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Chemometric tools for the authentication of cod liver oil based on nuclear magnetic resonance and infrared spectroscopy data
Cod liver oil is a popular dietary supplement marketed as a rich source of omega-3 fatty acids as well as vitamins A and D. Due to its high market price, cod liver oil is vulnerable to adulteration with lower priced vegetable oils. In this study, (1)H and (13)C nuclear magnetic resonance spectroscop...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6834736/ https://www.ncbi.nlm.nih.gov/pubmed/31401671 http://dx.doi.org/10.1007/s00216-019-02063-y |
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author | Giese, Editha Rohn, Sascha Fritsche, Jan |
author_facet | Giese, Editha Rohn, Sascha Fritsche, Jan |
author_sort | Giese, Editha |
collection | PubMed |
description | Cod liver oil is a popular dietary supplement marketed as a rich source of omega-3 fatty acids as well as vitamins A and D. Due to its high market price, cod liver oil is vulnerable to adulteration with lower priced vegetable oils. In this study, (1)H and (13)C nuclear magnetic resonance spectroscopy, Fourier transform infrared spectroscopy, and gas chromatography (coupled to a flame ionization detector) were used in combination with multivariate statistics to determine cod liver oil adulteration with common vegetable oils (sunflower and canola oils). Artificial neural networks (ANN) were able to differentiate adulteration levels based on infrared spectra with a detection limit of 0.22% and a root mean square error of prediction (RMSEP) of 0.86%. ANN models using (1)H NMR and (13)C NMR data yielded detection limits of 3.0% and 1.8% and RMSEPs of 2.7% and 1.1%, respectively. In comparison, the ANN model based on fatty acid profiles determined by gas chromatography achieved a detection limit of 0.81% and an RMSEP of 1.1%. The approach of using spectroscopic techniques in combination with multivariate statistics can be regarded as a promising tool for the authentication of cod liver oil and may pave the way for a holistic quality assessment of fish oils. [Figure: see text] ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00216-019-02063-y) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6834736 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-68347362019-12-03 Chemometric tools for the authentication of cod liver oil based on nuclear magnetic resonance and infrared spectroscopy data Giese, Editha Rohn, Sascha Fritsche, Jan Anal Bioanal Chem Research Paper Cod liver oil is a popular dietary supplement marketed as a rich source of omega-3 fatty acids as well as vitamins A and D. Due to its high market price, cod liver oil is vulnerable to adulteration with lower priced vegetable oils. In this study, (1)H and (13)C nuclear magnetic resonance spectroscopy, Fourier transform infrared spectroscopy, and gas chromatography (coupled to a flame ionization detector) were used in combination with multivariate statistics to determine cod liver oil adulteration with common vegetable oils (sunflower and canola oils). Artificial neural networks (ANN) were able to differentiate adulteration levels based on infrared spectra with a detection limit of 0.22% and a root mean square error of prediction (RMSEP) of 0.86%. ANN models using (1)H NMR and (13)C NMR data yielded detection limits of 3.0% and 1.8% and RMSEPs of 2.7% and 1.1%, respectively. In comparison, the ANN model based on fatty acid profiles determined by gas chromatography achieved a detection limit of 0.81% and an RMSEP of 1.1%. The approach of using spectroscopic techniques in combination with multivariate statistics can be regarded as a promising tool for the authentication of cod liver oil and may pave the way for a holistic quality assessment of fish oils. [Figure: see text] ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00216-019-02063-y) contains supplementary material, which is available to authorized users. Springer Berlin Heidelberg 2019-08-10 2019 /pmc/articles/PMC6834736/ /pubmed/31401671 http://dx.doi.org/10.1007/s00216-019-02063-y Text en © The Author(s) 2019, corrected publication 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. |
spellingShingle | Research Paper Giese, Editha Rohn, Sascha Fritsche, Jan Chemometric tools for the authentication of cod liver oil based on nuclear magnetic resonance and infrared spectroscopy data |
title | Chemometric tools for the authentication of cod liver oil based on nuclear magnetic resonance and infrared spectroscopy data |
title_full | Chemometric tools for the authentication of cod liver oil based on nuclear magnetic resonance and infrared spectroscopy data |
title_fullStr | Chemometric tools for the authentication of cod liver oil based on nuclear magnetic resonance and infrared spectroscopy data |
title_full_unstemmed | Chemometric tools for the authentication of cod liver oil based on nuclear magnetic resonance and infrared spectroscopy data |
title_short | Chemometric tools for the authentication of cod liver oil based on nuclear magnetic resonance and infrared spectroscopy data |
title_sort | chemometric tools for the authentication of cod liver oil based on nuclear magnetic resonance and infrared spectroscopy data |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6834736/ https://www.ncbi.nlm.nih.gov/pubmed/31401671 http://dx.doi.org/10.1007/s00216-019-02063-y |
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