Field evaluation of smart spray systems in Oregon nursery production

Sunday, November 10, 2013: 3:39 PM
Meeting Room 8 AB (Austin Convention Center)
Robin Rosetta , Department of Horticulture, Oregon State University, Aurora, OR
Heping Zhu , Application Technology Research Unit (ATRU), USDA, ARS, Wooster, OH
Derek Wells , North Willamette Research and Extension Center, Oregon State University, Aurora, OR
Adam Clark , Application Technology Research Unit (ATRU), USDA-ARS, Wooster,, OH
Research on the field efficacy of two smart sprayer prototypes is being conducted in Oregon nurseries. The goal of this research is to develop sprayers that use technology to detect crop size and presence, and that vary the flow of pesticides from nozzles based on this information during applications. The first prototype, a modified hydraulic vertical boom system on a high ground clearance sprayer (TR-4 Tracker; GK Machine, Inc., Donald, OR), utilizes ultrasonic sensors to detect the size and volume of liner-sized plants. One side of the sprayer (three sections) was retrofitted with the intelligent spray control system, and the other side (three sections) remained as a conventional spray system which allowed paired comparisons between intelligent and conventional treatments simultaneously for the field trials. Field tests evaluated insect and disease control (powdery mildew on Norway maple and aphids on red oak) and determined no significant difference between the smart and conventional sprayers while the smart sprayer used less than 45% of pesticides and spray volume compared to the conventional sprayer. The second prototype is an air-assisted system utilizing a high-speed laser scanning sensor to measure plant structure and foliage density. Evaluation of field efficacy of insect (honeylocust pod gall midge) and disease (pear rust) control is ongoing at the time of this writing. Laboratory and field tests demonstrated that both of the smart sprayer designs had the capability to control spray outputs, matching canopy characteristics in real time, with the potential to drastically decrease pesticide usage thus reducing environmental impact, labor and pesticide costs.