A new study shows how 3D printing and AI-assisted pipes have changed how sugar beets are grown. This is just one example of how technology is changing agriculture.
In this cutting-edge study, laser scans, 3D printing, and artificial intelligence are combined to make detailed models of crop growth.
Different Ways to Look at Plant Phenotypes
Plant phenotyping, or collecting reliable plant data, is vital for modern plant breeding. Measurements had to be done manually, which was time-consuming.
In contrast, imaging technology and machine learning advances have automated much of this process, allowing for more accurate and comprehensive data collection. The updated paper in the journal GigaScience presents the 3D model of the sugar beet plant together with its validation.
Researchers used Light Detection and Ranging (LIDAR) to examine a live sugar beet plant from twelve different points of view. After the data was processed, it was put into a commercial-grade 3D printer, which made a life-size and very detailed copy of the plant. These models demonstrate fundamental qualities and are intended to serve as guidelines for AI systems in breeding efforts.
Dr. Jonas Bömer and his team led this new idea from the Institute of Sugar Beet Research and the University of Bonn. They stressed the importance of accurate 3D models for sensor-driven crop breeding and said these models help standardize measures and make AI systems' data more accurate.
Possible Uses and Huge Potential
The effects of this study go far beyond growing sugar beets. Since the 3D printing files are free, other scientists can make copies of these models. This makes it easier to compare study results from different labs and areas. It also makes it easier for people in developing countries, which may not have as many resources, to do advanced studies.
The researchers used LIDAR and 3D printing to make a very detailed and steady model that changes very little over time. Because the models are so stable, they can be used repeatedly in greenhouse and field tests. These models help test and compare 3D sensor systems, ensure that parameter extraction algorithms work correctly, and monitor how these algorithms work in real-world situations.
In his talk, Dr. Bömer said that using additive manufacturing technologies to make reference models that can be used repeatedly opens up a new way to create standardized methods for objective and accurate referencing, which is suitable for both scientific research and practical plant breeding.
The study suggests that merging modern sensor technology, 3D printing, and AI could benefit crop breeding. By increasing crop yields and quality, this integrated approach has the potential to make breeding programs significantly more efficient and successful, thereby contributing to global food security.
Combining 3D printing with AI-assisted procedures and crop breeding advances provides farmers with new instruments for more accurate farming. Researchers are enabling more precise and effective plant phenotyping by creating repeatably applicable realistic models of sugar beet plants. This technology is suitable for breeding sugar beets but could also change how other crops are bred, like rice and African orphan crops.
As Chris Armit, a data scientist, pointed out, the value of a printable 3D model lies in its ability to print many copies, one for each field of crops. He said it was a low-cost phenotyping method because the LIDAR camera was the primary cost. He was excited to see this method used on other crops.
This research is a big step forward in agriculture because it shows how current technology can improve old methods and make crop production more sustainable.
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