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Optimization and Validation of Liquid Phase Microextraction Method Based on Oil Droplets to Quantify Algal Metabolites (2-Methylisoborneol, Geosmin, Etc.) in Drinking Water Supplies Publisher



Tahmasebi R1 ; Saatloo NV2 ; Sadighara P3 ; Mohamadi S4
Authors
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Authors Affiliations
  1. 1. Research and Department of Chromatography, Iranian Academic Center for Education, Culture and Research (ACECR), Urmia, Iran
  2. 2. Department of Food Hygiene and Quality Control, Faculty of Veterinary Medicine, Urmia University, Urmia, Iran
  3. 3. Department of Environmental Health, Food Safety Division, Faculty of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  4. 4. Department of Food Hygiene and Quality Control, Faculty of Veterinary Medicine, Shahrekord University, P.O. Box: 315, Shahrekord, Iran

Source: Water# Air# and Soil Pollution Published:2023


Abstract

A novel liquid phase microextraction method based on solvent oil droplets was optimized and validated for sample pretreatment of algal odorous metabolites (i.e., 2-Methylisoborneol, Geosmin, etc.) in drinking water supplies prior to gas chromatography. Segregation and condensation are based on the diffusion of solvent oil micro drops as an extracting solvent in the sample solution (drinking water supplies) and then back extraction of the analytes to another organic solvent, which is a three-phase direct immersion type of LPME. The important variables influencing the microextraction procedure such as type and volume of extracting oil and back extracting solvent, time and temperature of extraction, and ionic strength were optimized separately. Under optimal conditions, the correlation coefficient, limits of detection, linear dynamic ranges, preconcentration factors, and precision of the method were evaluated. The method displayed a high linearity range for the analytes (R 2 ≥ 0.9808–0.9959), low limit of detection (0.03–3.01 μg L−1), and a good linear dynamic range (0.08–50 μg L−1). The precision comprised of reproducibility and repeatability were evaluated by computing the relative standard deviation (RSD %), which was ranged as 3.48–3.87%. Consequently, the optimized method along with the GC-FID method was successfully extracted the algal metabolites from water samples, with satisfactory recoveries (94–97%). © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.