A gardener expecting the juiciest summer tomato crop might tend to every plant in a plot. However, that may not be the case with a farmer who toils to feed the world.
Scientists are now confident that this could be possible. They have been using and combining layers of technologies—such as artificial intelligence, machine learning, sensors, high-throughput phenotyping platforms like small-scale rolling robots and drones that can also weed, fertilize, and cull single plants in a field—with the eventual aim of substituting the dependence of farmers on heavy machinery and broadcast spraying in operations of all sizes.
The researchers have named their effort COALESCE—COntext Aware LEarning for Sustainable CybEr-agricultural systems. They recently won a five-year, $7 million Cyber-Physical Systems Frontier award collaboratively funded by the National Science Foundation and the U.S. Department of Agriculture’s National Institute of Food and Agriculture.
The researchers introduced the most advanced cyber capabilities in sensing, modeling, and reasoning to the real world of plants and soil. They reported that this will “enable farmers to respond to crop stressors with lower cost, greater agility, and significantly lower environmental impact than current practices.”
Soumik Sarkar, the Walter W. Wilson Faculty Fellow in Engineering and an associate professor of mechanical engineering at Iowa State University, is the lead principal investigator for the project. Girish Chowdhary, an associate professor of agricultural and biological engineering at the University of Illinois Urbana-Champaign, is a partner principal investigator.
The team also includes colleagues from George Mason University in Virginia, the Iowa Soybean Association, Ohio State University, and the University of Arizona.
Beyond Precision Agriculture
“You hear about precision agriculture all the time,” noted Sarkar, denoting the practice of monitoring crops and soils to ensure they get precisely what they require for maximum production while minimizing the need for pesticides, fertilizers, and other costly and potentially polluting inputs. “Now, we’re trying to move another notch above that.”
Call that “ultra-precision agriculture, which is scale agnostic,” stated Asheesh (Danny) Singh, a professor of agronomy and the Bayer Chair in Soybean Breeding at Iowa State.
A lot of agricultural problems start in a small area of a field. We want to localize problems early on—make decisions and start controls before they affect the whole field and adjoining farms. Working at the plant level gives us that ultra-high precision with row crops such as soybeans.
Asheesh Singh, Professor of Agronomy and Bayer Chair in Soybean Breeding, Iowa State University
The researchers added that the technology would also be economical and sufficiently accessible to assist producers who grow vegetables and other specialty crops on farms of different sizes.
The concepts on which COALESCE are based have been making rounds in the Iowa State campus for many years and have resulted in the development of a core research team: Sarkar; Singh; Baskar Ganapathysubramanian, the Joseph C. and Elizabeth A. Anderlik Professor in Engineering; and Arti Singh, an assistant professor of agronomy.
Moreover, the concepts have been awarded various competitive grants, for example, an initial grant to the core team from the Iowa Soybean Association with Arti Singh as the principal investigator. In addition, a three-year seed grant was awarded to the core team from Iowa State’s Presidential Initiative for Interdisciplinary Research. These grants enabled the researchers to achieve initial discoveries and collaborate with other researchers.
A project known as “Data Driven Discoveries for Agricultural Innovation,” which is a demonstration from the seed project, depicts an airplane, three drones, and four robots gathering data from a field to help the farmer standing to the side.
How useful can all that data be to a farmer?
Data science isn’t just about assembling data and making predictions. It’s also about making decisions.
Baskar Ganapathysubramanian, Joseph C. and Elizabeth A. Anderlik Professor in Engineering, Iowa State University
Where are plants affected, for instance, by pests, poor soils, or dry conditions? And what could be the solution for that?
A collaboration with the Iowa Soybean Association has helped discuss such data-to-decision scenarios with farmers. Arti Singh noted that farmers show interest in the potential of ultra-precision agriculture.
“They’re the ones who said, ‘Yes, this is possible,’” she added. However, more efforts will be required to get there.
The advent of an ultra-precision, cyber-physical system for agriculture “cannot happen without the level of investment provided by this Frontier project,” noted Asheesh Singh. “And without the expertise on this team, and the partnership with farmers, work like this cannot happen.”