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ARS Home » Plains Area » Fargo, North Dakota » Edward T. Schafer Agricultural Research Center » Sugarbeet Research » Research » Publications at this Location » Publication #413012
Research Project: Improving Sugarbeet Productivity and Sustainability through Genetic, Genomic, Physiological, and Phytopathological Approaches

Location: Sugarbeet Research

Title: Autonomous four-wheel drive electric vehicle for site-specific weed control

Author
item ESHKABILOV, SULAYMON - North Dakota State University
item Kim, James

Submitted to: ASABE Annual International Meeting
Publication Type: Abstract Only
Publication Acceptance Date: 3/19/2024
Publication Date: N/A
Citation: N/A

Interpretive Summary: This paper discusses an electric vehicle (EV) for weed management. Weeds are unwanted plants that complete with crops for water and nutrients and thus causes yield loss and genetic resistance to herbicides. This four-wheel drive EV is integrated with a prescription weed map created by drone imagery data to apply site-specific weed control using non-toxic treatments such as mechanical cultivation and thermal spray. The EV is capable of maximum 5 mph and 1000 lb payload. The proposed toxic-free weeding system will be beneficial to growers to improve yield and soil fertility and protect environment and human from adverse effects of herbicides.

Technical Abstract: Weed control is critically important for farmers to diminish yield losses due to weed spread. There are a few commonly used practices such as pesticide application, mechanical weed removal, crop rotation, cover cropping, biological control, and genetic weed resistance crop development. We are proposing a site-specific weed control system to deplete weeds in sugarbeet fields using non-toxic treatment such as a mechanical tillage system and thermal spray equipment installed on a robotic platform that is four-wheel driven by hub motors. The proposed all-terrain electric-powered autonomous vehicle's is equipped with up to 5 mph cruising speed and 1000 lb payload. Our proposed system will be integrated with the drone imagery data for a prescription weed map to apply non-toxic site-specific weed control principles that promote sustainable weed management by minimizing unnecessary tillage and energy consumption, and save environment and human health from toxic herbicides.