Development of an advanced analytical technique for detecting multiple pesticide residues in vegetables through liquid chromatography tandem mass spectroscopy (LC-MS/MS).

IF 1.4 4区 农林科学 Q4 ENVIRONMENTAL SCIENCES Journal of Environmental Science and Health Part B-pesticides Food Contaminants and Agricultural Wastes Pub Date : 2024-01-01 Epub Date: 2024-10-02 DOI:10.1080/03601234.2024.2407713
Sujan Majumder, Arvind Kumar, Sadhan Debnath, Abhinay, A N Singh, T K Behera
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Abstract

A comprehensive LC-MS/MS method, which employs Positive Electrospray Ionization (PEI) and Multiple Reaction Monitoring (MRM) was developed for the simultaneous determination of 35 pesticides belonging to various chemical classes in tomato, brinjal, chili, and okra samples. Extraction was facilitated using a modified QuEChERS method, which allows efficient sample analysis in a single run. Calibration curves for each pesticide exhibited linearity within the concentration range of 0.0025 to 0.1 µg mL-1, with correlation coefficients ranging from 0.993 to 0.999. Mean recoveries at five fortification levels (0.01 to 0.5 µg kg-1) ranged from 80 to 90%, demonstrating satisfactory precision (RSD < 20%). The matrix effects, mitigated through an optimized cleanup process, were observed within the range of 6.42% to 19.52%. The developed method having the limit of quantification of 0.01 mg kg-1 for all 35 pesticides, proved to be highly sensitive and rapid for multi-residue estimation in diverse vegetable samples. Subsequently, the method was used to analyze the market samples from Varanasi, India, which revealed the presence of pesticides like Chlorpyrifos, Chlorantraniliproleand Indoxacarb in tomato, brinjal, chili and okra. Therefore, the method could be considered as a robust tool for monitoring pesticide residues in vegetables, aiding in quality assessment and regulatory compliance in the agriculture sector.

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开发一种通过液相色谱串联质谱(LC-MS/MS)检测蔬菜中多种农药残留的先进分析技术。
采用正电喷雾离子化(PEI)和多重反应监测(MRM)技术,建立了一种综合的 LC-MS/MS 方法,用于同时测定番茄、青江菜、辣椒和秋葵样品中的 35 种不同化学类别的农药。采用改进的 QuEChERS 方法进行萃取,一次运行即可完成高效的样品分析。每种农药的校准曲线在 0.0025 至 0.1 µg mL-1 的浓度范围内呈线性关系,相关系数在 0.993 至 0.999 之间。五个添加水平(0.01 至 0.5 微克/千克-1)的平均回收率为 80% 至 90%,精度令人满意(RSD < 20%)。基质效应通过优化的净化过程得到缓解,范围在 6.42% 至 19.52% 之间。所开发的方法对所有 35 种农药的定量限均为 0.01 mg kg-1,证明该方法灵敏度高、快速,可用于多种蔬菜样品中多残留农药的测定。随后,该方法被用于分析印度瓦拉纳西的市场样本,结果显示番茄、青江菜、辣椒和秋葵中存在毒死蜱、氯氰虫酰胺和茚虫威等农药。因此,该方法可被视为监测蔬菜中农药残留的有力工具,有助于农业部门的质量评估和监管合规。
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来源期刊
CiteScore
4.00
自引率
5.00%
发文量
87
审稿时长
1 months
期刊介绍: 12 issues per year Abstracted/indexed in: Agricola; Analytical Abstracts; ASFA 3: Aquatic Pollution & Environmental Quality; BioSciences Information Service of Biological Abstracts (BIOSIS); CAB Abstracts; CAB AGBiotech News and Information; CAB Irrigation & Drainage Abstracts; CAB Soils & Fertilizers Abstracts; Chemical Abstracts Service Plus; CSA Aluminum Industry Abstracts; CSA ANTE: Abstracts in New Technology and Engineering; CSA ASFA 3 Aquatic Pollution and Environmental Quality; CSA ASSIA: Applied Social Sciences Index & Abstracts; CSA Ecology Abstracts; CSA Entomology Abstracts; CSA Environmental Engineering Abstracts; CSA Health & Safety Science Abstracts; CSA Pollution Abstracts; CSA Toxicology Abstracts; CSA Water Resource Abstracts; EBSCOhost Online Research Databases; Elsevier BIOBASE/Current Awareness in Biological Sciences; Elsevier Engineering Information: EMBASE/Excerpta Medica/ Engineering Index/COMPENDEX PLUS; Environment Abstracts; Environmental Knowledge; Food Science and Technology Abstracts; Geo Abstracts; Geobase; Food Science; Index Medicus/ MEDLINE; INIST-Pascal/ CNRS; NIOSHTIC; ISI BIOSIS Previews; Pesticides; Food Contaminants and Agricultural Wastes: Analytical Abstracts; Pollution Abstracts; PubSCIENCE; Reference Update; Research Alert; Science Citation Index Expanded (SCIE); and Water Resources Abstracts.
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