Microorganism Identification via Coherent Light Diffraction
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Solution Overview
Problem
Current methods for rapid, efficient, and accurate identification of microorganisms using diffraction analysis are limited by their destructive nature, lack of contactlessness, and inefficiency in targeting individual microbial colonies.
Innovation Solution
A method and system that utilize coherent light to acquire and analyze diffraction patterns of microbial colonies on a plate, allowing for non-destructive, contactless, and efficient identification by comparing monitored diffraction patterns with reference patterns, using automated mechanisms to precisely target and analyze individual colonies based on their optical properties and morphologies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional diffraction analysis methods are used to identify microorganisms, then identification can be performed, but the process is destructive and requires direct contact with the colonies
Solution Approach 1:
The system segments the identification process into two distinct phases: first, non-contact optical imaging to locate and characterize colonies, and second, targeted diffraction analysis only on selected colonies. This segmentation allows the majority of colonies to be screened without destructive contact, resolving the contradiction between reliable identification and harmful contact effects.
Solution Approach 2:
The patent introduces an optical imaging system as an intermediary between the user and the microbial colonies. This intermediary enables initial colony characterization and selection without direct contact or destruction of the colonies, allowing the destructive diffraction analysis to be applied selectively rather than universally, thus reducing overall harmful effects while maintaining identification reliability.
2Measurement precision
If manual diffraction analysis of each colony is performed, then accurate identification is achieved, but the process is time-consuming and inefficient
Solution Approach 1:
The system performs preliminary optical imaging and automated colony detection before conducting diffraction analysis. By pre-identifying and locating colonies through non-destructive imaging, the system prepares the sample set in advance, allowing rapid sequential diffraction measurements without time-consuming manual colony location, thus resolving the contradiction between precision and productivity.
Solution Approach 2:
The patent replaces manual mechanical operations (handheld diffraction devices, manual colony selection) with an automated optical system that uses cameras, computer vision algorithms, and robotic positioning. This substitution eliminates manual labor bottlenecks while maintaining measurement precision, enabling high-speed automated colony identification that resolves the speed-accuracy tradeoff.
3Productivity
If automated targeting of colonies is implemented, then testing efficiency improves, but system complexity increases
Solution Approach 1:
The patent employs a multi-functional optical system where a single imaging platform performs multiple tasks: colony detection, positioning, characterization, and targeting for diffraction analysis. This universal system consolidates what would otherwise require separate devices, achieving high productivity without proportionally increasing overall system complexity.
Solution Approach 2:
The automated system uses self-service algorithms that automatically detect, locate, and characterize colonies without human intervention. The computer vision software autonomously processes images, identifies colony positions, and guides the diffraction analysis, eliminating the need for complex manual control interfaces while maintaining high testing efficiency.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables rapid, accurate, and repeatable identification of microorganisms by generating comparison parameters that match monitored diffraction patterns with reference patterns, improving the speed and reliability of microbial identification while minimizing variations in culturing conditions.
Implementation Method 1
monitoring a diffraction pattern resulting from the diffraction of the light by the target colony
Data Source
Figure 1
Figure 2
Figure 3A~3B
AI summary
A method of identifying microorganisms is provided. The method comprises: acquiring data representing a region on a plate within which at least one colony of microorganisms is disposed;exposing a target colony of the at least one colony of microorganisms to a beam of coherent light, in accordance with the data;monitoring a diffraction pattern resulting from the diffraction of the light by the target colony; and generating target colony data in accordance with the monitored diffraction pattern and a reference diffraction pattern.