K-State researchers are advancing AI-powered crop pest detection.
Researchers at Kansas State University (K-State) are testing the Insect Eavesdropper, a technology that uses microphones, artificial intelligence, and data analysis to detect hidden insect activity in crops. The system could help farmers identify pest problems earlier and improve crop monitoring.
Graduate student Emily Sur is leading field research that involves placing microphones on soybean plants to record insect sounds and vibrations. Researchers then compare the recordings with plant inspections to determine how effectively the technology detects pests.
“I've always enjoyed being outdoors, so that's one of the things that drew me to this project, getting to work outside in the fields,” said Sur.
The project is part of a multistate collaboration led by Emily Bick of the University of Wisconsin-Madison. The technology captures vibrations produced by insects feeding or moving inside plants, helping identify pests that are often difficult to see through traditional scouting methods.
At K-State, Sur works with Brian McCornack and other researchers to test the system under real farming conditions. Much of the research has focused on the soybean stem borer, a pest that is hard to detect because it tunnels inside plant stems.
“By using this new tool, we can detect these insidious invaders without needing to sacrifice plants,” McCornack said.
Researchers combine expertise in entomology, engineering, artificial intelligence, and data science to analyze large amounts of sound data. Their goal is to create a practical tool that provides continuous crop monitoring and supports better pest-management decisions.
The project is also giving students hands-on experience with research, technology, and problem-solving. Participants gain valuable skills in data collection, troubleshooting, and interdisciplinary collaboration.
By combining agriculture and advanced technology, the Insect Eavesdropper could help farmers detect hidden crop threats sooner and respond more effectively. Researchers believe the system has strong potential to improve crop health monitoring and support sustainable agricultural production.
Photo Caption: A soybean plant is clipped with a recording device that is ready to "eavesdrop" on soybean stem borers.
Photo Credit: Kansas State University