By Andi Anderson
Soybean farmers across Illinois face a major challenge each year: drought. Limited rainfall can reduce crop growth, lower yields, and affect farm income. To address this issue, researchers are exploring advanced technologies that can help farmers identify crop stress earlier and make better management decisions.
Researchers at Southern Illinois University Carbondale (SIU) and the University of Missouri (Mizzou) are collaborating on a $300,000 project funded by the USDA National Institute of Food and Agriculture. The research focuses on using artificial intelligence (AI) and drone-based imaging technologies to monitor drought stress in soybean fields.
Illinois is the leading soybean-producing state in the United States, making soybean health and productivity especially important. According to the Illinois Soybean Association, thousands of farmers depend on successful soybean harvests to support their families and businesses. However, drought conditions can create water stress in plants, leading to leaf wilting, discoloration, and changes in leaf shape. If these signs are not detected early, crop losses can occur.
Traditionally, farmers monitor crop health through field observations. While effective, this method can be time-consuming, particularly for producers managing large farms. Stress symptoms may also vary across different sections of the same field, making regular monitoring more difficult.
“Our long-term goal is to make AI-based agricultural technologies more accessible and practical for farmers,” said Chao Lu, the professor leading the research for SIU. “Managing water resources is an important part of soybean production.”
As part of the project, researchers use drones to capture images of soybean fields. These images are then analyzed using AI models that can identify and evaluate different levels of drought-related plant stress. The technology is designed to complement traditional field scouting and provide farmers with additional information about crop conditions.
Researchers acknowledge that developing reliable AI systems presents several challenges. Agricultural environments are constantly changing due to differences in weather, lighting, soil quality, and plant growth patterns.
“While direct field observation provides valuable information, it can be difficult to apply consistently across large areas,” said Lu, a professor of electrical, computer and biomedical engineering. “The condition of soybean plants may also vary within the same field, making regular monitoring more challenging.”
“Soybean fields can vary considerably in soil conditions, weather, lighting, and plant growth,” Lu said. “Even within the same field, plants may experience different conditions, which can affect their appearance and growth patterns. These variations create challenges for AI-based analysis.”
The project also provides valuable educational opportunities. SIU graduate students are contributing to AI model development and agricultural data analysis while gaining hands-on experience in solving real-world farming challenges. Collaboration with Mizzou researchers further strengthens the project by combining expertise in engineering, technology, and agriculture.
“Engineering and agricultural research often approach problems from different perspectives,” Lu said. “By working with agricultural researchers, engineering students can gain a better understanding of the challenges faced in agricultural environments and how technical approaches may contribute to possible solutions.”
The research grant also supports outreach activities that allow researchers to share findings and introduce AI technologies to farmers and community members. These efforts help increase awareness of emerging agricultural innovations.
The project will continue through June 30, 2027, with researchers focused on improving AI models under a wider range of field conditions. Future work will also explore how drone imagery, soil measurements, and weather data can be combined to create more effective and affordable tools for farmers.
“One important direction is to examine how the models perform when field conditions differ from those represented in the existing research data,” Lu said. “This will help us better understand their strengths and limitations and identify areas where further improvements may be needed.”
As technology continues to advance, researchers believe AI and drone-based systems could become valuable tools for helping farmers manage drought challenges, improve crop health, and support long-term agricultural productivity.
Photo Credit: istock-psisa
Categories: Illinois, Sustainable Agriculture