Invention Reference Number
Plant transformation is a critical but labor-intensive step in validating gene function, creating a major mismatch between gene discovery and experimental validation. This technology addresses that bottleneck by automating key steps in plant transformation using an integrated system that combines sensing, robotic handling, and digital control. The method significantly increases throughput and reliability while reducing reliance on manual labor and operator variability. By enabling rapid, repeatable handling of plant samples, the technology supports faster evaluation of genetic modifications and effect of other treatment variations on plant traits across a wide range of research and applied settings.
Description
This invention describes an automated approach for transforming plants through a coordinated system that replaces traditionally manual operations with machine-assisted processes. The method integrates computer vision, automated manipulation, and centralized control to identify plant features, obtain samples, and manage handling and transfers between growth and processing environments.
Using image-based analysis, the system locates candidate plant regions and guides automated handling tools to perform precise sample interactions without human intervention. Samples are then transferred through a sequence of controlled environments using automated timing and positioning, enabling consistent processing at scale. Throughout the workflow, data associated with plant characteristics and handling steps can be captured and stored digitally.
The approach is adaptable to different plant types, sizes, and experimental protocols, and is designed to integrate with upstream and downstream laboratory systems. By automating a traditionally slow, inconsistent and labor-intensive workflow, the technology enables higher consistency, reliability and throughput in experimentation and enables high quality data in support of trustworthy AI for accelerating plant sciences.
Benefits
- Enables consistent, repeatable sample handling
- Increases plant transformation throughput
- Reduces labor intensity and operator-dependent variability
- Supports data capture across workflows for AI integration as well as AI model development
Applications and Industries
- Plant biology and functional genomics research
- Agricultural biotechnology and crop development
- Laboratory automation and robotics platforms
- Controlled-environment plant testing and analysis
Contact
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.
