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Data-gathering helps prevent crop disease

Rashelle Matthiesen presents to guests at the Southeast Iowa Research Farm on the data collection used for tar spot risk modeling. (Kalen McCain/The Union)
Two different spore traps (high-tech and low-tech) collect samples from Iowa fields. Data gathered by plant pathologists is used to model the risk of diseases like tar spot. (Photo courtesy of ISU Extension Office)
A close-up photo of tar spot spores, by Edward Zaworski, Iowa State University

CRAWFORDSVILLE — In the months after planting season, once corn start tasseling, farmers will face a difficult decision several times before harvest: spray fungicide for $15-$30 an acre, or cross their fingers and hope they don’t lose crops to tar spot.

When weather gets humid and leaves stay wet, plant pathologists say there’s a risk of developing the yield-wrecking fungus on corn, cotton and wheat. However, risk factors for the disease don’t line up perfectly with the likelihood of infections.

In fact, even the presence of tar spot spores doesn’t mean a high chance of disease. A problem only develops if an area has viable hosts (like corn,) effective pathogens (the spores) and a favorable environment (high humidity and heat.)

"With foliar diseases in Iowa, some years they can have a more significant impact on yield than other years,“ said Project Research Scientist and ISU Plant Pathologist Rashelle Matthiesen, who presented on data modeling for the fungus in a talk at the Southeast Iowa Research Farm in early March. ”The tricky thing is helping farmers to know when to spray, because a lot of time infection occurs before you can see the symptoms. So you need to know before it explodes, were the conditions conducive for this pathogen to infect?“

Matthiesen is part of a team from Iowa State University that gathers data for predictive models on the spread of tar spot. Researchers set up spore traps and hold routine inspections in fields to measure local conditions, along with spore counts for the fungus. Their data is sent to other professionals working on a nine-state forecast for the disease.

The model is currently implemented on a free app called Tar Spotter, available for most smartphones. Its recommendations are based on small-plot tests that compare fields with and without fungicides under various conditions.

“You enter the data from your field, the weather data, what you’re doing … and then it will give you a prediction of whether you should spray or not,” Matthiesen said. “And then these prediction model tools are being looked at and analyzed … each year, we’re going back to find out if that actually worked or not.”

Alison Roberts is a lead scientist on the project, an Iowa State professor and extension field crops pathologist.

In a call from Ames, she said models could allow farmers to make better-informed decisions.

“The only thing you can do is spray a fungicide to control some of these diseases,” she said. “By having these disease prediction tools, instead of farmers just spraying a fungicide as insurance, or to help them sleep better at night, we would have these tools that would help with more judicial use of fungicides, which would be better for everyone. The environment and the farmer.”

Beyond the data’s use by farmers, Roberts said it was useful for scientists like herself, looking into more detailed factors affecting tar spot and other plant diseases.

She said it was exciting to have funding for the research, which began three years ago.

“It gives me a better understanding of what diseases are developing and where,” she said. “If you have a better understanding of something, you have a better understanding of how to manage that … we’ve learned a ton over the last three years of this project thanks to the funding. And because of our improved knowledge, we can then develop better management tools to help farmers manage these diseases and therefore protect their yield.”