By Janan Shoja Doost
A University of Guelph researcher is using artificial intelligence (AI) and robotics to improve how crop diseases are detected and managed, making the process faster, more accurate and more efficient for farmers.
Dr. Gurjit Randhawa, a professor in the School of Computer Science within the College of Computational, Mathematical, and Physical Sciences, collaborated with Dr. Aitazaz Faroque of the University of Prince Edward Island to apply machine learning tools to detect crop diseases in potato fields on Canada’s Atlantic coast.
This work, supported by the Prince Edward Island Potato Board and the Government of New Brunswick, focused on developing AI models to detect Potato Virus Y (PVY), a major challenge for potato farmers that can jeopardize seed certification and spread rapidly across fields.
Manual scouting for PVY is labour-intensive and relies on experienced workers to identify subtle symptoms, says Randhawa.
“It’s exhausting work. I wanted to build something practical – robots that could do this with accuracy and speed,” he says.
Randhawa and his team developed AgriScout, an autonomous scouting robot that uses computer vision and AI models to identify infected plants in real-time. The robot’s high-precision geotagging system, accurate to within half a centimetre, enables efficient mapping and removal of diseased plants.
The results were published in August 2025 in Computers and Electronics in Agriculture and showed that the robot achieved comparable accuracy to human experts in early-stage detection.
“It’s not just about technology – it’s about solving real problems that farmers face,” says Randhawa. “When farmers see what the robot can do, they’re excited. It’s encouraging to know this can have a real impact on the ground.”
With funding from the Ontario Agri-Food Innovation Alliance, Randhawa is now expanding his work to Ontario soybean fields to detect white mould, a persistent soilborne disease. A new robot, equipped with thermal and multispectral cameras, is being tested this summer to monitor the environmental conditions that trigger mould outbreaks.
The project is funded by the Natural Sciences and Engineering Research Council (NSERC). The Ontario Agri-Food Innovation Alliance is a collaboration between the Government of Ontario and the University of Guelph.