AutoWeed: AI Sport Spraying for Smarter Weed Control

AutoWeed is a collaborative project between JCU, AutoWeed Pty Ltd, and Sugar Research Australia, using artificial intelligence, computer vision, and robotics to detect and precisely spray weeds in sugarcane farming systems. Instead of blanket spraying entire paddocks, the technology identifies weed targets in real time and applies herbicide only where needed. This improves input efficiency, reduces chemical use, and helps lower the environmental risks associated with herbicide runoff into waterways linked to the Great Barrier Reef catchment.

The project has been developed with industry and government partners and tested under real farm conditions. Reported field results have shown weed knockdown performance close to conventional blanket spraying while substantially reducing herbicide use, demonstrating strong commercial and environmental potential. Current work is also extending toward AI-guided prescription mapping and region-specific deployment pathways.

AutoWeed is a strong example of JCU research delivering impact at the intersection of agriculture, engineering, AI, and sustainability. It supports more profitable farming, more targeted chemical use, and better environmental stewardship while helping position North Queensland as a leader in practical agtech innovation.

Project Team and Collaborators:
Professor Mostafa Rahimi Azghadi and JCU researchers; AutoWeed Pty Ltd; Sugar Research Australia; Reef Catchments; Queensland Department of Primary Industries; collaborating growers and regional stakeholders.

Funding Sources to be Acknowledged:

The Reef Trust Partnership, between the Australian Government and The Great Barrier Reef Foundation

Reef Place-Based Integrated Projects initiative funded through the Queensland Government’s Queensland Reef Water Quality Program.