Light-Intensity Spectral Detection for Foodborne Pathogens
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Solution Overview
Problem
Current methods for detecting foodborne pathogens in food processing are slow and inefficient, leading to significant delays in identifying contaminated food, which can cause widespread illness and economic losses.
Innovation Solution
A system utilizing a light intensity measuring apparatus coupled with a computing system that applies machine learning and spectral analysis to detect foodborne pathogens in real-time, enabling early detection and prevention of contamination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional pathogen detection methods are used, then detection accuracy can be maintained, but detection speed is slow and time-consuming
Solution Approach 1:
The patent replaces traditional mechanical/cultural detection methods with optical detection using a spectrometer. The system shines light through water samples and analyzes spectral absorption patterns to identify pathogen presence, eliminating the need for time-consuming bacterial culture growth and manual examination, thereby achieving rapid detection within minutes
Solution Approach 2:
The system transforms the detection approach by measuring optical parameters (light absorption spectra) rather than relying on biological growth parameters. By analyzing how pathogens absorb specific wavelengths of light, the system converts a time-dependent biological process into an instantaneous optical measurement, resolving the speed-time contradiction
2Measurement precision
If traditional detection methods are used, then equipment complexity is low, but detection precision and multi-pathogen identification capability are insufficient
Solution Approach 1:
The spectrometer serves multiple functions: it detects various types of pathogens (bacteria, viruses, parasites), identifies contamination in water samples, and provides spectral analysis for characterization. This multi-functional device replaces multiple specialized detection systems, achieving high measurement precision while managing complexity through consolidation
Solution Approach 2:
The system introduces light as an intermediary between the sample and detection. The spectrometer uses light absorption as a mediator to indirectly detect pathogen presence without direct interaction with the pathogens, enabling precise non-contact measurement that simplifies the detection process while maintaining high accuracy
3Productivity
If rapid detection is implemented, then response time is reduced, but measurement precision may be compromised
Solution Approach 1:
The system performs preliminary spectral scanning of water samples in real-time during food processing operations. By continuously monitoring and establishing baseline spectral patterns, the system prepares detection data in advance, allowing rapid identification of deviations that indicate pathogen presence without compromising accuracy
Solution Approach 2:
The system implements feedback through continuous spectral analysis and comparison against known pathogen signatures. The spectrometer provides real-time feedback on water sample quality, allowing immediate detection and response while maintaining precision through iterative verification of spectral patterns against reference databases
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 and accurate identification of multiple foodborne pathogens, reducing the risk of illness outbreaks and economic losses by allowing for immediate quarantine and remedial actions.
Implementation Method 1
a detector configured to detect the light that has passed through at least a portion of the water sample in the chamber and measure multiple times intensities of wavelengths of the light to obtain multiple sets of measured intensities of wavelengths
Data Source
AI summary
An example system includes a light intensity measuring apparatus couplable to a food processing apparatus and a computing system. The light intensity measuring apparatus includes a chamber configured to receive a water sample from the food processing apparatus, a light source, a detector configured to detect light that has passed through the water sample and measure multiple times intensities of wavelengths of the light to obtain multiple sets of measured intensities of wavelengths, and a communication module configured to provide the multiple sets of measured intensities of wavelengths. The computing system may receive the multiple sets of measured intensities, process the multiple sets to obtain a set of values, apply a first set of decision trees to the set of values to obtain a first result indicating a positive or negative foodborne pathogen detection, generate a notification indicating either the positive of negative detection, and provide the notification.