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Rapid discrimination and determination of polyunsaturated fatty acid composition in marine oils by FTIR Spectroscopy and Multivariate Data Analysis

Vongsvivut,J, Miller,MR, McNaughton,D, Heraud,P and Barrow,CJ 2014, Rapid discrimination and determination of polyunsaturated fatty acid composition in marine oils by FTIR Spectroscopy and Multivariate Data Analysis, Food and Bioprocess Technology, vol. 7, no. 8, pp. 2410-2422, doi: 10.1007/s11947-013-1251-0.

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Title Rapid discrimination and determination of polyunsaturated fatty acid composition in marine oils by FTIR Spectroscopy and Multivariate Data Analysis
Author(s) Vongsvivut,J
Miller,MR
McNaughton,D
Heraud,P
Barrow,CJORCID iD for Barrow,CJ orcid.org/0000-0002-2153-7267
Journal name Food and Bioprocess Technology
Volume number 7
Issue number 8
Start page 2410
End page 2422
Total pages 13
Publisher Springer New York LLC
Place of publication New York, United States
Publication date 2014-01-25
ISSN 1935-5130
1935-5149
Keyword(s) FTIR spectroscopy
Marine oils
Multivariate data analysis
Polyunsaturated fatty acids (PUFAs)
Science & Technology
Life Sciences & Biomedicine
Food Science & Technology
MULTIPLICATIVE SIGNAL CORRECTION
HOKI MACRURONUS-NOVAEZELANDIAE
PARTIAL LEAST-SQUARES
INFRARED-SPECTROSCOPY
FISH-OIL
NEW-ZEALAND
LIVER OIL
DIET
OMEGA-3-FATTY-ACIDS
OPTIMIZATION
Summary A 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.
Language eng
DOI 10.1007/s11947-013-1251-0
Field of Research 030606 Structural Chemistry and Spectroscopy
Socio Economic Objective 970110 Expanding Knowledge in Technology
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2014, Springer New York LLC
Persistent URL http://hdl.handle.net/10536/DRO/DU:30067748

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