Identification and characterization of fish oil supplements based on fatty acid analysis combined with a hierarchical clustering algorithm

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.