UACES Facebook Machine learning vs weeds: Aug. 23 field day at Keiser to feature new tech to help farmers
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Machine learning vs weeds: Aug. 23 field day at Keiser to feature new tech to help farmers

Can machine learning help in the battle against ever-tougher weeds?

July 22, 2022

By Mary Hightower
U of A System Division of Agriculture

Fast facts

  • Field day set for Keiser in NE Arkansas
  • Program features research done with See & SprayTM Ultimate
  • Pre-event registration ends Aug. 19
  • Register online

(270 words)

(Newsrooms: With art https://flic.kr/s/aHBqjzXiN2

The Aug. 23 date is CQ)

FAYETTEVILLE, Ark. — 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 & SprayTM Ultimate system.

See and Spray rig at work in a soybean field
The See & Spray ™ system at work (Image courtesy John Deere. credit mandatory)

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 & SprayTM 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 & SprayTM 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 & SprayTM Ultimate sprayer following lunch. The registration deadline is Aug. 19. Registration is available online.

To learn more about Division of Agriculture research, visit the Arkansas Agricultural Experiment Station website: https://aaes.uada.edu. Follow on Twitter at @ArkAgResearch. To learn more about the Division of Agriculture, visit https://uada.edu/. Follow us on Twitter at @AgInArk. To learn about extension programs in Arkansas, contact your local Cooperative Extension Service agent or visit www.uaex.uada.edu.

About the Division of Agriculture

The University of Arkansas System Division of Agriculture’s mission is to strengthen agriculture, communities, and families by connecting trusted research to the adoption of best practices. Through the Agricultural Experiment Station and the Cooperative Extension Service, the Division of Agriculture conducts research and extension work within the nation’s historic land grant education system. 

The Division of Agriculture is one of 20 entities within the University of Arkansas System. It has offices in all 75 counties in Arkansas and faculty on five system campuses.  

The University of Arkansas System Division of Agriculture is an equal opportunity/equal access/affirmative action institution.  If you require a reasonable accommodation to participate or need materials in another format, please contact Mike Duren,  870-526-2199, mduren@uada.eduas soon as possible. Dial 711 for Arkansas Relay. 

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Media contact: Mary Hightower
mhightower@uada.edu

 

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