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Detection and Quantification of Tomato Paste Adulteration Using Conventional and Rapid Analytical Methods

Tomato, and its concentrate are important food ingredients with outstanding gastronomic and industrial importance due to their unique organoleptic, dietary, and compositional properties. Various forms of food adulteration are often suspected in the different tomato-based products causing major econo...

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Autores principales: Vitalis, Flora, Zaukuu, John-Lewis Zinia, Bodor, Zsanett, Aouadi, Balkis, Hitka, Géza, Kaszab, Timea, Zsom-Muha, Viktoria, Gillay, Zoltan, Kovacs, Zoltan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7663517/
https://www.ncbi.nlm.nih.gov/pubmed/33114443
http://dx.doi.org/10.3390/s20216059
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author Vitalis, Flora
Zaukuu, John-Lewis Zinia
Bodor, Zsanett
Aouadi, Balkis
Hitka, Géza
Kaszab, Timea
Zsom-Muha, Viktoria
Gillay, Zoltan
Kovacs, Zoltan
author_facet Vitalis, Flora
Zaukuu, John-Lewis Zinia
Bodor, Zsanett
Aouadi, Balkis
Hitka, Géza
Kaszab, Timea
Zsom-Muha, Viktoria
Gillay, Zoltan
Kovacs, Zoltan
author_sort Vitalis, Flora
collection PubMed
description Tomato, and its concentrate are important food ingredients with outstanding gastronomic and industrial importance due to their unique organoleptic, dietary, and compositional properties. Various forms of food adulteration are often suspected in the different tomato-based products causing major economic and sometimes even health problems for the farmers, food industry and consumers. Near infrared (NIR) spectroscopy and electronic tongue (e-tongue) have been lauded as advanced, high sensitivity techniques for quality control. The aim of the present research was to detect and predict relatively low concentration of adulterants, such as paprika seed and corn starch (0.5, 1, 2, 5, 10%), sucrose and salt (0.5, 1, 2, 5%), in tomato paste using conventional (soluble solid content, consistency) and advanced analytical techniques (NIR spectroscopy, e-tongue). The results obtained with the conventional methods were analyzed with univariate statistics (ANOVA), while the data obtained with advanced analytical methods were analyzed with multivariate methods (Principal component analysis (PCA), linear discriminant analysis (LDA), partial least squares regression (PLSR). The conventional methods were only able to detect adulteration at higher concentrations (5–10%). For NIRS and e-tongue, good accuracies were obtained, even in identifying minimal adulterant concentrations (0.5%). Comparatively, NIR spectroscopy proved to be easier to implement and more accurate during our evaluations, when the adulterant contents were estimated with R(2) above 0.96 and root mean square error (RMSE) below 1%.
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spelling pubmed-76635172020-11-14 Detection and Quantification of Tomato Paste Adulteration Using Conventional and Rapid Analytical Methods Vitalis, Flora Zaukuu, John-Lewis Zinia Bodor, Zsanett Aouadi, Balkis Hitka, Géza Kaszab, Timea Zsom-Muha, Viktoria Gillay, Zoltan Kovacs, Zoltan Sensors (Basel) Article Tomato, and its concentrate are important food ingredients with outstanding gastronomic and industrial importance due to their unique organoleptic, dietary, and compositional properties. Various forms of food adulteration are often suspected in the different tomato-based products causing major economic and sometimes even health problems for the farmers, food industry and consumers. Near infrared (NIR) spectroscopy and electronic tongue (e-tongue) have been lauded as advanced, high sensitivity techniques for quality control. The aim of the present research was to detect and predict relatively low concentration of adulterants, such as paprika seed and corn starch (0.5, 1, 2, 5, 10%), sucrose and salt (0.5, 1, 2, 5%), in tomato paste using conventional (soluble solid content, consistency) and advanced analytical techniques (NIR spectroscopy, e-tongue). The results obtained with the conventional methods were analyzed with univariate statistics (ANOVA), while the data obtained with advanced analytical methods were analyzed with multivariate methods (Principal component analysis (PCA), linear discriminant analysis (LDA), partial least squares regression (PLSR). The conventional methods were only able to detect adulteration at higher concentrations (5–10%). For NIRS and e-tongue, good accuracies were obtained, even in identifying minimal adulterant concentrations (0.5%). Comparatively, NIR spectroscopy proved to be easier to implement and more accurate during our evaluations, when the adulterant contents were estimated with R(2) above 0.96 and root mean square error (RMSE) below 1%. MDPI 2020-10-24 /pmc/articles/PMC7663517/ /pubmed/33114443 http://dx.doi.org/10.3390/s20216059 Text en © 2020 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Vitalis, Flora
Zaukuu, John-Lewis Zinia
Bodor, Zsanett
Aouadi, Balkis
Hitka, Géza
Kaszab, Timea
Zsom-Muha, Viktoria
Gillay, Zoltan
Kovacs, Zoltan
Detection and Quantification of Tomato Paste Adulteration Using Conventional and Rapid Analytical Methods
title Detection and Quantification of Tomato Paste Adulteration Using Conventional and Rapid Analytical Methods
title_full Detection and Quantification of Tomato Paste Adulteration Using Conventional and Rapid Analytical Methods
title_fullStr Detection and Quantification of Tomato Paste Adulteration Using Conventional and Rapid Analytical Methods
title_full_unstemmed Detection and Quantification of Tomato Paste Adulteration Using Conventional and Rapid Analytical Methods
title_short Detection and Quantification of Tomato Paste Adulteration Using Conventional and Rapid Analytical Methods
title_sort detection and quantification of tomato paste adulteration using conventional and rapid analytical methods
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7663517/
https://www.ncbi.nlm.nih.gov/pubmed/33114443
http://dx.doi.org/10.3390/s20216059
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