What the fish? Tracing the geographical origin of fish using NIR spectroscopy

Food authentication is a growing concern with rising complexities of the food supply network, with fish being an easy target of food fraud. In this regard, NIR spectroscopy has been used as an efficient tool for food authentication. This article reviews the latest research advances on NIR based fish...

Full description

Saved in:
Bibliographic Details
Main Authors: Nidhi Dalal, Raffaela Ofano, Luigi Ruggiero, Antonio Giandonato Caporale, Paola Adamo
Format: Article
Language:English
Published: Elsevier 2024-01-01
Series:Current Research in Food Science
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2665927124001151
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1846125291345281024
author Nidhi Dalal
Raffaela Ofano
Luigi Ruggiero
Antonio Giandonato Caporale
Paola Adamo
author_facet Nidhi Dalal
Raffaela Ofano
Luigi Ruggiero
Antonio Giandonato Caporale
Paola Adamo
author_sort Nidhi Dalal
collection DOAJ
description Food authentication is a growing concern with rising complexities of the food supply network, with fish being an easy target of food fraud. In this regard, NIR spectroscopy has been used as an efficient tool for food authentication. This article reviews the latest research advances on NIR based fish authentication. The process from sampling/sample preparation to data analysis has been covered. Special attention was given to NIR spectra pre-processing and its unsupervised and supervised analysis. Sampling is an important aspect of traceability study and samples chosen ought to be a true representative of the population. NIR spectra acquired is often laden with overlapping bands, scattering and highly multicollinear. It needs adequate pre-processing to remove all undesirable features. The pre-processing technique can make or break a model and thus need a trial-and-error approach to find the best fit. As for spectral analysis and modelling, multicollinear nature of NIR spectra demands unsupervised analysis (PCA) to compact the features before application of supervised multivariate techniques such as LDA, PLS-DA, QDA etc. Machine learning approach of modelling has shown promising result in food authentication modelling and negates the need for unsupervised analysis before modelling.
format Article
id doaj-art-f1b4283f7f2e41f2a5aeb8c21c196349
institution Kabale University
issn 2665-9271
language English
publishDate 2024-01-01
publisher Elsevier
record_format Article
series Current Research in Food Science
spelling doaj-art-f1b4283f7f2e41f2a5aeb8c21c1963492024-12-13T11:02:58ZengElsevierCurrent Research in Food Science2665-92712024-01-019100789What the fish? Tracing the geographical origin of fish using NIR spectroscopyNidhi Dalal0Raffaela Ofano1Luigi Ruggiero2Antonio Giandonato Caporale3Paola Adamo4Corresponding author.; Department of Agricultural Sciences, University of Naples ‘Federico II’, ItalyDepartment of Agricultural Sciences, University of Naples ‘Federico II’, ItalyDepartment of Agricultural Sciences, University of Naples ‘Federico II’, ItalyDepartment of Agricultural Sciences, University of Naples ‘Federico II’, ItalyDepartment of Agricultural Sciences, University of Naples ‘Federico II’, ItalyFood authentication is a growing concern with rising complexities of the food supply network, with fish being an easy target of food fraud. In this regard, NIR spectroscopy has been used as an efficient tool for food authentication. This article reviews the latest research advances on NIR based fish authentication. The process from sampling/sample preparation to data analysis has been covered. Special attention was given to NIR spectra pre-processing and its unsupervised and supervised analysis. Sampling is an important aspect of traceability study and samples chosen ought to be a true representative of the population. NIR spectra acquired is often laden with overlapping bands, scattering and highly multicollinear. It needs adequate pre-processing to remove all undesirable features. The pre-processing technique can make or break a model and thus need a trial-and-error approach to find the best fit. As for spectral analysis and modelling, multicollinear nature of NIR spectra demands unsupervised analysis (PCA) to compact the features before application of supervised multivariate techniques such as LDA, PLS-DA, QDA etc. Machine learning approach of modelling has shown promising result in food authentication modelling and negates the need for unsupervised analysis before modelling.http://www.sciencedirect.com/science/article/pii/S2665927124001151Fish authenticationFood traceabilityNIR based modellingNIR data analysisSeafood fraudFood fraud
spellingShingle Nidhi Dalal
Raffaela Ofano
Luigi Ruggiero
Antonio Giandonato Caporale
Paola Adamo
What the fish? Tracing the geographical origin of fish using NIR spectroscopy
Current Research in Food Science
Fish authentication
Food traceability
NIR based modelling
NIR data analysis
Seafood fraud
Food fraud
title What the fish? Tracing the geographical origin of fish using NIR spectroscopy
title_full What the fish? Tracing the geographical origin of fish using NIR spectroscopy
title_fullStr What the fish? Tracing the geographical origin of fish using NIR spectroscopy
title_full_unstemmed What the fish? Tracing the geographical origin of fish using NIR spectroscopy
title_short What the fish? Tracing the geographical origin of fish using NIR spectroscopy
title_sort what the fish tracing the geographical origin of fish using nir spectroscopy
topic Fish authentication
Food traceability
NIR based modelling
NIR data analysis
Seafood fraud
Food fraud
url http://www.sciencedirect.com/science/article/pii/S2665927124001151
work_keys_str_mv AT nidhidalal whatthefishtracingthegeographicaloriginoffishusingnirspectroscopy
AT raffaelaofano whatthefishtracingthegeographicaloriginoffishusingnirspectroscopy
AT luigiruggiero whatthefishtracingthegeographicaloriginoffishusingnirspectroscopy
AT antoniogiandonatocaporale whatthefishtracingthegeographicaloriginoffishusingnirspectroscopy
AT paolaadamo whatthefishtracingthegeographicaloriginoffishusingnirspectroscopy