Edible Oil Authentication via Calibrated MALDI-MS Spectral Library
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Solution Overview
Problem
Current methods for authenticating edible oils, such as GC-FID and PCA analysis of MALDI-MS spectra, are time-consuming, labor-intensive, and require skilled operators, limiting scalability and accuracy in differentiating similar oil species.
Innovation Solution
A method using calibrated MALDI-MS data comparison with a spectral library through cosine similarity testing, data binning, and normalization, enabling automated identification of edible oils without the need for extensive manual processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GC-FID method is used to authenticate edible oils, then measurement precision is improved, but loss of time increases and productivity decreases
Solution Approach 1:
The patent extracts only the essential spectral features (peak positions, intensities, and patterns) from the complete MALDI-MS spectrum, comparing these extracted features against a library of reference oil spectra. This extraction approach maintains authentication accuracy while dramatically reducing analysis time by avoiding the lengthy hydrolysis and chromatographic separation steps required by GC-FID.
Solution Approach 2:
The patent creates a spectral library containing copies of reference oil spectra that can be rapidly compared against sample spectra using correlation algorithms. This copying approach enables quick authentication by matching spectral patterns without requiring the time-consuming chemical processing steps of traditional methods.
2Measurement precision
If PCA analysis is used to process MALDI-MS spectra, then measurement precision is improved, but device complexity increases and ease of operation deteriorates
Solution Approach 1:
The patent implements an automated spectral matching system that performs self-service authentication by automatically comparing sample spectra against the reference library using correlation algorithms. The system independently identifies oil types without requiring operators to manually select peaks or interpret complex PCA plots, thereby maintaining precision while greatly simplifying operation.
Solution Approach 2:
The patent replaces the manual mechanical process of peak selection and PCA interpretation with an automated computational system that uses correlation algorithms to compare spectra. This substitution eliminates the need for operator expertise in complex statistical analysis while maintaining or improving measurement precision.
3Measurement precision
If manual peak selection and PCA analysis are used, then measurement precision is improved, but productivity decreases
Solution Approach 1:
The patent enables continuous authentication by implementing an automated workflow where spectra are continuously acquired and immediately compared against the reference library without interruption for manual analysis. This continuous operation dramatically increases productivity while maintaining precision through consistent algorithmic comparison.
Solution Approach 2:
The patent uses a pre-built spectral library containing copies of reference oil spectra, allowing rapid parallel comparison of multiple samples against the same reference set. This copying approach enables high-throughput authentication without requiring repeated manual analysis for each sample.
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 allows for rapid, reliable, and scalable authentication of edible oils, reducing reliance on skilled operators and improving differentiation between similar oil species, enhancing the efficiency and accuracy of oil identification.
Implementation Method 1
matrix-assisted laser desorption/ionisation mass spectrometry (MALDI-MS)
Data Source
AI summary
The present disclosure provides a method and system for analysing one or more edible oil samples. In an embodiment the disclosure provides for calibrating the matrix-assisted laser desorption/ionisation mass spectrometry (MALDI-MS) data obtained for one or more edible oil samples to obtain calibrated spectral data; and comparing the calibrated spectral data derived from the one or more samples against a library of calibrated MALDI-MS spectra for a plurality of edible oil samples to determine the most likely composition of the one or more edible oil samples.