This solution integrates high-resolution cameras, total stations, and UAVs to improve plant phenotyping accuracy. It addresses issues in 3D modeling accuracy and georeferencing, enabling faster and more reliable crop trait analysis.
This innovative solution integrates high-resolution cameras, total stations, and UAVs to enhance the accuracy of crop phenotyping. By addressing the limitations of traditional point cloud registration methods and improving georeferencing accuracy, this approach allows for more precise plant trait analysis, crucial for accelerating crop breeding processes. The integration of 3D modeling and deep learning further refines phenotyping, enabling faster identification of crop varieties that can adapt to climate change.
Key features:
This solution is currently at Technology Readiness Level 4, having been validated through initial experiments with ground robots. Further validation will be conducted using UAVs across different crops over a two-year period, in collaboration with industry partners.
Ghent University is a comprehensive public research university with a strong applied research and innovation culture. Industry collaborates through the Tech Lane Ghent Science Park, where corporate R&D, public research institutes and UGent labs are co‑located, and via a second science park in Ostend. Integration with Ghent University Hospital enables clinical translation and access to patient care environments. Research is backed by competitive European programmes such as Horizon Europe and the ERC, alongside national and regional support from FWO and VLAIO. UGent’s TechTransfer office, working with an Industrial Liaison Network and a central EU funding team, supports IP, licensing, spin‑offs and contract research to accelerate partnerships.