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Improving crops with laser beams and 3D printing
Context:
A recent study published in the journal GigaScience shows how laser scanning and 3D printing create a detailed 3D model of a sugar beet plant.
More on News:
A team from the Institute for Sugar Beet Research in Göttingen and the University of Bonn used LiDAR (Light Detection and Ranging) technology to scan a real sugar beet plant( reproducible and suitable for field use) from twelve different angles.
Key Highlights:
- Crop breeding has moved beyond simply using genetic information to latest advances using machine learning algorithms and advanced imaging technology.
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- It captures the essential characteristics of plants.
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- It involves laser scanning (LiDAR) and 3D printing to create accurate, reproducible models of sugar beet plants and aids in AI-assisted crop improvement.
- The data resulted in a real-sized, highly detailed model of the sugar beet.
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- These 3D models serve as accurate references essential for sensor-driven phenotyping.
- “Plant phenotyping,” the science of precisely measuring plants, has greatly improved in recent years.
- Automation in Plant Phenotyping: Traditionally, phenotyping required labour-intensive manual measurements. Now, this process is becoming automated using state-of-the-art sensor technology.
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- They use advanced sensors and AI to gather data on plant size, fruit quality, leaf size, and other growth parameters.
- It not only speeds up the process but also captures complex data at a scale unattainable by human effort alone.
Significance:
- Freely Available Resources: All research data, methodology, and 3D printing files are freely available for download, allowing anyone to print their 3D sugar beet plant.
- Global Accessibility: The affordability of 3D printing and the availability of free files make this approach adaptable in resource-poor settings, including developing countries.
- Broader Applications: The methodology can be applied to other crops, potentially aiding low-cost phenotyping strategies for crops like rice and African orphans.