ASHS 2025 Conference

Broadcast herbicide applications across fallow fields with sparse weed populations can lead to substantial chemical waste, increased costs, and environmental impacts. To address this issue, we developed and evaluated a low-cost, vision-based targeted herbicide spraying system leveraging the Open Weed Locator (OWL) methodology using only the OWL hardware with project-specific custom software. It utilizes simple RGB cameras and image-processing algorithms to detect green vegetation (weeds) against soil backgrounds in real-time, triggering targeted herbicide application only where weeds are detected. The primary objective of this study is to assess the practical effectiveness of this technology in field conditions, focusing on use-cases relevant to fallow weed management scenarios. Field trials are planned to quantify the system’s performance by evaluating weed detection accuracy through metrics such as sensitivity, specificity and precision. Additionally, we will measure the percentage of herbicide chemical savings compared to conventional broadcast methods. Preliminary analyses suggest that this targeted approach significantly reduces chemical input. Detailed evaluations from forthcoming field trials will provide essential data to guide future improvements and support broader adoption of affordable, precision weed management tools.