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Rapid Differentiation of Unfrozen and Frozen-Thawed Tuna with Non-Destructive Methods and Classification Models: Bioelectrical Impedance Analysis (BIA), Near-Infrared Spectroscopy (NIR) and Time Domain Reflectometry (TDR)
The performances of three non-destructive sensors, based on different principles, bioelectrical impedance analysis (BIA), near-infrared spectroscopy (NIR) and time domain reflectometry (TDR), were studied to discriminate between unfrozen and frozen-thawed fish. Bigeye tuna (Thunnus obesus) was selec...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8750308/ https://www.ncbi.nlm.nih.gov/pubmed/35010181 http://dx.doi.org/10.3390/foods11010055 |
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author | Nieto-Ortega, Sonia Melado-Herreros, Ángela Foti, Giuseppe Olabarrieta, Idoia Ramilo-Fernández, Graciela Gonzalez Sotelo, Carmen Teixeira, Bárbara Velasco, Amaya Mendes, Rogério |
author_facet | Nieto-Ortega, Sonia Melado-Herreros, Ángela Foti, Giuseppe Olabarrieta, Idoia Ramilo-Fernández, Graciela Gonzalez Sotelo, Carmen Teixeira, Bárbara Velasco, Amaya Mendes, Rogério |
author_sort | Nieto-Ortega, Sonia |
collection | PubMed |
description | The performances of three non-destructive sensors, based on different principles, bioelectrical impedance analysis (BIA), near-infrared spectroscopy (NIR) and time domain reflectometry (TDR), were studied to discriminate between unfrozen and frozen-thawed fish. Bigeye tuna (Thunnus obesus) was selected as a model to evaluate these technologies. The addition of water and additives is usual in the fish industry, thus, in order to have a wide range of possible commercial conditions, some samples were injected with different water solutions (based on different concentrations of salt, polyphosphates and a protein hydrolysate solution). Three different models, based on partial least squares discriminant analysis (PLS-DA), were developed for each technology. This is a linear classification method that combines the properties of partial least squares (PLS) regression with the classification power of a discriminant technique. The results obtained in the evaluation of the test set were satisfactory for all the sensors, giving NIR the best performance (accuracy = 0.91, error rate = 0.10). Nevertheless, the classification accomplished with BIA and TDR data resulted also satisfactory and almost equally as good, with accuracies of 0.88 and 0.86 and error rates of 0.14 and 0.15, respectively. This work opens new possibilities to discriminate between unfrozen and frozen-thawed fish samples with different non-destructive alternatives, regardless of whether or not they have added water. |
format | Online Article Text |
id | pubmed-8750308 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-87503082022-01-12 Rapid Differentiation of Unfrozen and Frozen-Thawed Tuna with Non-Destructive Methods and Classification Models: Bioelectrical Impedance Analysis (BIA), Near-Infrared Spectroscopy (NIR) and Time Domain Reflectometry (TDR) Nieto-Ortega, Sonia Melado-Herreros, Ángela Foti, Giuseppe Olabarrieta, Idoia Ramilo-Fernández, Graciela Gonzalez Sotelo, Carmen Teixeira, Bárbara Velasco, Amaya Mendes, Rogério Foods Article The performances of three non-destructive sensors, based on different principles, bioelectrical impedance analysis (BIA), near-infrared spectroscopy (NIR) and time domain reflectometry (TDR), were studied to discriminate between unfrozen and frozen-thawed fish. Bigeye tuna (Thunnus obesus) was selected as a model to evaluate these technologies. The addition of water and additives is usual in the fish industry, thus, in order to have a wide range of possible commercial conditions, some samples were injected with different water solutions (based on different concentrations of salt, polyphosphates and a protein hydrolysate solution). Three different models, based on partial least squares discriminant analysis (PLS-DA), were developed for each technology. This is a linear classification method that combines the properties of partial least squares (PLS) regression with the classification power of a discriminant technique. The results obtained in the evaluation of the test set were satisfactory for all the sensors, giving NIR the best performance (accuracy = 0.91, error rate = 0.10). Nevertheless, the classification accomplished with BIA and TDR data resulted also satisfactory and almost equally as good, with accuracies of 0.88 and 0.86 and error rates of 0.14 and 0.15, respectively. This work opens new possibilities to discriminate between unfrozen and frozen-thawed fish samples with different non-destructive alternatives, regardless of whether or not they have added water. MDPI 2021-12-27 /pmc/articles/PMC8750308/ /pubmed/35010181 http://dx.doi.org/10.3390/foods11010055 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Nieto-Ortega, Sonia Melado-Herreros, Ángela Foti, Giuseppe Olabarrieta, Idoia Ramilo-Fernández, Graciela Gonzalez Sotelo, Carmen Teixeira, Bárbara Velasco, Amaya Mendes, Rogério Rapid Differentiation of Unfrozen and Frozen-Thawed Tuna with Non-Destructive Methods and Classification Models: Bioelectrical Impedance Analysis (BIA), Near-Infrared Spectroscopy (NIR) and Time Domain Reflectometry (TDR) |
title | Rapid Differentiation of Unfrozen and Frozen-Thawed Tuna with Non-Destructive Methods and Classification Models: Bioelectrical Impedance Analysis (BIA), Near-Infrared Spectroscopy (NIR) and Time Domain Reflectometry (TDR) |
title_full | Rapid Differentiation of Unfrozen and Frozen-Thawed Tuna with Non-Destructive Methods and Classification Models: Bioelectrical Impedance Analysis (BIA), Near-Infrared Spectroscopy (NIR) and Time Domain Reflectometry (TDR) |
title_fullStr | Rapid Differentiation of Unfrozen and Frozen-Thawed Tuna with Non-Destructive Methods and Classification Models: Bioelectrical Impedance Analysis (BIA), Near-Infrared Spectroscopy (NIR) and Time Domain Reflectometry (TDR) |
title_full_unstemmed | Rapid Differentiation of Unfrozen and Frozen-Thawed Tuna with Non-Destructive Methods and Classification Models: Bioelectrical Impedance Analysis (BIA), Near-Infrared Spectroscopy (NIR) and Time Domain Reflectometry (TDR) |
title_short | Rapid Differentiation of Unfrozen and Frozen-Thawed Tuna with Non-Destructive Methods and Classification Models: Bioelectrical Impedance Analysis (BIA), Near-Infrared Spectroscopy (NIR) and Time Domain Reflectometry (TDR) |
title_sort | rapid differentiation of unfrozen and frozen-thawed tuna with non-destructive methods and classification models: bioelectrical impedance analysis (bia), near-infrared spectroscopy (nir) and time domain reflectometry (tdr) |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8750308/ https://www.ncbi.nlm.nih.gov/pubmed/35010181 http://dx.doi.org/10.3390/foods11010055 |
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