Vision for Ultra-Precision Agriculture Includes Machine-Learning Enabled Sensing, Modeling, Robots Tending Crops

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A gardener hoping for a crop of the juiciest summer tomatoes might tend to each and every plant in a plot. But a farmer working to feed the world?

A gardener hoping for a crop of the juiciest summer tomatoes might tend to each and every plant in a plot. But a farmer working to feed the world?

Researchers believe that may be possible. They’re applying and integrating layers of technologies – including sensors, machine learning, artificial intelligence, high-throughput phenotyping platforms such as drones and small-scale rolling robots that can also fertilize, weed and cull single plants in a field – with the ultimate goal of replacing farmers’ reliance on heavy machinery and broadcast spraying in operations of all sizes.

The researchers call their effort COALESCE – COntext Aware LEarning for Sustainable CybEr-agricultural systems. They have just won a five-year, $7 million Cyber-Physical Systems Frontier award jointly funded by the National Science Foundation and the U.S. Department of Agriculture’s National Institute of Food and Agriculture.

Introducing the latest cyber capabilities in sensing, modeling and reasoning to the real world of plants and soil, the researchers wrote in a project summary, will “enable farmers to respond to crop stressors with lower cost, greater agility, and significantly lower environmental impact than current practices.”

Read More: Iowa State University

Researchers at the University of Illinois Urbana-Champaign have developed small-scale robots that can fertilize, weed and cull single plants in a field. This photo shows testing in an Iowa State University soybean plot. Larger photo. (Photo Credit: Ashlyn Rairdin and courtesy of Soumik Sarkar/Iowa State University)

https://www.news.iastate.edu/news/2021/04/29/coalesce