Application of support vector machines to 1H NMR data of fish oils:: methodology for the confirmation of wild and farmed salmon and their origins

被引:59
作者
Masoum, Saeed
Malabat, Christophe
Jalali-Heravi, Mehdi
Guillou, Claude
Rezzi, Serge
Rutledge, Douglas Neil
机构
[1] INRA, UMR 214, Chim Analyt Lab, INA PG, F-75005 Paris, France
[2] Sharif Univ Technol, Dept Chem, Tehran, Iran
[3] Commiss European Communities, Joint Res Ctr, Inst Hlth & Consumer Protect, Phys & Chem Exposure Unit, I-21020 Ispra, Italy
关键词
support vector machines (SVMs); salmon; authenticity; NMR; correlation optimized warping (COW);
D O I
10.1007/s00216-006-1025-x
中图分类号
Q5 [生物化学];
学科分类号
071010 [生物化学与分子生物学]; 081704 [应用化学];
摘要
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. H-1 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.
引用
收藏
页码:1499 / 1510
页数:12
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