Title: Application of Support Vector Machines to 1H NMR Data of Fish Oils: Methodology for the Confirmation of Wild and Farmed Salmon and their Origins
Authors: MASOUM SaeedMALABAT ChristopheJALALI-HERAVI MehdiGUILLOU CLAUDEREZZI SergeRUTLEDGE Douglas
Citation: ANALYTICAL AND BIOANALYTICAL CHEMISTRY vol. 387 p. 1499-1510
Publisher: SPRINGER HEIDELBERG
Publication Year: 2007
JRC Publication N°: JRC44363
ISSN: 1618-2642
URI: http://www.springerlink.com/content/321u073841t48606/fulltext.html
http://publications.jrc.ec.europa.eu/repository/handle/JRC44363
DOI: 10.1007/s00216-006-1025-x
Type: Articles in Journals
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.
JRC Institute:Institute for Health and Consumer Protection

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