Azghadi, Mostafa Rahimi, Olsen, Alex, Saleh, Alzayat, Wood, Jake, Granshaw, Terry, Fillols, Emilie, and Philippa, Bronson (2024) Precise robotic spot-spraying of weeds for improved environmental and economic outcomes in the sugarcane industry. In: Proceedings of the 45th Conference of the Australian Society of Sugar Cane Technologists. pp. 339-344. From: ASSCT 2024: 45th Annual Conference of the Australian Society of Sugar Cane Technologists, 16-19 April 2024, Townsville, QLD, Australia.

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Abstract

The outcomes of an innovative project, funded by the partnership between the Australian Government's Reef Trust and the Great Barrier Reef Foundation, aimed at enhancing water quality in reef catchments and reducing input costs for sugarcane farmers, are presented. Our robotic spot spraying tool, AutoWeed, utilises artificial intelligence and computer vision technology to significantly decrease herbicide usage on sugarcane farms. Field trials comparing AutoWeed to industry standard broadcast spraying demonstrate its effectiveness, with a 97% efficacy and a 35% reduction in herbicide use, proportional to weed density, on 25 ha across six trials. Moreover, AutoWeed spot spraying shows a 39% reduction in herbicide concentration and a 54% reduction in herbicide load in irrigation runoff 3-6 days after spraying compared to broadcast spraying. These findings highlight the potential of AutoWeed to curtail herbicide use on sugarcane farms while maintaining effective weed control and fostering sustained water-quality benefits.

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