Location: Sustainable Agricultural Systems Laboratory
Project Number: 8042-22000-167-096-R
Project Type: Reimbursable Cooperative Agreement
Start Date: Jan 1, 2024
End Date: Dec 30, 2024
Objective:
Our overarching goal is to develop mapping technology of cover crops, cash crops, and weeds.
Our specific goals are to refine precision agriculture technology (computer vision and artificial intelligence tools) to estimate and map weed density and biomass in US soybean production regions, and build a web-based application that automates data analysis and visualization for both farmers and researchers.
Approach:
The research will be carried out at two scales: in small-plots using a hand-held camera system, and on-farm using tractor-mounted cameras. We anticipate expanding this work to include drones in years two and three. Our network has developed two systems that are both inexpensive and efficient in collecting weed density and biomass. The first system uses a 3-D reconstruction technique (monocular camera and structure from motion analysis of digital videos) using a hand-held pole-mounted GoPro camera. The second system is a tractor-mounted sensor box consisting of multi-spectral, LiDAR, and ultrasonic sensors. Coupled with the data flow systems already developed by our network, both systems are expected to accelerate efficient data collection throughout the growing season and across locations. A mobile app has also been developed for collecting pertinent meta-data that accompanies the collected video data. These technologies have already been beta-tested at select locations in the US. This project will greatly expand the coverage across important US soybean production regions and calibration for more weed species. Further, we will develop a web-based user interface that automates data analysis, visualization, and recommendation systems.
