Edible oil analysis system and method

Abstract

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.

1 . A method for analysing one or more edible oil samples, the method comprising:
 receiving, by a processor, matrix-assisted laser desorption/ionisation mass spectrometry (MALDI-MS) data for one or more edible oil samples, calibrating, by the processor, the MALDI-MS data for the one or more edible oil samples to obtain calibrated MALDI-MS data by using reference peaks selected from triacylglycerol (TAG) peak(s) and 2,5-dihydroxybenzoic acid (DHB) matrix peak(s) of the MALDI-MS data of the one or more edible oil samples;   comparing, by the processor, the calibrated MALDI-MS data derived from the one or more samples against a library comprising calibrated MALDI-MS data for a plurality of edible oil samples, wherein the library of calibrated MALDI-MS data is obtained by calibrating reference peaks selected from triacylglycerol (TAG) peak(s) and 2,5-dihydroxybenzoic acid (DHB) matrix peak(s) of the MALDI-MS data for the plurality of edible oil samples, wherein such comparison does not include principal component analysis (PCA) analysis; and   determining a most likely composition of the one or more edible oil samples.   
     
     
         2 . The method for analysing one or more edible oil samples according to  claim 1 , wherein the comparison between the calibrated MALDI-MS data derived from the one or more samples and the library of calibrated MALDI-MS data for the plurality of edible oil samples is performed using a Cosine similarity test. 
     
     
         3 . The method for analysing one or more edible oil samples according to  claim 1 , wherein the most likely composition of the one or more edible oil samples is determined after ranking, based on the calibrated MALDI-MS data, a plurality of calibrated MALDI-MS data of known edible oil types in the library according to their likelihood of being in the one or more edible oil samples, from most likely to least likely using cosine similarity test scores; and
 determining the most likely identification of the one or more edible oil samples based upon the highest ranked cosine similarity score.   
     
     
         4 . The method for analysing one or more edible oil samples according to  claim 2 , wherein the cosine similarity test is conducted on one or more regions of the calibrated MALDI-MS data derived from the one or more samples selected from the group comprising high mass, low mass and TAG regions and one or more corresponding regions of the edible oil samples in the library of calibrated MALDI-MS data. 
     
     
         5 . The method for analysing one or more edible oil samples according to  claim 1 , wherein following calibration and before comparison with the library of calibrated MALDI-MS data, the calibrated MALDI-MS data derived from the one or more samples is quantised by data binning. 
     
     
         6 . The method for analysing one or more edible oil samples according to  claim 6 , wherein the data binning is performed by dividing an entire spectra into intervals of 0.5 m/z, averaging intensity of all readings within each bin, and setting an m/z reading as a m/z value at the middle of the interval. 
     
     
         7 . The method for analysing one or more edible oil samples according to  claim 6 , wherein following binning, the calibrated MALDI-MS data derived from the one or more samples is normalised by dividing an intensity of each bin with either a maximum intensity or a total intensity of all bins, multiplying by an appropriate scaling parameter and rounding to a nearest integer. 
     
     
         8 . The method for analysing one or more edible oil samples according to  claim 1 , wherein the comparison between the calibrated MALDI-MS data derived from the one or more samples and the library of calibrated MALDI-MS data for the plurality of edible oil samples is performed using a statistical test selected from the group consisting of characteristic peak matching methods, partial least squares discriminant analysis (PLS-DA), and decision tree-based methods.