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Robots and AI Help Save Multibillion Dollar Grape Crop

imaging robot

The robotic system can image samples from 351 grapevines in two hours.

Credit: Allison Usavage

Researchers at Cornell University are using robotics and AI technology to identify grape plants infected with a damaging fungus that attacks wine grapes and other plants.

Adjunct professor Lance Cadle-Davidson developed prototypes of imaging robots as part of a team at the U.S. Department of Agriculture's Agricultural Research Service. The robots could scan grape leaf samples automatically, but researchers were bottlenecked by the need to manually assess thousands of grape leaf samples for evidence of infection.

Assistant research professor Yu Jiang and his team used AI to address the issue, applying deep neural networks to analyze microscopic images of grape leaves.

"It has revolutionized our science," Cadle-Davidson says. "Yu's AI tools actually do a better job of explaining the genetics of these grapes than we can do sitting at a microscope for months at a time doing backbreaking work."

The team describes its work in "Deep Learning-Based Saliency Maps for the Quantification of Grape Powdery Mildew at the Microscopic Level," which won a best paper award at the 2021 American Society of Agricultural and Biological Engineers annual international meeting.

From Cornell University
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