Abstract
Lettuce is a key dietary vegetable, and efficient intra-row weed control is vital for optimizing yield. However, rising labor costs, environmental hazards of herbicides, and the expense of laser-based systems hinder automated solutions. This study presents an intelligent intra-row weeding robot integrating an optimized YOLOv11l-based vision system and a mechanical weeding platform. The model achieved high detection metrics (Precision 99.699%, Recall 99.863%, mAP50 99.499%), outperforming other YOLOv11 variants. In conveyor belt tests, the system attained 84.579% lettuce localization and 81.058% weed removal rates across variable weed densities and speeds. Field trials confirmed robust performance, achieving up to 82.218% weeding efficiency and injury rates below 2.6% under varying lighting and travel conditions. The proposed system offers a high-accuracy, efficient solution for precision lettuce weeding, promoting sustainable agricultural practices.
| Original language | English (US) |
|---|---|
| DOIs | |
| State | Published - 2025 |
| Event | 2025 American Society of Agricultural and Biological Engineers Annual International Meeting, ASABE 2025 - Toronto, Canada Duration: Jul 13 2025 → Jul 16 2025 |
Conference
| Conference | 2025 American Society of Agricultural and Biological Engineers Annual International Meeting, ASABE 2025 |
|---|---|
| Country/Territory | Canada |
| City | Toronto |
| Period | 7/13/25 → 7/16/25 |
Bibliographical note
Publisher Copyright:© 2025 ASABE. All rights reserved.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 2 Zero Hunger
-
SDG 8 Decent Work and Economic Growth
-
SDG 12 Responsible Consumption and Production
Keywords
- Deep learning
- Lettuce
- Mechanical weeding
- Robot
- Weed control
Fingerprint
Dive into the research topics of 'An Intelligent Robot Based on Optimized YOLOv11l for Weed Control in Lettuce'. Together they form a unique fingerprint.Cite this
- APA
- Standard
- Harvard
- Vancouver
- Author
- BIBTEX
- RIS