Robot Leaf Analyzer
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 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.
As part of the project, the group is developing a robotic pressure chamber that can autonomously sample leaves and immediately test them on site to provide the freshest data. The system will work to gather data even in large fields, and over a period of time, rather than just providing a snapshot.
Frequently updated data can help growers better plan irrigation schedules to conserve water, optimize the time and effort spent by crop specialists tasked with determining and analyzing lead water potential, and help decrease some of the costs in the food-production chain.
Current measuring techniques involve collecting leaf samples and transporting them to an off-site location, where testers can use very accurate, expensive pressure chambers; or sampling and analyzing leaf samples in the field using hand-held pressure chambers.