Abstract

In the present contribution, the potential of LC-HR-MS coupled to software based data handling for fish authenticity and traceability will be presented. Salmon salar discrimination based on geographic origin was accomplished by untargeted LC-HR-MS analysis on hybrid quadrupole/OrbitrapTM-based mass spectrometer and by raw data mining with commercial software for small molecules identification. Salmon filets were extracted by methanol/chloroform mixtures and both the polar and non-polar fractions were analysed for a comprehensive compound characterization and differential analysis. In particular, conventional chromatographic separation was accomplished with a relatively short linear gradient with full scan HR-MS acquisitions performed in both positive and negative modes. The gathered spectra were processed via the commercial software Compound Discoverer v.2.0 (Thermo Fisher Scientific) in order to detect and group the unknown compounds with an accuracy <= 2ppm and achieve a preliminary statistical analysis of the integrated peak areas. The study was carried out by setting as grouping factor the geographic origin (Canada, Norway and Chile) and data were pretreated by means of the retention time alignment of extracted chromatograms and background subtraction. Volcano plots combining the statistical significance of the identified compounds and magnitude of change in the extracted peak areas were investigated in order to filter the compound list to the main species most suitable in discriminating the different salmon groups. Edited compounds list constrained by means of p-value thresholds was subjected within the same workflow to further statistical evaluation by PCA in order to simplify the multivariate system and highlight the intrinsic trend of the analyzed samples in the reduced projected space. The PCA performed on polar fraction of the salmon extracts allowed to distinguish clearly three data groups belonging to the three geographic origins (Canada, Norway and Chile).

Autore Pugliese

• Monaci Linda , Pilolli Rosa

Tutti gli autori

• L. Monaci; R. Pilolli; E. De Angelis; A.F. Logrieco; M. Arlorio; L. Hollosi; M. Godula

Titolo volume/Rivista

Non Disponibile

Anno di pubblicazione

2018

ISSN

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ISBN

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Settori ERC

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