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Rapid discrimination and determination of polyunsaturated fatty acid composition in marine oils by FTIR Spectroscopy and Multivariate Data Analysis
Version 2 2024-06-03, 12:59Version 2 2024-06-03, 12:59
Version 1 2014-11-25, 15:06Version 1 2014-11-25, 15:06
journal contribution
posted on 2024-06-03, 12:59 authored by J Vongsvivut, MR Miller, D McNaughton, P Heraud, Colin BarrowColin BarrowA rapid analytical approach for discrimination and quantitative determination of polyunsaturated fatty acid (PUFA) contents, particularly eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), in a range of oils extracted from marine resources has been developed by using attenuated total reflection Fourier transform infrared spectroscopy and multivariate data analysis. The spectral data were collected without any sample preparation; thus, no chemical preparation was involved, but data were rather processed directly using the developed spectral analysis platform, making it fast, very cost effective, and suitable for routine use in various biotechnological and food research and related industries. Unsupervised pattern recognition techniques, including principal component analysis and unsupervised hierarchical cluster analysis, discriminated the marine oils into groups by correlating similarities and differences in their fatty acid (FA) compositions that corresponded well to the FA profiles obtained from traditional lipid analysis based on gas chromatography (GC). Furthermore, quantitative determination of unsaturated fatty acids, PUFAs, EPA and DHA, by partial least square regression analysis through which calibration models were optimized specifically for each targeted FA, was performed in both known marine oils and totally independent unknown n - 3 oil samples obtained from an actual commercial product in order to provide prospective testing of the developed models towards actual applications. The resultant predicted FAs were achieved at a good accuracy compared to their reference GC values as evidenced through (1) low root mean square error of prediction, (2) good coefficient of determination close to 1 (i.e., R 2≥ 0.96), and (3) the residual predictive deviation values that indicated the predictive power at good and higher levels for all the target FAs. © 2014 Springer Science+Business Media New York.
History
Journal
Food and Bioprocess TechnologyVolume
7Pagination
2410-2422Location
New York, United StatesPublisher DOI
ISSN
1935-5130eISSN
1935-5149Language
engPublication classification
C Journal article, C1 Refereed article in a scholarly journalCopyright notice
2014, Springer New York LLCIssue
8Publisher
Springer New York LLCUsage metrics
Keywords
FTIR spectroscopyMarine oilsMultivariate data analysisPolyunsaturated fatty acids (PUFAs)Science & TechnologyLife Sciences & BiomedicineFood Science & TechnologyMULTIPLICATIVE SIGNAL CORRECTIONHOKI MACRURONUS-NOVAEZELANDIAEPARTIAL LEAST-SQUARESINFRARED-SPECTROSCOPYFISH-OILNEW-ZEALANDLIVER OILDIETOMEGA-3-FATTY-ACIDSOPTIMIZATION030606 Structural Chemistry and Spectroscopy970110 Expanding Knowledge in TechnologyCentre for Chemistry and BiotechnologySchool of Life and Environmental Sciences
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