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Rapid and non-invasive measurements of fat and pigment concentrations in live and slaughtered Atlantic salmon (Salmo salar L.)

Abstract

The aim of this study was to non-invasively determine fat and pigment concentrations in salmon muscle based on visible and near infrared (VIS/NIR) spectroscopy measurements of live/whole fish and fillets, and by means of digital photography (DP) of fillets. The fish used were two populations of farmed Atlantic salmon (Salmo, salar L.) consisting of 46 salmon averaging 0.7 kg (range 0.17-1.7 kg, Group S) and 30 salmon averaging 2.3 kg (range 1.4-4.1 kg, Group L). Chemical analyses (fat and pigment content) and computerized tomography, CT (fat content) were used as reference methods. Group L was analysed in the live state (VIS/NIR 1, after gutting (VIS/NIR and CT), and as fillets (VIS/NIR and DP). Group S was analysed in the gutted state (VIS/NIR) and as fillets (VIS/NIR and DP). VIS spectroscopy predictions of pigment in whole salmon from Group S were obtained with a root mean square error of prediction (RMSEP) of 0.9 mg kg(-1) astaxanthin, and a correlation between VIS spectroscopy predicted and chemically measured pigment of r=0.85 (p<0.0001). The fat concentration was determined by the NIR spectroscopy in live fish with RMSEP = 1.0 fat% unit, and a correlation with chemical reference values of r=0.94 (p<0.0001). Fat predictions from NIR spectroscopy correlated also well with predictions from CT analyses, r=0.95 (p<0.0001). VIS spectroscopy and DP were equally well suited to determine pigment concentrations in salmon fillets, with prediction errors of only 0.4 mg kg(-1) astaxanthin, and a correlation with chemically determined pigment of r=0.92 (p<0.0001). The results obtained in the present study are the first to demonstrate successful non-invasive pigment predictions in whole salmon using VIS/NIR spectroscopy, and the possibility for simultaneous, rapid and non-destructive quantification of fat and pigment concentrations. (C) 2008 Elsevier B.V. All rights reserved.

Category

Academic article

Language

English

Author(s)

Affiliation

  • Nofima, The Norwegian Institute of Food, Fisheries and Aquaculture Research
  • Norges miljø- og biovitenskapelige universitet
  • SINTEF Digital / Smart Sensors and Microsystems

Year

2008

Published in

Aquaculture

ISSN

0044-8486

Publisher

Elsevier

Volume

280

Issue

1-4

Page(s)

129 - 135

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