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Utilizing a Rapid Multi-Plug Filtration Cleanup Method for 72 Pesticide Residues in Grape Wines Followed by Detection with Gas Chromatography Tandem Mass Spectrometry
A convenient and fast multi-residue method for the efficient identification and quantification of 72 pesticides belonging to different chemical classes in red and white grape wines has been developed. The analysis was based on gas chromatography tandem quadrupole mass spectrometric determination (GC...
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/PMC8623294/ https://www.ncbi.nlm.nih.gov/pubmed/34829012 http://dx.doi.org/10.3390/foods10112731 |
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author | Liu, Shaowen Bai, Aijuan Song, Le Zou, Nan Han, Yongtao Zhou, Li Yu, Chuanshan Li, Changjun Pan, Canping |
author_facet | Liu, Shaowen Bai, Aijuan Song, Le Zou, Nan Han, Yongtao Zhou, Li Yu, Chuanshan Li, Changjun Pan, Canping |
author_sort | Liu, Shaowen |
collection | PubMed |
description | A convenient and fast multi-residue method for the efficient identification and quantification of 72 pesticides belonging to different chemical classes in red and white grape wines has been developed. The analysis was based on gas chromatography tandem quadrupole mass spectrometric determination (GC–MS/MS). The optimization strategy involved the selection of the amount of multi-walled carbon nanotubes (MWCNTs) and the number of cleanup procedure cycles for multi-plug filtration cleanup (m-PFC) to achieve ideal recoveries and reduce the sample matrix compounds in the final extracts. The optimized procedure obtained consistent recoveries between 70.2 and 108.8% (70.2 and 108.8% for white wine, and 72.3 and 108.4% for red wine), with relative standard deviations (RSDs) that were generally lower than 9.2% at the three spiking levels of 0.01, 0.05 and 0.1 mg/kg. The linearity was studied in the range between 0.002 and 0.1 mg/kg using pesticide standards prepared both in pure solvent and in the presence of the matrix, showing coefficients of determination (R(2)) higher than 0.9495 for all the pesticides. To improve accuracy, matrix-matched calibration curves were used for calculating the quantification results. Finally, the method was used successfully for detecting pesticide residues in commercial grape wines. |
format | Online Article Text |
id | pubmed-8623294 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-86232942021-11-27 Utilizing a Rapid Multi-Plug Filtration Cleanup Method for 72 Pesticide Residues in Grape Wines Followed by Detection with Gas Chromatography Tandem Mass Spectrometry Liu, Shaowen Bai, Aijuan Song, Le Zou, Nan Han, Yongtao Zhou, Li Yu, Chuanshan Li, Changjun Pan, Canping Foods Article A convenient and fast multi-residue method for the efficient identification and quantification of 72 pesticides belonging to different chemical classes in red and white grape wines has been developed. The analysis was based on gas chromatography tandem quadrupole mass spectrometric determination (GC–MS/MS). The optimization strategy involved the selection of the amount of multi-walled carbon nanotubes (MWCNTs) and the number of cleanup procedure cycles for multi-plug filtration cleanup (m-PFC) to achieve ideal recoveries and reduce the sample matrix compounds in the final extracts. The optimized procedure obtained consistent recoveries between 70.2 and 108.8% (70.2 and 108.8% for white wine, and 72.3 and 108.4% for red wine), with relative standard deviations (RSDs) that were generally lower than 9.2% at the three spiking levels of 0.01, 0.05 and 0.1 mg/kg. The linearity was studied in the range between 0.002 and 0.1 mg/kg using pesticide standards prepared both in pure solvent and in the presence of the matrix, showing coefficients of determination (R(2)) higher than 0.9495 for all the pesticides. To improve accuracy, matrix-matched calibration curves were used for calculating the quantification results. Finally, the method was used successfully for detecting pesticide residues in commercial grape wines. MDPI 2021-11-08 /pmc/articles/PMC8623294/ /pubmed/34829012 http://dx.doi.org/10.3390/foods10112731 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 Liu, Shaowen Bai, Aijuan Song, Le Zou, Nan Han, Yongtao Zhou, Li Yu, Chuanshan Li, Changjun Pan, Canping Utilizing a Rapid Multi-Plug Filtration Cleanup Method for 72 Pesticide Residues in Grape Wines Followed by Detection with Gas Chromatography Tandem Mass Spectrometry |
title | Utilizing a Rapid Multi-Plug Filtration Cleanup Method for 72 Pesticide Residues in Grape Wines Followed by Detection with Gas Chromatography Tandem Mass Spectrometry |
title_full | Utilizing a Rapid Multi-Plug Filtration Cleanup Method for 72 Pesticide Residues in Grape Wines Followed by Detection with Gas Chromatography Tandem Mass Spectrometry |
title_fullStr | Utilizing a Rapid Multi-Plug Filtration Cleanup Method for 72 Pesticide Residues in Grape Wines Followed by Detection with Gas Chromatography Tandem Mass Spectrometry |
title_full_unstemmed | Utilizing a Rapid Multi-Plug Filtration Cleanup Method for 72 Pesticide Residues in Grape Wines Followed by Detection with Gas Chromatography Tandem Mass Spectrometry |
title_short | Utilizing a Rapid Multi-Plug Filtration Cleanup Method for 72 Pesticide Residues in Grape Wines Followed by Detection with Gas Chromatography Tandem Mass Spectrometry |
title_sort | utilizing a rapid multi-plug filtration cleanup method for 72 pesticide residues in grape wines followed by detection with gas chromatography tandem mass spectrometry |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8623294/ https://www.ncbi.nlm.nih.gov/pubmed/34829012 http://dx.doi.org/10.3390/foods10112731 |
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