Literature DB >> 30716913

Assessing fish authenticity by direct analysis in real time-high resolution mass spectrometry and multivariate analysis: discrimination between wild-type and farmed salmon.

Giuseppina M Fiorino1, Ilario Losito2, Elisabetta De Angelis1, Marco Arlorio3, Antonio F Logrieco1, Linda Monaci4.   

Abstract

The constant increase in seafood consumption worldwide has led to a parallel growth of the incidence of products obtained by aquaculture on the market, but also of the fraudulent commercialization of farmed products as wild-type ones. A careful characterization of the lipid component of seafood products based on chromatography-mass spectrometry techniques has been reported as a promising approach to reliably differentiate farmed from wild-type products. In this context, a fast method based on Direct Analysis in Real Time (DART) coupled to High Resolution Mass Spectrometry (HRMS) based on a single stage Orbitrap mass analyzer, integrated by Principal Component Analysis (PCA), was developed in the present study and applied to scout for spectral features useful to discriminate wild-type from farmed salmon of Salmo salar species. In particular, normalized intensities obtained for the 30 most intense signals (all referred to fatty acids, FA) detected in negative ion DART-HRMS spectra of the lipid extracts of salmon fillets [26 wild-type from Canada, 74 farmed from Canada (25), Norway (25) and Chile (24)] were considered as the variables for PCA. The scatterplot referred to the first two principal components showed a clear distinction between wild-type and farmed salmon, which gathered as a unique cluster, despite the remarkable differences in their geographical origin. In accordance with previous studies based on more complex and time-demanding analytical approaches, three saturated (14:0, 16:0 and 18:0) FA, along with unsaturated ones having 20 or 22 carbon atoms, were found as the main discriminating variables for wild-type salmons, whereas FA with compositions 18:1, 18:2, 18:3 and several oxidized forms arising from them were found to have a significantly higher incidence in farmed salmon. The method was further validated by Discriminant Analysis (DA) performed on the same dataset used for PCA integrated by data obtained from 6 commercial samples, putatively referred to farmed Norwegian salmon. Results showed that 100% of the latter were correctly classified as farmed type. Relative abundances of DART-HRMS signals related to specific FA appear then very promising for the differentiation of wild-type salmon from farmed ones, a very relevant issue in the context of consumers' protection from seafood frauds.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Direct Analysis in Real Time-High Resolution Mass Spectrometry (DART-HRMS); Food authenticity; Multivariate analysis; Salmon; Validation

Mesh:

Substances:

Year:  2018        PMID: 30716913     DOI: 10.1016/j.foodres.2018.10.013

Source DB:  PubMed          Journal:  Food Res Int        ISSN: 0963-9969            Impact factor:   6.475


  6 in total

1.  Analysis of Lipids in Green Coffee by Ultra-Performance Liquid Chromatography-Time-of-Flight Tandem Mass Spectrometry.

Authors:  Yijun Liu; Min Chen; Yimin Li; Xingqin Feng; Yunlan Chen; Lijing Lin
Journal:  Molecules       Date:  2022-08-18       Impact factor: 4.927

Review 2.  Spectroscopic techniques for authentication of animal origin foods.

Authors:  Vandana Chaudhary; Priyanka Kajla; Aastha Dewan; R Pandiselvam; Claudia Terezia Socol; Cristina Maria Maerescu
Journal:  Front Nutr       Date:  2022-09-20

3.  Optimization of an Untargeted DART-HRMS Method Envisaging Identification of Potential Markers for Saffron Authenticity Assessment.

Authors:  Elisabetta De Angelis; Rosa Pilolli; Alice Bejjani; Rocco Guagnano; Cristiano Garino; Marco Arlorio; Linda Monaci
Journal:  Foods       Date:  2021-05-29

Review 4.  Geographical Origin Authentication of Agri-Food Products: Α Review.

Authors:  Katerina Katerinopoulou; Achilleas Kontogeorgos; Constantinos E Salmas; Angelos Patakas; Athanasios Ladavos
Journal:  Foods       Date:  2020-04-13

5.  Machine Learning Approaches Applied to GC-FID Fatty Acid Profiles to Discriminate Wild from Farmed Salmon.

Authors:  Liliana Grazina; P J Rodrigues; Getúlio Igrejas; Maria A Nunes; Isabel Mafra; Marco Arlorio; M Beatriz P P Oliveira; Joana S Amaral
Journal:  Foods       Date:  2020-11-07

Review 6.  Suitability of High-Resolution Mass Spectrometry for Routine Analysis of Small Molecules in Food, Feed and Water for Safety and Authenticity Purposes: A Review.

Authors:  Maxime Gavage; Philippe Delahaut; Nathalie Gillard
Journal:  Foods       Date:  2021-03-12
  6 in total

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