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Abstract
Support vector machines (SVMs) were used as a novel learning machine in the authentication of the origin of salmon. SVMs have the advantage of relying on a well-developed theory and have already proved to be successful in a number of practical applications. This paper provides a new and effective method for the discrimination between wild and farm salmon and eliminates the possibility of fraud through misrepresentation of the country of origin of salmon. The method requires a very simple sample preparation of the fish oils extracted from the white muscle of salmon samples. 1H NMR spectroscopic analysis provides data that is very informative for analysing the fatty acid constituents of the fish oils. The SVM has been able to distinguish correctly between the wild and farmed salmon; however ca. 5% of the country of origins were misclassified.
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1 Sharif University of Technology, Department of Chemistry, Tehran, Iran (GRID:grid.412553.4) (ISNI:0000000107409747)
2 Laboratoire de Chimie Analytique, Paris, France (GRID:grid.412553.4)
3 Physical and Chemical Exposure Unit, European Commission, Joint Research Centre, Institute for Health and Consumer Protection, Ispra (VA), Italy (GRID:grid.434554.7) (ISNI:0000 0004 1758 4137)
4 Physical and Chemical Exposure Unit, European Commission, Joint Research Centre, Institute for Health and Consumer Protection, Ispra (VA), Italy (GRID:grid.434554.7) (ISNI:0000 0004 1758 4137); BioAnalytical Science, Metabonomics and Biomarkers, Nestlé Research Center, Lausanne 26, Switzerland (GRID:grid.419905.0) (ISNI:0000 0001 0066 4948)
5 Laboratoire de Chimie Analytique, Paris, France (GRID:grid.419905.0)





