The prototype uses a camera-based vision system to differentiate between crop plants and weeds; and then, based on the camera data, a sprayer nozzle is activated to spray weed-killer on individual weeds. The team is integrating the machine vision and sprayer assembly components and plan to test the prototype this summer, most likely in Salinas, California.
“We conducted field trials to determine their efficacy and the amount that hand-weeding labor requirements were reduced,” said Mark Siemens, a University of Arizona Cooperative Extension expert and researcher. “We also provided the opportunity to have growers evaluate the technology on their farm so they could make their own decisions about how the technology would fit into their farming operation.”