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Rapid classification and quantification of marine oil omega-3 supplements using ATR-FTIR, FT-NIR and chemometrics

•Novel method was developed for classifying marine oils based on their lipid matrices.•Mid-infrared was more sensitive than near-infrared for the classification of oils.•Ethyl esters in triacylglycerols were correctly classified as mixtures at 11% (w/w).•Six quantitative models were developed for ma...

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Bibliographic Details
Published in:Journal of food composition and analysis 2019-04, Vol.77, p.9-19
Main Authors: Karunathilaka, Sanjeewa R., Choi, Sung Hwan, Mossoba, Magdi M., Yakes, Betsy Jean, Brückner, Lea, Ellsworth, Zachary, Srigley, Cynthia T.
Format: Article
Language:English
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Summary:•Novel method was developed for classifying marine oils based on their lipid matrices.•Mid-infrared was more sensitive than near-infrared for the classification of oils.•Ethyl esters in triacylglycerols were correctly classified as mixtures at 11% (w/w).•Six quantitative models were developed for major fatty acids/fatty acid classes.•Procedures show promise for verifying accuracy of marine oil label declarations. The increased demand for marine oil dietary supplements requires rapid and accurate screening to verify product quality and accuracy of label declarations. Simple and rapid procedures, based on spectra from a portable Fourier-transform infrared (FTIR) device and a benchtop FT-near infrared (FT-NIR) spectrometer combined with chemometrics, were developed to: (1) differentiate sources of omega-3 polyunsaturated fatty acids (PUFA) in their natural triacylglycerol (TAG) or concentrated ethyl ester (EE) forms, and (2) quantify six main fatty acids (FA)/FA classes. A partial least squares discriminant analysis (PLS-DA) model developed for ATR-FTIR data was successfully used to classify a large number of representative products (n = 95) as belonging to the TAG or EE classes, or as mixtures of such. Broad-based partial least squares regression (PLSR) models for each of six fatty acid (FA)/FA classes were successfully validated by cross-validation and by using an independent validation test set. For both complementary procedures, PLSR model predictions showed good linear correlations with a reference gas chromatographic method (R2 > 0.91) and excellent predictive qualities for eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). These simple, rapid, and nondestructive spectroscopic procedures have the potential for differentiating between natural and concentrated forms of omega-3 PUFA and verifying the accuracy of label declarations.
ISSN:0889-1575
1096-0481
DOI:10.1016/j.jfca.2018.12.009