Literature DB >> 29146353

Handheld NIR device: A non-targeted approach to assess authenticity of fish fillets and patties.

Silvia Grassi1, Ernestina Casiraghi2, Cristina Alamprese3.   

Abstract

This study evaluates the reliability of a handheld NIR device in distinguishing fillets and patties of Atlantic cod (n = 80) from those of haddock (n = 90), in comparison with a FT-NIR benchtop spectrometer. The authentication issue was faced by Linear Discriminant Analysis (LDA) and Soft Independent Modelling of Class Analogy (SIMCA), pre-treating spectral data with different algorithms, and validating models both internally and externally. The best LDA models gave 100% correct classification in prediction. Sensitivity >65% and specificity >74% in prediction were calculated for the best SIMCA models. No significant differences (P > .05) were found between the two instruments by McNemar test. Thus, the work demonstrated that a handheld NIR device can be a simple, cost-effective, and reliable alternative to benchtop spectrometers in fish fillet and patty authentication. These important findings can help in improving commercial fraud fight, extending the possibility to authenticate fish species also in processed products.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Atlantic cod; Fish authentication; Haddock; Near infrared spectroscopy; Portable device

Mesh:

Year:  2017        PMID: 29146353     DOI: 10.1016/j.foodchem.2017.09.145

Source DB:  PubMed          Journal:  Food Chem        ISSN: 0308-8146            Impact factor:   7.514


  15 in total

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7.  The Feasibility of Two Handheld Spectrometers for Meat Speciation Combined with Chemometric Methods and Its Application for Halal Certification.

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8.  Monitoring the Processing of Dry Fermented Sausages with a Portable NIRS Device.

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Review 9.  Historical Evolution and Food Control Achievements of Near Infrared Spectroscopy, Electronic Nose, and Electronic Tongue-Critical Overview.

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10.  Differentiation between Fresh and Thawed Cephalopods Using NIR Spectroscopy and Multivariate Data Analysis.

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Journal:  Foods       Date:  2021-03-03
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