Recent research highlights the integration of laser scanning and 3D printing to advance crop breeding. The study, published in GigaScience, presents a detailed 3D model of a sugar beet plant, capturing essential characteristics of the plant’s above-ground parts. This model is designed for use in AI-assisted crop improvement pipelines, offering reproducibility and practicality for field applications.
The 3D models, created using LIDAR technology and commercial-grade 3D printing, are available for free download, enabling other researchers and enthusiasts to replicate the model. This approach enhances plant phenotyping by providing precise reference material for sensor-driven technologies, improving the accuracy of measurements related to plant growth parameters.
The study, led by Jonas Bömer from the Institute of Sugar Beet Research and the University of Bonn, demonstrates the potential of combining AI, 3D printing, and sensor technology to enhance plant breeding. The model’s affordability and accessibility make it a valuable tool for both advanced research and resource-limited settings, potentially benefiting the breeding of other crops in the future.
Recent research published in GigaScience explores the integration of laser scanning and 3D printing to advance crop breeding. The study presents a detailed 3D model of a sugar beet plant, capturing key characteristics of its above-ground parts, which is designed for use in AI-assisted crop improvement. Created using LIDAR and commercial-grade 3D printing, the model is available for free download, facilitating reproducibility and enhancing plant phenotyping. Led by Jonas Bömer from the Institute of Sugar Beet Research and the University of Bonn, the study showcases the potential of combining AI, 3D printing, and sensor technology to improve plant breeding, offering benefits for both advanced and resource-limited research settings.
