Chemometric Differentiation of Sole and Plaice Fish Fillets Using Three Near-Infrared Instruments

Fish species substitution is one of the most common forms of fraud all over the world, as fish identification can be very challenging for both consumers and experienced inspectors in the case of fish sold as fillets. The difficulties in distinguishing among different species may generate a "gre...

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Veröffentlicht in:Foods 2022-06, Vol.11 (11), p.1643
Hauptverfasser: Cavallini, Nicola, Pennisi, Francesco, Giraudo, Alessandro, Pezzolato, Marzia, Esposito, Giovanna, Gavoci, Gentian, Magnani, Luca, Pianezzola, Alberto, Geobaldo, Francesco, Savorani, Francesco, Bozzetta, Elena
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Sprache:eng
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Zusammenfassung:Fish species substitution is one of the most common forms of fraud all over the world, as fish identification can be very challenging for both consumers and experienced inspectors in the case of fish sold as fillets. The difficulties in distinguishing among different species may generate a "grey area" in which mislabelling can occur. Thus, the development of fast and reliable tools able to detect such frauds in the field is of crucial importance. In this study, we focused on the distinction between two flatfish species largely available on the market, namely the Guinean sole ( ) and European plaice ( ), which are very similar looking. Fifty fillets of each species were analysed using three near-infrared (NIR) instruments: the handheld SCiO (Consumer Physics), the portable MicroNIR (VIAVI), and the benchtop MPA (Bruker). PLS-DA classification models were built using the spectral datasets, and all three instruments provided very good results, showing high accuracy: 94.1% for the SCiO and MicroNIR portable instruments, and 90.1% for the MPA benchtop spectrometer. The good classification results of the approach combining NIR spectroscopy, and simple chemometric classification methods suggest great applicability directly in the context of real-world marketplaces, as well as in official control plans.
ISSN:2304-8158
2304-8158
DOI:10.3390/foods11111643