(13)C NMR pattern recognition techniques for the classification of Atlantic salmon (Salmo salar L.) according to their wild, farmed, and geographical origin.

(13)C nuclear magnetic resonance (NMR) in combination with multivariate data analysis was used to (1) discriminate between farmed and wild Atlantic salmon ( Salmo salar L.), (2) discriminate between different geographical origins, and (3) verify the origin of market samples. Muscle lipids from 195 Atlantic salmon of known origin (wild and farmed salmon from Norway, Scotland, Canada, Iceland, Ireland, the Faroes, and Tasmania) in addition to market samples were analyzed by (13)C NMR spectroscopy and multivariate analysis. Both probabilistic neural networks (PNN) and support vector machines (SVM) provided excellent discrimination (98.5 and 100.0%, respectively) between wild and farmed salmon. Discrimination with respect to geographical origin was somewhat more difficult, with correct classification rates ranging from 82.2 to 99.3% by PNN and SVM, respectively. In the analysis of market samples, five fish labeled and purchased as wild salmon were classified as farmed salmon (indicating mislabeling), and there were also some discrepancies between the classification and the product declaration with regard to geographical origin.

Determination of origin of Atlantic salmon (Salmo salar): the use of multiprobe and multielement isotopic analyses in combination with fatty acid composition to assess wild or farmed origin.

Variability within the stable isotope ratios in various lipidic fractions and the fatty acid composition of muscle oil has been analyzed for a large sample (171 fish) of wild and farmed Atlantic salmon ( Salmo salar) from 32 origins within Europe, North America, and Tasmania. Sampling was extended over all seasons in 2 consecutive years and included fish raised by different practices, in order to maximize the range of variation present. It is shown that two readily measured parameters, delta 15N measured on choline and delta18 O measured on total oil, can be successfully used to discriminate between fish of authentic wild and farmed origin. However, the certainty of identification of mislabeling in market-derived fish is strengthened by including the percentage of linoleic acid C18:2n-6 in the lipidic fraction. Thus, several apparent misidentifications were found. The combination of these three analytical parameters and the size of the database generated makes the method practical for implementation in official laboratories as a tool of labeling verification.