Apr 13, 2016

WSU-developed tech could give growers better harvest data

New technology could help specialty crop growers get more out of their harvests, WSU researchers report in the March issue of “Computers and Electronics in Agriculture.”

Most growers of specialty crops like fruits, vegetables and tree nuts pay harvesters by the bin or bucket-full. But piece-rate work can be rife with inaccuracies, with some growers overpaying by tens of thousands of dollars.

In their paper, “Cloud-based harvest management information system for hand-harvested specialty crops,” researchers with California State University at Bakersfield, the WSU Center for Precision and Automated Agricultural Systems, the WSU School of Electrical Engineering and Computer Science, and the WSU Department of Horticulture lay out a fairer approach that relies on smart data collection.

Lead author Dr. Yiannis Ampatzidis, former postdoctoral scientist at the WSU Irrigated Agriculture Research and Extension Center in Prosser, now assistant professor of engineering at California State University, Bakersfield, worked with WSU horticulture professor Dr. Matt Whiting to develop the FairWeigh system. Tested in sweet cherry, blueberry and apple orchards in Washington, FairWeigh uses radio-frequency ID tags, GPS modules and cloud computing to record and upload data each time a picker brings a bucket of fruit to a collection bin.

FairWeigh measures the weight of harvested fruit, and the time and location of every fruit drop, then transmits that data wirelessly to a computer server. Growers can use that data to understand yields in real time, increase accuracy on their payroll, and improve picker safety and fruit quality, ultimately making their harvest more efficient.

“With today’s computing capability, data can be collected and analyzed efficiently,” said Dr. Li Tan, a co-author and WSU computer science professor who created and patented the software that analyzes FairWeigh data. “That helps build a data-driven agricultural operation, improving efficiency through data science.”

Read the paper here.

— Seth Truscott, Washington State University