Targeted weed management of Palmer amaranth using robotics and deep learning (YOLOv7)
Problem
Traditional herbicide spraying is indiscriminate, harming the environment and crops; Palmer amaranth is Nebraska's most troublesome weed.
Why it matters
Targeted spraying could cut herbicide use, environmental damage, and crop losses.
What the AI did
Developed a full-stack AI-enabled weeding robot using YOLOv7 object detection for real-time weed identification and precision spot spraying.
Results
60.4% average precision and 62% recall in real-time weed identification and spot spraying
Impact
Evidence supports a working prototype identifying weeds across growth stages, but only in controlled conditions and with modest precision.
Record
| Venue | Frontiers in Robotics and AI |
|---|---|
| Published | 2024 |
| Work type | article |
| Authors | Amlan Balabantaray, Shaswati Behera, CheeTown Liew, Nipuna Chamara, Mandeep Singh, Amit J. Jhala, Santosh Kumar Pitla |
| Citations | 22 (OpenAlex, at import time) |
| References | 17 |
| Model or method | YOLOv7 |
| Organization | not stated in source |
| Primary source | https://doi.org/10.3389/frobt.2024.1441371 |
| Open access | gold |
| Keywords | YOLOv7, weeding robot, Palmer amaranth, precision spraying, deep learning, agriculture |
Importance rating
significant — thousands to millions affected
Indiscriminate herbicide use harms environment and crops; targeted spraying could cut herbicide use across agronomic crops; Palmer amaranth called Nebraska's most troublesome weed, but no scale quantified.