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Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Typings of Edible Oils through Spectral Networking of Triacylglycerol Fingerprints

[Image: see text] Adulteration of edible oils by the manufacturers has been found frequently in modern societies. Due to the complexity of the chemical contents in edible oils, it is challenging to quantitatively determine the extent of adulteration and prove the authenticity of edible oils. In this...

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Autores principales: Kuo, Ting-Hao, Kuei, Min-Shan, Hsiao, Yi, Chung, Hsin-Hsiang, Hsu, Cheng-Chih, Chen, Hong-Jhang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2019
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6761802/
https://www.ncbi.nlm.nih.gov/pubmed/31572877
http://dx.doi.org/10.1021/acsomega.9b02433
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author Kuo, Ting-Hao
Kuei, Min-Shan
Hsiao, Yi
Chung, Hsin-Hsiang
Hsu, Cheng-Chih
Chen, Hong-Jhang
author_facet Kuo, Ting-Hao
Kuei, Min-Shan
Hsiao, Yi
Chung, Hsin-Hsiang
Hsu, Cheng-Chih
Chen, Hong-Jhang
author_sort Kuo, Ting-Hao
collection PubMed
description [Image: see text] Adulteration of edible oils by the manufacturers has been found frequently in modern societies. Due to the complexity of the chemical contents in edible oils, it is challenging to quantitatively determine the extent of adulteration and prove the authenticity of edible oils. In this study, a robust and simple MALDI-TOF-MS platform for rapid fingerprinting of triacylglycerols (TAGs) in edible oils was developed, where spectral similarity analysis was performed to quantitatively reveal correlations among edible oils in the chemical level. Specifically, we proposed oil networking, a spectral similarity-based illustration, which enabled reliable classifications of tens of commercial edible oils from vegetable and animal origins. The strategy was superior to traditional multivariate statistics due to its high sensitivity in probing subtle changes in TAG profiles, as further demonstrated by the success in determination of the adulterated lard in a food fraud in Taiwan. Finally, we showed that the platform allowed quantitative assessment of the binary mixture of olive oil and canola oil, which is a common type of olive oil adulteration in the market. Overall, these results suggested a novel strategy for chemical fingerprint-based quality control and authentication of oils in the food industry.
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spelling pubmed-67618022019-09-30 Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Typings of Edible Oils through Spectral Networking of Triacylglycerol Fingerprints Kuo, Ting-Hao Kuei, Min-Shan Hsiao, Yi Chung, Hsin-Hsiang Hsu, Cheng-Chih Chen, Hong-Jhang ACS Omega [Image: see text] Adulteration of edible oils by the manufacturers has been found frequently in modern societies. Due to the complexity of the chemical contents in edible oils, it is challenging to quantitatively determine the extent of adulteration and prove the authenticity of edible oils. In this study, a robust and simple MALDI-TOF-MS platform for rapid fingerprinting of triacylglycerols (TAGs) in edible oils was developed, where spectral similarity analysis was performed to quantitatively reveal correlations among edible oils in the chemical level. Specifically, we proposed oil networking, a spectral similarity-based illustration, which enabled reliable classifications of tens of commercial edible oils from vegetable and animal origins. The strategy was superior to traditional multivariate statistics due to its high sensitivity in probing subtle changes in TAG profiles, as further demonstrated by the success in determination of the adulterated lard in a food fraud in Taiwan. Finally, we showed that the platform allowed quantitative assessment of the binary mixture of olive oil and canola oil, which is a common type of olive oil adulteration in the market. Overall, these results suggested a novel strategy for chemical fingerprint-based quality control and authentication of oils in the food industry. American Chemical Society 2019-09-11 /pmc/articles/PMC6761802/ /pubmed/31572877 http://dx.doi.org/10.1021/acsomega.9b02433 Text en Copyright © 2019 American Chemical Society This is an open access article published under an ACS AuthorChoice License (http://pubs.acs.org/page/policy/authorchoice_termsofuse.html) , which permits copying and redistribution of the article or any adaptations for non-commercial purposes.
spellingShingle Kuo, Ting-Hao
Kuei, Min-Shan
Hsiao, Yi
Chung, Hsin-Hsiang
Hsu, Cheng-Chih
Chen, Hong-Jhang
Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Typings of Edible Oils through Spectral Networking of Triacylglycerol Fingerprints
title Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Typings of Edible Oils through Spectral Networking of Triacylglycerol Fingerprints
title_full Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Typings of Edible Oils through Spectral Networking of Triacylglycerol Fingerprints
title_fullStr Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Typings of Edible Oils through Spectral Networking of Triacylglycerol Fingerprints
title_full_unstemmed Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Typings of Edible Oils through Spectral Networking of Triacylglycerol Fingerprints
title_short Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Typings of Edible Oils through Spectral Networking of Triacylglycerol Fingerprints
title_sort matrix-assisted laser desorption/ionization mass spectrometry typings of edible oils through spectral networking of triacylglycerol fingerprints
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6761802/
https://www.ncbi.nlm.nih.gov/pubmed/31572877
http://dx.doi.org/10.1021/acsomega.9b02433
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