To determine water needs accurately, growers hand-pluck individual leaves from plants, put them in pressure chambers, and apply air pressure to see when water begins to leak from the leaf stems. That kind of testing is time consuming and means growers can only reach so many areas of a field each day and cannot test as frequently as needed to accurately determine optimal irrigation scheduling patterns.

A group of researchers from UC Riverside and UC Merced have received a grant for more than $1 million from the U.S. Department of Agriculture through the National Science Foundation’s National Robotics Initiative to address these challenges. From UC Riverside are Assistant Professor Konstantinos Karydis and Professor Amit K. Roy-Chowdhury, both from the Department of Electrical and Computer Engineering. UC Merced, which leads the effort, is represented by Stefano Carpin, professor of computer science; and Joshua Viers, professor of environmental engineering.

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