Merck
CN
  • Stir fabric phase sorptive extraction for the determination of triazine herbicides in environmental waters by liquid chromatography.

Stir fabric phase sorptive extraction for the determination of triazine herbicides in environmental waters by liquid chromatography.

Journal of chromatography. A (2014-12-24)
Mercedes Roldán-Pijuán, Rafael Lucena, Soledad Cárdenas, Miguel Valcárcel, Abuzar Kabir, Kenneth G Furton
ABSTRACT

Stir fabric phase sorptive extraction (SFPSE), which integrates sol-gel hybrid organic-inorganic coated fabric phase sorptive extraction media with a magnetic stirring mechanism, is presented for the first time. Two flexible fabric substrates, cellulose and polyester were used as the host matrix for three different sorbents e.g., sol-gel poly(tetrahydrofuran), sol-gel poly(ethylene glycol), and sol-gel poly(dimethyldiphenylsiloxane). The new microextraction device has been analytically evaluated using triazine herbicides as model compounds. The factors affecting the extraction efficiency of SFPSE have been investigated and the optimal extraction conditions have been determined. Under these optimum conditions, the limits of quantification (LOQs) for sol-gel poly(ethylene glycol) coated SFPSE device in combination with UPLC-DAD for the analysis of the seven triazine herbicides were in the range of 0. 26-1.50μg/L with precision (relative standard deviation) at 2μg/L concentration ranging from 1.4-4.8% (intra-day, n=5) and 6.8-11.8% (inter-day, n=3). Enrichment factors were found between 444 and 1411 (compared to 2000 theoretical maximum). Absolute extraction recoveries were in the range of 22.2-70.5%. The developed method was applied for the determination of selected triazine herbicides from three river water samples. Relative recoveries of the target analytes, in the range from 75 to 126%, were found to be satisfactory. The combination of SFPSE with LC-MS/MS allows the improvement of the method sensitivity to the range from 0.015μg/L to 0.026μg/L with precision better than 10.8% expressed as relative standard deviation (RSD).

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