Application of support vector machines to 1H NMR data of fish oils: methodology for the confirmation of wild and farmed salmon and their origins.
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. (1)H 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.
Masoum
Saeed
S
Department of Chemistry, Sharif University of Technology, P.O. Box 11365-9516 Tehran, Iran. s_masoum@alum.sharif.edu
Malabat
Christophe
C
Jalali-Heravi
Mehdi
M
Guillou
Claude
C
Rezzi
Serge
S
Rutledge
Douglas Neil
DN
D000818:Animals; D000829:Animals, Domestic; D000835:Animals, Wild; D005227:Fatty Acids / Q000737:chemistry; D005395:Fish Oils / Q000032:analysis* / Q000096:biosynthesis / Q000737:chemistry*; D005398:Fisheries; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D011522:Protons; D012474:Salmon / Q000145:classification / Q000378:metabolism*
D005227:Fatty Acids; D005395:Fish Oils; D011522:Protons