Automated Plant Tissue Excision via Machine Vision Guidance
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Solution Overview
Problem
Current plant transformation methods are bottlenecked by the mismatch between gene sequencing throughput and gene function validation, relying heavily on manual labor and low throughput, which limits productivity.
Innovation Solution
An automated system utilizing machine vision and robotic manipulation for precise excision and transportation of plant tissue samples, enabling high-throughput plant transformation through image processing and automated handling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual plant transformation methods are used, then precision in plant handling can be maintained through human skill, but throughput remains low due to reliance on manual labor for each step
Solution Approach 1:
The patent replaces manual mechanical operations with an automated robotic system that uses machine vision guidance. A robotic arm with customizable end effectors performs plant handling, excision, and transfer operations that were previously done manually, thereby increasing throughput while maintaining precision through automated control and visual feedback.
Solution Approach 2:
The system incorporates machine vision that automatically detects and tracks plant tissues, enabling the robotic system to self-navigate and perform operations without human intervention. The vision system provides real-time feedback that allows the automated system to adapt to variations in plant morphology and positioning.
2Loss of time
If manual handling of plant samples is used, then flexibility in handling different plant types can be maintained, but time consumption increases due to manual operations for excision, transfer, and labeling
Solution Approach 1:
The patent replaces manual mechanical operations with an automated robotic system that uses machine vision guidance. A robotic arm with customizable end effectors performs plant handling, excision, and transfer operations that were previously done manually, thereby increasing throughput while maintaining precision through automated control and visual feedback.
Solution Approach 2:
The robotic system is designed with universal end effectors that can be configured to handle different plant types and perform various operations such as excision, transfer, and labeling. This multi-functionality allows the same automated system to maintain flexibility across different plant species and experimental protocols.
3Productivity
If automated robotic manipulation is implemented, then throughput of plant transformation is significantly increased, but initial system complexity and cost increase
Solution Approach 1:
The automated system is divided into modular functional components: machine vision subsystem, robotic manipulation subsystem with interchangeable end effectors, and control software. This segmentation allows the system to be implemented incrementally and adapted to different laboratory configurations, reducing the barrier to entry despite the overall complexity.
Data Source
AI summary
A method and a system for automated plant surveillance and manipulation are provided. Pursuant to the method and the system, images of target plants are obtained through a machine vision system having multiple cameras. The obtained images of the target plants are processed to determine tissue candidates of the target plants and to determine a position and an orientation of each tissue candidate. A tool is manipulated, based on the position and the orientation of each tissue candidate, to excise each tissue candidate to obtain tissue samples. The tissue samples are transported for subsequently manipulation including live processing of the tissue samples or destructive processing of the tissue samples.