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Quantitative Detection of Trace Malachite Green in Aquiculture Water Samples by Extractive Electrospray Ionization Mass Spectrometry

Exposure to malachite green (MG) may pose great health risks to humans; thus, it is of prime importance to develop fast and robust methods to quantitatively screen the presence of malachite green in water. Herein the application of extractive electrospray ionization mass spectrometry (EESI-MS) has b...

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Autores principales: Fang, Xiaowei, Yang, Shuiping, Chingin, Konstantin, Zhu, Liang, Zhang, Xinglei, Zhou, Zhiquan, Zhao, Zhanfeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4997500/
https://www.ncbi.nlm.nih.gov/pubmed/27529262
http://dx.doi.org/10.3390/ijerph13080814
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author Fang, Xiaowei
Yang, Shuiping
Chingin, Konstantin
Zhu, Liang
Zhang, Xinglei
Zhou, Zhiquan
Zhao, Zhanfeng
author_facet Fang, Xiaowei
Yang, Shuiping
Chingin, Konstantin
Zhu, Liang
Zhang, Xinglei
Zhou, Zhiquan
Zhao, Zhanfeng
author_sort Fang, Xiaowei
collection PubMed
description Exposure to malachite green (MG) may pose great health risks to humans; thus, it is of prime importance to develop fast and robust methods to quantitatively screen the presence of malachite green in water. Herein the application of extractive electrospray ionization mass spectrometry (EESI-MS) has been extended to the trace detection of MG within lake water and aquiculture water, due to the intensive use of MG as a biocide in fisheries. This method has the advantage of obviating offline liquid-liquid extraction or tedious matrix separation prior to the measurement of malachite green in native aqueous medium. The experimental results indicate that the extrapolated detection limit for MG was ~3.8 μg·L(−1) (S/N = 3) in lake water samples and ~0.5 μg·L(−1) in ultrapure water under optimized experimental conditions. The signal intensity of MG showed good linearity over the concentration range of 10–1000 μg·L(−1). Measurement of practical water samples fortified with MG at 0.01, 0.1 and 1.0 mg·L(−1) gave a good validation of the established calibration curve. The average recoveries and relative standard deviation (RSD) of malachite green in lake water and Carassius carassius fish farm effluent water were 115% (6.64% RSD), 85.4% (9.17% RSD) and 96.0% (7.44% RSD), respectively. Overall, the established EESI-MS/MS method has been demonstrated suitable for sensitive and rapid (<2 min per sample) quantitative detection of malachite green in various aqueous media, indicating its potential for online real-time monitoring of real life samples.
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spelling pubmed-49975002016-08-26 Quantitative Detection of Trace Malachite Green in Aquiculture Water Samples by Extractive Electrospray Ionization Mass Spectrometry Fang, Xiaowei Yang, Shuiping Chingin, Konstantin Zhu, Liang Zhang, Xinglei Zhou, Zhiquan Zhao, Zhanfeng Int J Environ Res Public Health Article Exposure to malachite green (MG) may pose great health risks to humans; thus, it is of prime importance to develop fast and robust methods to quantitatively screen the presence of malachite green in water. Herein the application of extractive electrospray ionization mass spectrometry (EESI-MS) has been extended to the trace detection of MG within lake water and aquiculture water, due to the intensive use of MG as a biocide in fisheries. This method has the advantage of obviating offline liquid-liquid extraction or tedious matrix separation prior to the measurement of malachite green in native aqueous medium. The experimental results indicate that the extrapolated detection limit for MG was ~3.8 μg·L(−1) (S/N = 3) in lake water samples and ~0.5 μg·L(−1) in ultrapure water under optimized experimental conditions. The signal intensity of MG showed good linearity over the concentration range of 10–1000 μg·L(−1). Measurement of practical water samples fortified with MG at 0.01, 0.1 and 1.0 mg·L(−1) gave a good validation of the established calibration curve. The average recoveries and relative standard deviation (RSD) of malachite green in lake water and Carassius carassius fish farm effluent water were 115% (6.64% RSD), 85.4% (9.17% RSD) and 96.0% (7.44% RSD), respectively. Overall, the established EESI-MS/MS method has been demonstrated suitable for sensitive and rapid (<2 min per sample) quantitative detection of malachite green in various aqueous media, indicating its potential for online real-time monitoring of real life samples. MDPI 2016-08-11 2016-08 /pmc/articles/PMC4997500/ /pubmed/27529262 http://dx.doi.org/10.3390/ijerph13080814 Text en © 2016 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
Fang, Xiaowei
Yang, Shuiping
Chingin, Konstantin
Zhu, Liang
Zhang, Xinglei
Zhou, Zhiquan
Zhao, Zhanfeng
Quantitative Detection of Trace Malachite Green in Aquiculture Water Samples by Extractive Electrospray Ionization Mass Spectrometry
title Quantitative Detection of Trace Malachite Green in Aquiculture Water Samples by Extractive Electrospray Ionization Mass Spectrometry
title_full Quantitative Detection of Trace Malachite Green in Aquiculture Water Samples by Extractive Electrospray Ionization Mass Spectrometry
title_fullStr Quantitative Detection of Trace Malachite Green in Aquiculture Water Samples by Extractive Electrospray Ionization Mass Spectrometry
title_full_unstemmed Quantitative Detection of Trace Malachite Green in Aquiculture Water Samples by Extractive Electrospray Ionization Mass Spectrometry
title_short Quantitative Detection of Trace Malachite Green in Aquiculture Water Samples by Extractive Electrospray Ionization Mass Spectrometry
title_sort quantitative detection of trace malachite green in aquiculture water samples by extractive electrospray ionization mass spectrometry
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4997500/
https://www.ncbi.nlm.nih.gov/pubmed/27529262
http://dx.doi.org/10.3390/ijerph13080814
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