Grant to Improve Cucurbit Downy Mildew Warning System
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Photograph: Cucurbit downy mildew. Photograph by Peter Ojiambo, Department of Plant Pathology.
Shortly after they rise in the morning, cucumber growers turn on their computers to know if it’s time to spray a fungicide on their crop or if they can put it off for another day. For the past few years, cucurbit producers have been using a cucurbit downy mildew warning system called the Cucurbit Downy Mildew (CDM) ipmPIPE and have counted on its forecasts about the risk of seeing downy mildew in their fields. This year, thanks to a new $136,000 USDA Regional IPM grant, the predictions they receive will be even more accurate.
Peter Ojiambo, NC State University plant pathologist and project director of the CDM ipmPIPE project, applied for the grant last year to conduct research to enhance specific components to the existing forecasting system. The funding has helped them improve the forecasts and delve deeper into a disease that can leave cucurbit growers with a useless field.
The CDM ipmPIPE project officially began in 2008, after Gerald Holmes, NC State University plant pathologist at that time, received a million dollar grant from USDA Risk Management Agency to establish a national warning system for cucurbit downy mildew (see Prospectives story, Winter 2010). The system relies on disease reports submitted to the forecasting website by state collaborators located in the eastern half of the country and weather forecasts from the National Weather Service and the State Climate Office at NC State.
Until now, forecasts about downy mildew risk have been based on the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. HYSPLIT calculates the trajectory of pollution particles based on atmospheric currents. Although the forecasts have helped growers protect their cucurbit crops more efficiently, the HYSPLIT model has several drawbacks, according to Ojiambo.
“HYSPLIT doesn’t take the pathogen biology into account, and the prediction should be driven by the biology of the pathogen versus simply the physical and atmospheric principles,” says Ojiambo. “You can’t go into the system to change the variables in the model.”
Ojiambo says that the downy mildew spores are sensitive to radiation, so the risk of infection is lower on a sunny day than on a day with heavy clouds and drizzle. Because HYSPLIT doesn’t account for spore death, its predictions can make the disease outlook seem more serious than it really is.
To account for weather variables that affect the life of the spores, NC State disease forecaster Thomas Keever has been generating the initial forecast with HYSPLIT and then adding the other variables by hand. A few months ago, however, Keever’s job became much easier. The team switched to a new dispersion model known as FLEXPART which has an open-source code.
“Before the new system, Thomas would spend 10 to 12 hours a day looking at models and figuring out the rest manually,” says Ryan Boyles, state climatologist. “Now the process is more automated. The map can account for deposition concentrations.”
Because he can change the variables within the weather model, Keever can generate a forecast more quickly. Growers now receive alerts about the risk of infection sooner.
With funding from the grant, Ojiambo can delve more thoroughly into the biology of downy mildew which specifically affects the spread of the disease. This past summer, he and his staff collected experiments using downy mildew spores, where spores were either exposed to the sun or placed under the shade during cloudy and sunny days. The tests will hopefully reveal what key environmental conditions affect the survival of the downy mildew spores. Results will provide new biological data which will be added to the weather model.
Next year, Ojiambo will run the same tests on pumpkins and squash. Each different cucurbit is infected by a different downy mildew pathogen. The goal is to capture and account for differences among the different cucurbit types.
Funding from USDA has helped the team make significant strides in the past three years, but Boyles says that the forecasts function more as guidance than true predictions.
“I would like to see us get to a point where we could predict by subspecies and get to the specific part of each county where the risk is highest,” he says. “A collection of spores will give us an idea of how accurate the forecasts are.”
Ultimately, the goal of the system is to help growers time their fungicide sprays more efficiently. Because of the expense of cucurbit fungicides, many growers don’t want to spray until they absolutely have to.
“The first spray is key,” says Ojiambo. “If you miss it, it’s tough to make up for it. The disease spreads fast, and most growers don’t have time to react. You have to make sure you catch it in time.”
For more information, or to sign up for cucurbit downy mildew alerts via e-mail, contact Peter Ojiambo atpojiamb@ncsu.edu.
Written by: Rosemary Hallberg, Former Communication Specialist, Southern Region IPM Center
Photograph: Cucurbit downy mildew. Photograph by Peter Ojiambo, Department of Plant Pathology.