurbit host types by P. cubensis, three host types; cucumber ('Straight 8'), cantaloupe ('Kermit'), and acorn squash ('Table Queen'), were inoculated and exposed to leaf wetness durations of 2 to 24 h at six constant temperatures ranging from 5 to 30°C in growth-chamber experiments. Sporangia germination was assessed after each wetness period, and leaf area infected was assessed 5 and 7 days after inoculation. Germination of sporangia was highest on cantaloupe (16.5 to 85.7%) and lowest on squash (10.7 to 68.9%), while disease severity was highest and lowest on cucumber and cantaloupe, respectively. Host type, temperature, wetness duration and their interactions significantly (P < 0.0001) affected germination and disease severity. Germination and disease data for each host type were separately fitted to a modified form of a Weibull function that characterizes a unimodal response and monotonic increase of germination or infection with temperature and wetness duration, respectively. The effect of host type on germination and infection was characterized primarily by differences in the upper limit parameter in response to temperature. Differences among host types based on other parameters were either small or inconsistent. Temperature and wetness duration that supported a given level of germination or infection varied among host types. At 20°C, 15% leaf area infected was expected following 2, 4, and 8 h of wetness for cucumber, squash, and cantaloupe, respectively. When temperature was increased to 25°C, 15% disease severity was expected following 3, 7, and 15 h of wetness for cucumber, squash, and cantaloupe, respectively. Risk charts were constructed to estimate the potential risk of infection of cucurbit host types by P. cubensis based on prevailing or forecasted temperature and leaf wetness duration. These results will improve the timing and application of the initial fungicide spray for the control of cucurbit downy mildew.

Quantitative models for germination and infection of Pseudoperonospora cubensis in response to temperature and duration of leaf wetness

The influence of temperature and leaf wetness duration on germination of sporangia and infection of cantaloupe leaves by Pseudoperonospora cubensis was examined in three independent controlled-environment experiments by inoculating plants with a spore suspension and exposing them to a range of leaf wetness durations (2 to 24 h) at six fixed temperatures (5 to 30 degrees C). Germination of sporangia was assessed at the end of each wetness period and infection was evaluated from assessments of disease severity 5 days after inoculation. Three response surface models based on modified forms of the Weibull function were evaluated for their ability to describe germination of sporangia and infection in response to temperature and leaf wetness duration. The models estimated 15.7 to 17.3 and 19.5 to 21.7 degrees C as the optimum temperature (t) range for germination and infection, respectively, with little germination or infection at 5 or 30 degrees C. For wetness periods of 4 to 8 h, a distinct optimum for infection was observed at t = 20 degrees C but broader optimum curves resulted from wetness periods >8 h. Model 1 of the form f(w,t) = f(t) x (1 - exp{-[B x w](D)}) resulted in smaller asymptotic standard errors and yielded higher correlations between observed and predicted germination and infection data than either model 2 of the form f(w,t) = A{1 - exp[- f(t) x (w - C)](D)} or model 3 of the form f(w,t) = [1 - exp{-(B x w)(2)}]/cosh[(t - F)G/2]. Models 1 and 2 had nonsignificant lack-of-fit test statistics for both germination and infection data, whereas a lack-of-fit test was significant for model 3. The models accounted for approximately 87% (model 3) to 98% (model 1) of the total variation in the germination and infection data. In the validation of the models using data generated with a different isolate of P. cubensis, slopes of the regression line between observed and predicted germination and infection data were not significantly different (P > 0.2487) and correlation coefficients between observed and predicted values were high (r(2) > 0.81). Models 1 and 2 were used to construct risk threshold charts that can be used to estimate the potential risk for infection based on observed or forecasted temperature and leaf wetness duration.