Spray-assisted drop formation liquid-phase microextraction for the determination of sertraline in environmental water samples with matrix-matching calibration in GC–MS

Author:

Zeytinci Nagehan Kübra,Akbıyık Hilal,Tezgin Emine,Zaman Buse Tuğba,Bozyiğit Gamze Dalgıç,Şaylan Meltem,Bakırdere Sezgin

Abstract

AbstractSertraline is used as an antidepressant drug for the treatment of psychiatric disorders, including anxiety and depression. In the current study, a simple and effective method was developed for the sensitive monitoring of sertraline in water samples using a GC–MS system. The spray-assisted droplet formation liquid-phase microextraction (SADF-LPME) method was used as a sample preparation method for the enrichment of analytes. Accordingly, dichloromethane was used as an extraction solvent and easily dispersed into a sample/standard solution using a lab-made modified spray device without using a dispersing solvent. The significant factors affecting the SADF-LPME efficiency, including sample pH, mixing conditions, extraction solvent type, and spray cycle, were univariately optimized to ascertain the extraction performance and applicability of the system. Under the optimized conditions, the plotted calibration curve of the method was linear in the range of 100.2–2011.7 µg/kg (mass-based standard preparation) with a good correlation coefficient (R2) of 0.9997. The detection and quantification limits of method were found to be 37.5 and 125 µg/kg, respectively. Validation of the method was successfully carried out using different tap water samples and applying a matrix-matching calibration strategy. The acceptable percent recoveries were recorded between 77.3 and 133.7%, with high repeatability. The recommended method is an alternative and fast extraction method with several advantages, including a simple experimental process, good dispersibility, and fast and superior extraction performance. It can be readily applicable to the monitoring and quantification of sertraline in tap water samples with good precision and accuracy.

Funder

Türkiye Bilimsel ve Teknolojik Araştırma Kurumu

Publisher

Springer Science and Business Media LLC

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