Issue 22, 2021

Trace detection of organophosphorus pesticides in vegetables via enrichment by magnetic zirconia and temperature-assisted ambient micro-fabricated glow discharge plasma desorption ionization mass spectrometry

Abstract

In this study, an innovative rapid detection technology for quickly screening and quantifying organophosphorus pesticides (OPPs) in vegetables was developed based on ambient micro-fabricated glow discharge plasma desorption/ionization mass spectrometry (MFGDP-MS), where Fe3O4/ZrO2 synthesized by a one-step coprecipitation was used for enrichment. It can not only effectively enrich OPPs, but can be separated by an external magnetic field, thereby simplifying the traditional steps of centrifugation and cleanup in sample preparation. The introduction of a temperature control system (TCS) can tackle the problem of the low ionization efficiency in MFGDP and expand its application range. Under optimized experimental conditions, the limits of detection (LODs) of the standard solution as low as 0.0068–0.7500 μg L−1 mm−2 were achieved, with relative standard deviations (RSDs) being less than 17.8%. Moreover, vegetable extracts were spiked to evaluate the accuracy of the method, and good recoveries (76.9–123.5%) were obtained. Remarkably, it took no more than 7 minutes from sample preparation to testing, resulting in significantly improved ability of the quantitative detection of plentiful samples.

Graphical abstract: Trace detection of organophosphorus pesticides in vegetables via enrichment by magnetic zirconia and temperature-assisted ambient micro-fabricated glow discharge plasma desorption ionization mass spectrometry

Supplementary files

Article information

Article type
Paper
Submitted
04 Sep 2021
Accepted
18 Sep 2021
First published
20 Sep 2021

Analyst, 2021,146, 6944-6954

Trace detection of organophosphorus pesticides in vegetables via enrichment by magnetic zirconia and temperature-assisted ambient micro-fabricated glow discharge plasma desorption ionization mass spectrometry

Y. Yang, Y. Li, Z. Huang, Y. Tian, C. Qian and Y. Duan, Analyst, 2021, 146, 6944 DOI: 10.1039/D1AN01600H

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