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Identification and characterization of fish oil supplements based on fatty acid analysis combined with a hierarchical clustering algorithm
Author(s) -
Khoomrung Sakda,
Raber Georg,
Laoteng Kobkul,
Francesconi Kevin A.
Publication year - 2014
Publication title -
european journal of lipid science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.614
H-Index - 94
eISSN - 1438-9312
pISSN - 1438-7697
DOI - 10.1002/ejlt.201300369
Subject(s) - fish oil , eicosapentaenoic acid , fatty acid , fish <actinopterygii> , identification (biology) , cluster analysis , food science , hierarchical clustering , polyunsaturated fatty acid , chemistry , biology , computer science , biochemistry , botany , artificial intelligence , fishery
We report a method for simple screening and quality assessment of fish oil supplements based on fatty acid profiles of 25 commercial fish oil supplements determined by using GC/MS with a hierarchical clustering algorithm. Different fatty acid profiles were obtained for the various fish oil products derived from different sources and processes. The contents of eicosapentaenoic acid (20:5 n‐3) and DHA (22:6 n‐3), and of other specific fatty acids as well, could be used as a chemotaxonomic marker to characterize the fish oils. A hierarchical clustering algorithm was then generated and used to efficiently categorize the fish oil products in terms of fish origin, oil components, and production process. Identification of fish oil supplements.