As weeds become more adept at evading control, researchers in Arkansas and elsewhere are testing whether machine learning can improve weed management and save farmers money. 

Jason Norsworthy, distinguished professor of weed science with the University of Arkansas System Division of Agriculture, has been evaluating the combination of image recognition software and machine learning that comprises John Deere’s See & Spray Ultimate system. 

Norsworthy’s work is part of the Arkansas Agricultural Experiment Station, the research side of the University of Arkansas System Division of Agriculture. 

Norsworthy will discuss his research and a demonstration of the See & Spray Ultimate will be provided during a field day set for Aug. 23 at the Northeast Research and Extension Center at Keiser in northeast Arkansas. 

“I’m in the second year of testing the machine learning in this system,” Norsworthy said. “This field day will give our Mid-South growers an opportunity to see it in action compared to a standard broadcast system.” 

The field day opens at 9:30 a.m., with field tours going until 11:15 a.m. The action will head indoors for lunch and with a panel discussion and Q&A with Norsworthy; William Patzoldt, director of agronomy for Blue River Technology, which led the software development; a farmer familiar with the system; and a representative from John Deere. 

The field tours include a demonstration of the technology, tips for herbicide savings while maintaining effective control; effect of sensitivity settings on detection and spray application and the effectiveness of the See & Spray Ultimate weed control in cotton and soybean production. 

Pre-event registration incentive 

Attendees are asked to register in advance. Pre-event registrants will be eligible to be one of 10 people selected to ride in the cab of the See & Spray Ultimate sprayer following lunch. The registration deadline is Aug. 19. Registration is available online. 

Source: University of Arkansas System Division of Agriculture which is solely responsible for the information provided and is wholly owned by the source. Informa Business Media and all its subsidiaries are not responsible for any of the content contained in this information asset.