Researchers are combining laser scanning and 3D printing to create detailed models of sugar beet plants. These models, generated by Jonas Bömer and colleagues from the Institute of Sugar Beet Research and the University of Bonn, offer an innovative approach to crop improvement by capturing essential plant characteristics for AI-assisted phenotyping.
Using LIDAR technology, a real sugar beet plant was scanned from 12 angles to produce 3D data, which was then processed and printed into a life-sized model. This model serves as a reproducible reference for field use, facilitating accurate sensor measurements and data collection.
Plant phenotyping, the process of collecting precise plant data, has evolved significantly with automation and AI. Traditional human-based measurements have given way to automated pipelines that improve efficiency and capture complex plant traits, such as leaf orientation and growth parameters.
The 3D printed sugar beet model provides a standardized reference that enhances the accuracy of sensor-driven phenotyping. Its availability for free download ensures consistency across different research labs worldwide. The affordability of 3D printing also allows this technology to be adopted in resource-limited settings.
The approach demonstrated in this study is not limited to sugar beets. It offers potential applications for other crops, presenting a cost-effective phenotyping strategy that could benefit global agriculture, including regions requiring low-cost solutions.
Source: eurekalert.org
