[Application of microwave-assisted extraction coupled with dispersive liquid-liquid microextraction for the determination of polycyclic aromatic hydrocarbons in vegetables, Aplikasi pengekstrakan berbantukan mikrogelombang gandingan dengan pengekstrakan mikro cecair-cecair serakan bagi penentukan hidrokarbon aromatik polisiklik dalam sayur-sayuran]

Microwave-assisted extraction (MAE) coupled with dispersive liquid-liquid microextraction (DLLME) followed by gaschromatography flame ionization detector (GC-FID) for the determination of 13 PAHs in vegetable samples was developed in this study. The analytical performances of the optimized DLLME an...

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Bibliographic Details
Main Authors: Chai, Mee Kin, Tan, Yeong Hwang, Wong, Ling Shing
Format: Article
Published: The Malaysian Analytical Sciences Society 2020
Subjects:
Online Access:http://eprints.intimal.edu.my/1455/
https://mjas.analis.com.my/mjas/v24_n1/pdf/Chai_24_1_6.pdf
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Summary:Microwave-assisted extraction (MAE) coupled with dispersive liquid-liquid microextraction (DLLME) followed by gaschromatography flame ionization detector (GC-FID) for the determination of 13 PAHs in vegetable samples was developed in this study. The analytical performances of the optimized DLLME and MAE-DLLME including limit of detection (LOD), limit of quantification (LOQ), precision, accuracy, relative extraction recovery and relative extraction factor were validated and compared. The LOD of DLLME and MAE-DLLME were in the range of 0.040-0.400 and 0.0200-0.080 µg/L, respectively. For DLLME, precision and accuracy were 1.22-7.50% (RSD) and 71.77% to 90.93%, respectively; while for MAE-DLLME, were 0.77%-3.07% (RSD) and 83.65-98.42%, respectively. The relative extraction recovery was improved from 70.81% – 85.41% in DLLME to 85.79% - 99.61% in MAE-DLLME. The relative enrichment factors were ranged from 126-156 and 165 to 202 for DLLME and MAE-DLLME, respectively. The volume of extraction solvent was reduced from 50 µL to 30 µL in MAEDLLME. The overall analytical performances of MAE-DLLME is better than DLLME. The application of proposed MAEDLLME in real samples was also investigated and discussed.