Researchers at Southern Illinois University Carbondale are working on a new approach to soybean disease detection that could help farmers catch problems before they ever see a symptom. Billy Ram, an assistant professor of precision agriculture, and doctoral student Samuel Singh are designing a robot equipped with artificial intelligence to spot soybean diseases early. The team hopes agricultural machinery companies will eventually turn the technology into affordable tractor or spray attachments for farmers.
Why Soybean Diseases Threaten Illinois Farmers’ Profits
Illinois leads the nation in soybean production, with roughly 43,000 farmers depending on the crop to support their families and farms. Soybean prices have climbed over the past two decades, rising from an average of $6.15 per bushel between 2000 and 2004 to $12.71 per bushel between 2020 and 2024, according to the Illinois Soybean Association. However, non-land costs have also surged, with some farmers reporting a 400% jump in expenses over that same period.
Weather, pests, weeds and disease all cut into that already thin profit margin. Many soybean diseases come from fungi living in the soil, and rain helps spread them across a field, Ram said. By the time lesions show up on stems or leaves, the damage is often done.
“If a disease overpowers your field, late-stage fungicide application is not very efficient,” Ram said. “Once the disease attacks the farmer’s crops, the yield can be reduced to 60 to 70%. It has a real economic impact.” Because these soil-borne fungi can linger for years, they threaten multiple growing seasons instead of just one.
Building a Robot for Soybean Disease Detection
Ram and Singh are testing their work on a soybean field at University Farms affected by frogeye leaf spot, a disease that causes lesions on leaves and can spread to stems and pods. The team first tried using a drone to capture hyperspectral and multispectral images, which rely on wavelengths invisible to the human eye. Despite flying close to the crop, however, the drone could not gather enough data to reliably detect the disease.
The problem was location, not equipment. Frogeye leaf spot often hides on the underside of leaves and lower on the stem, areas a drone’s camera struggles to reach. “At the end of the day, we’re only working with cameras,” said Ram, whose research received funding through the Illinois Soybean Center. “We’re solving an engineering problem more than an agronomic problem.”
As a result, the team built a battery-powered, four-wheeled robot with GPS and multiple cameras mounted to view both the tops and undersides of soybean plants. Users can upload a field map, and the robot follows the rows on its own. “The robot should be able to drive down the field, keep track of each plant, identify if the plant has a disease and which type, and then share what percentage of the crop is diseased,” Ram said.
Mapping Hot Spots With AI Models
With the robot built, Ram and Singh are now developing the AI models needed to identify frogeye leaf spot with precision. Singh wants the finished system to generate maps that pinpoint disease hot spots instead of treating an entire field the same way. That would let farmers apply fungicide only where it’s needed, saving money and reducing chemical use.
“Soybean diseases are a problem all over Illinois,” Singh said. “This project is challenging, but it’s exciting because I think we can develop these maps.” Singh, who holds a bachelor’s degree in agricultural engineering and a master’s in remote sensing, has talked with local farmers at SIU agriculture events to better understand their day-to-day challenges.
“As an engineer, we love working on solutions that actually help people, not just something that sounds good on paper,” Singh said. Meanwhile, he added that the long-term goal is simple: use robots to make farming more efficient and less labor-intensive.
SIU’s Research Status Supports the Project
Singh chose SIU partly because of its Research 1 designation from the Carnegie Foundation for the Advancement of Higher Education, a distinction that places the university among the top 5% of research institutions nationally. “SIU is a R1 research facility so there’s a lot of quality research coming out of this university,” Singh said. “You get the exposure that you need. You get the expertise and guidance.”
Ram said the designation also brings real benefits for students and faculty working in agriculture, including access to advanced robotics and AI facilities close to campus. “We’re really focused on doing not just the day-to-day research but research that will be fruitful in the next 10 years,” he said.
The project remains in progress, but it points to a future where soybean disease detection happens automatically and long before a farmer would notice trouble by eye. For growers battling shrinking margins and unpredictable weather, that kind of early warning could protect both yield and profit. Farmers and agribusiness companies alike should watch for updates as Ram and Singh refine their AI models over the coming growing seasons.
Readers interested in the university’s ongoing agricultural research can learn more by visiting Southern Illinois University’s website. This story is based on a press release from Southern Illinois University Carbondale.