Spectral Pathogen Detection in Food Processing Byproducts

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Solution Overview

Problem

Current methods for detecting foodborne pathogens in food processing facilities are time-consuming and often fail to identify contamination until after significant illness and economic losses occur, as they require extensive investigation and testing that can take up to 48 hours to 72 hours for results.

Innovation Solution

A system utilizing light intensity measuring apparatuses, such as spectrometers, to scan food processing byproducts and apply machine learning and AI models to detect pathogens, providing early detection and reducing the Limit of Detection (LOD) by one to two orders of magnitude compared to classical methods.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Speed

If classical pathogen detection methods are used, then detection accuracy is maintained, but detection time increases significantly (48-72 hours)

Engineering Contradiction:

Improvedetection speedVSAvoidtime to detect contamination

Core Design Contradiction:

SpeedVSLoss of time

Solution Approach 1:

The system performs preliminary spectral scanning of food processing byproducts in real-time during production, rather than waiting for completed products. This allows contamination to be detected at the source before it propagates through the supply chain, eliminating the need for lengthy post-production testing while maintaining detection accuracy

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent replaces traditional mechanical/cultural methods of pathogen detection (incubation, plating, microscopic examination) with optical spectroscopy combined with machine learning. The spectrometer captures spectral signatures of pathogens in byproducts, and AI algorithms analyze these signatures to identify contamination within seconds, achieving both speed and accuracy

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If extensive investigation and testing are performed to ensure accurate detection, then detection reliability improves, but productivity decreases due to time losses

Engineering Contradiction:

Improvepathogen detection reliabilityVSAvoidfood processing throughput

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system implements continuous real-time monitoring of food processing byproducts throughout the production process. The spectrometer continuously scans byproducts as they move through processing, providing uninterrupted detection coverage without interrupting production flow, thereby maintaining both reliability and productivity

Inventive Principle:

Principle #20Continuity of useful action

Solution Approach 2:

The system uses food processing byproducts (waste streams) as an intermediary indicator of contamination. Instead of testing finished products or raw materials directly, the system analyzes byproducts which contain spectral signatures of any pathogen contamination present in the processing stream. This intermediary approach provides reliable detection while requiring minimal disruption to production

Inventive Principle:

Principle #24Intermediary (Mediator)

3Measurement precision

If traditional detection methods are used, then false positives are minimized, but the Limit of Detection (LOD) increases by one to two orders of magnitude

Engineering Contradiction:

ImproveLimit of DetectionVSAvoidearly contamination signals

Core Design Contradiction:

Measurement precisionVSLoss of information

Solution Approach 1:

The system changes the measurement parameters from traditional cultural methods to optical spectral analysis across multiple wavelengths. This allows detection of pathogen-specific spectral signatures at much lower concentrations, improving the Limit of Detection by one to two orders of magnitude while using machine learning to distinguish true signals from noise and prevent false positives

Inventive Principle:

Principle #35Parameter changes

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 detection of foodborne pathogens, allowing for immediate remedial actions, reducing economic losses, and preventing illnesses, hospitalizations, and deaths by identifying contamination before products are shipped, and aiding compliance with food safety regulations.

Implementation Method 1

an apparatus configured to generate light, detect the light that has passed through at least a portion of a sample of a food processing byproduct, and measure intensities of the light to obtain the set of intensity measurements for the set of wavelengths of light

Methodology Applied

Scientific EffectAbsorption Spectroscopy: Absorption Spectroscopy

Data Source

PatentUS20240019378A1Systems and methods for detecting foodborne pathogens by analyzing spectral data

Publication Date: 2024.01.18 HYPER-SPECTRAL LLC

AI summary

An example method includes receiving a first set of values based on a set of intensity measurements. The set of intensity measurements may be obtained by a light intensity measuring apparatus that measured intensities of light that passed through a sample of a food processing byproduct. A second set of values based on the first set of values may be generated. A set of trained decision trees may be applied to the second set of values to obtain a result. Based on the result, either a positive foodborne pathogen detection or a negative foodborne pathogen detection for a foodborne pathogen in the sample of the food processing byproduct may be determined. A foodborne pathogen detection notification that indicates either the positive foodborne pathogen detection or the negative foodborne pathogen detection for the foodborne pathogen in the sample of the food processing byproduct may be generated and provided.