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Detection of olive oil adulteration with vegetable oils by ultra‐performance convergence chromatography‐quadrupole time‐of‐flight mass spectrometry (UPC(2)‐QTOF MS) coupled with multivariate data analysis based on the differences of triacylglycerol compositions

Three different vegetable oils, including soybean, corn, and sunflower oils, were differentiated from olive oil by using ultra‐performance convergence chromatography coupled with quadrupole time‐of‐flight (UPC(2)‐QTOF MS) and multivariate data analysis based on their differences in triacylglycerol c...

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Autores principales: Luo, Yinghua, Gao, Boyan, Zhang, Yaqiong, Yu, Liangli (Lucy)
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7382181/
https://www.ncbi.nlm.nih.gov/pubmed/32724638
http://dx.doi.org/10.1002/fsn3.1664
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author Luo, Yinghua
Gao, Boyan
Zhang, Yaqiong
Yu, Liangli (Lucy)
author_facet Luo, Yinghua
Gao, Boyan
Zhang, Yaqiong
Yu, Liangli (Lucy)
author_sort Luo, Yinghua
collection PubMed
description Three different vegetable oils, including soybean, corn, and sunflower oils, were differentiated from olive oil by using ultra‐performance convergence chromatography coupled with quadrupole time‐of‐flight (UPC(2)‐QTOF MS) and multivariate data analysis based on their differences in triacylglycerol compositions. Then, olive oil was adulterated by adding these three vegetable oils in 1%, 0.75%, and 0.5% (v/v), and the adulterated olive oils were differentiated from the pure olive oils using the similar analytical strategies but different data processing approaches. After that, the representative markers in differentiating the adulterations were selected, and a mathematical model was created to detect the olive oil adulteration based on these specific markers. These results indicated that UPC(2)‐QTOF MS coupled with multivariate data analysis is a sensitive and accurate method in detecting olive oil adulteration, even in 0.5% adulteration level (v/v). This method could be applied in olive oil adulteration detection, and potentially beneficial to the oil industry.
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spelling pubmed-73821812020-07-27 Detection of olive oil adulteration with vegetable oils by ultra‐performance convergence chromatography‐quadrupole time‐of‐flight mass spectrometry (UPC(2)‐QTOF MS) coupled with multivariate data analysis based on the differences of triacylglycerol compositions Luo, Yinghua Gao, Boyan Zhang, Yaqiong Yu, Liangli (Lucy) Food Sci Nutr Original Research Three different vegetable oils, including soybean, corn, and sunflower oils, were differentiated from olive oil by using ultra‐performance convergence chromatography coupled with quadrupole time‐of‐flight (UPC(2)‐QTOF MS) and multivariate data analysis based on their differences in triacylglycerol compositions. Then, olive oil was adulterated by adding these three vegetable oils in 1%, 0.75%, and 0.5% (v/v), and the adulterated olive oils were differentiated from the pure olive oils using the similar analytical strategies but different data processing approaches. After that, the representative markers in differentiating the adulterations were selected, and a mathematical model was created to detect the olive oil adulteration based on these specific markers. These results indicated that UPC(2)‐QTOF MS coupled with multivariate data analysis is a sensitive and accurate method in detecting olive oil adulteration, even in 0.5% adulteration level (v/v). This method could be applied in olive oil adulteration detection, and potentially beneficial to the oil industry. John Wiley and Sons Inc. 2020-05-25 /pmc/articles/PMC7382181/ /pubmed/32724638 http://dx.doi.org/10.1002/fsn3.1664 Text en © 2020 The Authors. Food Science & Nutrition published by Wiley Periodicals LLC. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Research
Luo, Yinghua
Gao, Boyan
Zhang, Yaqiong
Yu, Liangli (Lucy)
Detection of olive oil adulteration with vegetable oils by ultra‐performance convergence chromatography‐quadrupole time‐of‐flight mass spectrometry (UPC(2)‐QTOF MS) coupled with multivariate data analysis based on the differences of triacylglycerol compositions
title Detection of olive oil adulteration with vegetable oils by ultra‐performance convergence chromatography‐quadrupole time‐of‐flight mass spectrometry (UPC(2)‐QTOF MS) coupled with multivariate data analysis based on the differences of triacylglycerol compositions
title_full Detection of olive oil adulteration with vegetable oils by ultra‐performance convergence chromatography‐quadrupole time‐of‐flight mass spectrometry (UPC(2)‐QTOF MS) coupled with multivariate data analysis based on the differences of triacylglycerol compositions
title_fullStr Detection of olive oil adulteration with vegetable oils by ultra‐performance convergence chromatography‐quadrupole time‐of‐flight mass spectrometry (UPC(2)‐QTOF MS) coupled with multivariate data analysis based on the differences of triacylglycerol compositions
title_full_unstemmed Detection of olive oil adulteration with vegetable oils by ultra‐performance convergence chromatography‐quadrupole time‐of‐flight mass spectrometry (UPC(2)‐QTOF MS) coupled with multivariate data analysis based on the differences of triacylglycerol compositions
title_short Detection of olive oil adulteration with vegetable oils by ultra‐performance convergence chromatography‐quadrupole time‐of‐flight mass spectrometry (UPC(2)‐QTOF MS) coupled with multivariate data analysis based on the differences of triacylglycerol compositions
title_sort detection of olive oil adulteration with vegetable oils by ultra‐performance convergence chromatography‐quadrupole time‐of‐flight mass spectrometry (upc(2)‐qtof ms) coupled with multivariate data analysis based on the differences of triacylglycerol compositions
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7382181/
https://www.ncbi.nlm.nih.gov/pubmed/32724638
http://dx.doi.org/10.1002/fsn3.1664
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