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Metal-organic framework-monolith composite-based in-tube solid phase microextraction on-line coupled to high-performance liquid chromatography-fluorescence detection for the highly sensitive monitoring of fluoroquinolones in water and food samples
- Pang, Jinling, Liao, Yingmin, Huang, Xiaojia, Ye, Ziwen, Yuan, Dongxing
- Talanta 2019 v.199 pp. 499-506
- automation, detection limit, fluorescence, fluoroquinolones, high performance liquid chromatography, honey, imidazoles, monitoring, silica, solid phase microextraction, solvents, standard deviation, surface area, zinc
- In this study, a new metal-organic framework-monolith composite for in-tube solid phase microextraction phase (IT-SPME) of fluoroquinolones (FQs) was prepared. 4-Vinylbenzoic acid was copolymerized with ethylenedimethacrylate in a fused silica capillary to form porous monolith. After that, zeolitic imidazolate frameworks (ZIF-8) were synthesized in situ within the pores and the surface of the monolith by controlled layer-by-layer self-assembly of Zn2+ and imidazole. The introduction of ZIF-8 enhanced the surface area of monolith composite, and thus, improving the extraction performance of IT-SPME for FQs obviously. Under the optimized conditions, a highly sensitive method for the monitoring of FQs residue in water and honey samples was developed by the on-line combination of IT-SPME with high-performance liquid chromatography with fluorescence detection (HPLC-FLD). The limits of detection (S/N = 3) for the targeted FQs in water and honey samples were as low as 0.14–0.61 ng/L and 0.39–1.1 ng/L, respectively. The relative standard deviations (RSDs) for intra-day and inter-day assay variability were less than 10% in all samples. The established on-line IT-SPME-HPLC-FLD was successfully used to detect ultra-trace FQs in environmental water and honey samples. Recoveries at different spiked concentrations ranged from 80.1% to 119% and 80.2–117% for water and honey samples, respectively, with satisfactory reproducibility. Compared to up-to-date reported methods, the proposed approach exhibits some features such as high sensitivity, convenience, partial automation, low consumptions of sample and solvent.