Researchers are revolutionizing crop improvement by combining laser scanning and 3D printing to create detailed models of sugar beet plants. Jonas Bömer and his team from the Institute of Sugar Beet Research and the University of Bonn have pioneered this innovative approach to AI-assisted phenotyping by capturing essential plant characteristics.
To generate these models, the researchers used LIDAR technology to scan a real sugar beet plant from 12 different angles, producing comprehensive 3D data. This data was then processed and used to create a life-sized 3D printed model. These models serve as reproducible references for field use, facilitating precise sensor measurements and data collection.
The field of plant phenotyping, which involves collecting accurate plant data, has seen significant advancements with the integration of automation and AI. Where measurements were once manually taken, automated systems now improve efficiency and capture complex traits like leaf orientation and growth parameters.
The 3D printed sugar beet models provide standardized references that enhance the accuracy of sensor-driven phenotyping. By making these models available for free download, researchers worldwide can ensure consistency in their studies. Additionally, the affordability of 3D printing technology makes it accessible even in resource-limited settings.
This method, though demonstrated with sugar beets, has potential applications for a wide range of crops. It presents a cost-effective strategy for phenotyping that could benefit global agriculture, particularly in regions that need low-cost solutions.
Source: eurekalert.org