Detection of Edible Plant Oil Adulteration by Triacylglycerol Profiles Using an Atmospheric Pressure Chemical Ionization Source and MS 3 Ion Trap Mass Spectrometry

Detection of lard adulteration in 3 kinds of vegetable oils by liquid chromatography-mass spectrometry with porous graphite carbon column

Liquid chromatography‒mass spectrometry employing porous graphite carbon columns and an n-octane-isopropanol mobile phase was utilized for the separation of triacylglycerols (TAGs) in various edible oils, aiming to identify lard adulteration in soybean, corn, and sunflower seed oils. Experiments were conducted using a Hypercarb column (2.1 mm × 100 mm, 5 µm) and an n-octane-isopropanol (70:30, V/V) mobile phase at a flow rate of 0.25 mL· min-1 and a column temperature of 60 °C. Detection was achieved through atmospheric pressure chemical ionization-mass spectrometry. Analysis of diverse edible oil samples revealed that oils of the same type shared similar TAG compositions, while different types exhibited distinct TAG profiles. Distinct variations in triglyceride composition were observed across different edible oils. Based on liquid chromatography‒mass spectrometry analysis, the characteristic component 1-stearic acid-2-palmitic acid-3-oleic acid glyceride (SPO), which may also include PSO, was identified in lard through principal component analysis and orthogonal partial least squares discriminant analysis. This component served as a marker for detecting as low as 0.1% lard adulteration in soybean, corn, and sunflower seed oils. The technique offers a precise and effective approach for the identification of lard adulteration in these edible oils.

Establishment and evaluation of multiple adulteration detection of camellia oil by mixture design

Multiple adulteration is a common trick to mask adulteration detection methods. In this study, the representative multiple adulterated camellia oils were prepared according to the mixture design. Then, these representative oils were employed to build two-class classification models and validate one-class classification model combined with fatty acid profiles. The cross-validation results indicated that the recursive SVM model possessed higher classification accuracy (97.9%) than PLS-DA. In OCPLS model, the optimal percentage of RO, SO, CO and SUO was 2.8%, 0%, 7.2%, 0% respectively in adulterated camellia oil, which is the most similar to the authentic camellia oils. Further validation showed that five adulterated oils with the optimal percentage could be correctly identified, indicating that the OCPLS model could identify multiple adulterated oils with these four cheaper oils. Moreover, this study serves as a reference for one class classification model evaluation and a solution for multiple adulteration detection of other foods.

Discrimination between vegetable oil and animal fat by a metabolomics approach using gas chromatography-mass spectrometry combined with chemometrics

Adulteration of olive oil with the other cheap oils and fats plays an important role in economics and has nutritional benefits. In this work, metabolite profiling was performed using gas chromatography-mass spectrometry to identify and quantify animal fat (lard) adulteration in vegetable oil (olive oil). Principal component analysis could correctly identify and clustering olive oil, sunflower oil, sesame oil, lard, and adulterated samples through the changes in their fatty acid methyl esters (FAMEs) profile. A targeted metabolomics method was then optimized and validated through construction of calibration curves of known FAMSs in olive oil and lard. The method was presented high linearity (R2 > 0.96) and good intra and inter day accuracy and precision (79-101 and 86-102% and 2-7 and 3-7, respectively) for determination of FAMEs. Afterwards the absolute concentration and relative percentage of FAMEs were successfully determined in 12 commercial olive oils and 3 lards samples. Methyl myristate, methyl palmitate, methyl oleate, and methyl stearate were selected as discriminant markers to identify and quantify lard adulteration even at a low level of lard (5%w/w), with errors less than 2% in the comparison of the absolute or relative concentrations of FAMEs using several statistical methods. The proposed methodology allowed us to quantify the FAMEs simultaneously and also could predict small amount of lard in the adulterated olive oil samples.