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Issue 6, 2017
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Continuous sample drop flow-microextraction followed by high performance liquid chromatography for determination of triazine herbicides from fruit juices

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Abstract

A simple, inexpensive, reliable, dispersive-solvent-free and environmentally friendly method based on continuous sample drop flow-microextraction (CSDF-ME) and high performance liquid–liquid chromatography-ultraviolet detection (HPLC-UV) was developed for the determination of triazine herbicides in fruit juice samples. In this method, a few microliters of organic solvent is transferred to the bottom of a conical test tube. Then, 5.0 mL of aqueous solution transforms to form fine droplets while passing through the organic solvent. During this step, the target analytes were extracted from the aqueous sample droplets into the extraction solvent. The parameters affecting the extraction process were studied and optimized. Under the optimum conditions, the extraction recoveries for different fruit juices are in the range of 71–90%. The calibration graphs are linear in the range of 1.5–600 μg L−1, with the correlation coefficient (r2) being higher than 0.9977. The limits of detection (LODs) are in the range of 0.5–1.0 μg L−1, which are lower than the maximum residue levels (MRLs) established by various official organizations. The repeatability (intra-day) and reproducibility (inter-day) of the method based on five replicate measurements of 80 μg L−1 of herbicides were in the range of 2.6–4.1% and 3.7–6.3%, respectively.

Graphical abstract: Continuous sample drop flow-microextraction followed by high performance liquid chromatography for determination of triazine herbicides from fruit juices

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Article information


Submitted
16 Oct 2016
Accepted
09 Jan 2017
First published
09 Jan 2017

Anal. Methods, 2017,9, 980-985
Article type
Paper

Continuous sample drop flow-microextraction followed by high performance liquid chromatography for determination of triazine herbicides from fruit juices

T. Ahmadi-Jouibari, Y. Pasdar, M. Pirsaheb and N. Fattahi, Anal. Methods, 2017, 9, 980
DOI: 10.1039/C6AY02839J

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