Early Warning Method for Aflatoxin Contamination Using LC-HRMS
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Solution Overview
Problem
Current methods lack an effective early warning system for aflatoxin contamination, which poses significant economic and health risks due to the inability to detect toxigenic Aspergillus flavus strains before contamination occurs.
Innovation Solution
An early warning method involving the detection and analysis of specific warning molecules like versiconol, versicolorin B, 5-methoxysterigmatocystin, and other bio-markers using liquid chromatography-high resolution mass spectrometry and machine learning algorithms to predict aflatoxin contamination risk.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional aflatoxin detection methods are used, then aflatoxin contamination can be detected, but early warning before contamination is not possible
Solution Approach 1:
The patent applies preliminary action by detecting warning molecules (versiconol, versicolorin B, 5-MST) that are produced during early fungal growth stages before aflatoxin contamination occurs. This allows the system to warn of potential contamination in advance, enabling preventive measures to be taken before the actual toxin production stage
Solution Approach 2:
The patent segments the aflatoxin contamination process into distinct stages by identifying specific biomarkers for each phase: warning molecules for early colonization, and aflatoxin itself for later contamination stages. This segmentation allows detection at multiple points in the contamination timeline, particularly enabling early warning before full contamination occurs
2Reliability
If toxigenic Aspergillus flavus strains are identified early, then aflatoxin contamination risk can be predicted, but complex detection and analysis procedures are required
Solution Approach 1:
The patent uses warning molecules (versiconol, versicolorin B, 5-MST) as intermediary biomarkers that indicate the presence and toxigenic potential of Aspergillus flavus strains. These intermediaries serve as early indicators that are easier to detect and quantify than direct toxigenicity assessment, simplifying the detection process while maintaining reliability
Solution Approach 2:
The patent replaces complex mechanical/cultural methods for identifying toxigenic strains (such as animal bioassays or extensive culture procedures) with analytical chemistry methods (LC-MS/MS) that directly quantify warning molecule biomarkers. This substitution significantly reduces device complexity and procedural complexity while improving detection speed and reliability
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
This approach enables accurate identification of toxigenic Aspergillus flavus strains and predicts aflatoxin contamination risk, providing a sensitive and effective early warning system for ensuring food safety.
Implementation Method 1
subjecting the sample extract to detection and analysis by liquid chromatography-high resolution mass spectrometer
Implementation Method 2
collecting mass spectrometry information, and performing qualitative analysis based on the mass spectrometry information
Data Source
AI summary
The present invention relates to an early warning method before the occurrence of aflatoxin contamination. The steps are as follows: extracting toxins from the sample to obtain a sample extract, and subjecting the sample extract to detection and analysis by liquid chromatography-high resolution mass spectrometer, performing qualitative analysis based on the mass spectrometry information to obtain qualitative results, performing quantitative analysis based on a standard curve of the chromatographic peak area of each warning molecule/the peak area of the internal standard-warning molecule concentration to obtain quantitative results of these warning molecules, wherein a risk of aflatoxin contamination of the sample is assessed to obtain a classification prediction model, inputting the quantitative results of the warning molecules for a toxigenic strain of Aspergillus flavus, and outputting a risk assessment result based on the classification prediction model, thereby achieving the early warning before aflatoxin contamination occurs.