Issue 33, 2022

TiO2@MOF-919(Fe–Cu) as a sorbent for the extraction of benzoylurea pesticides from irrigation water and fruit juices

Abstract

The TiO2@MOF-919(Fe–Cu) solid-phase extraction material was prepared by growing MOF-919(Fe–Cu) in situ on three-dimensional radial TiO2 microspheres by a simple solvothermal method. This combination drew on both the resources of good single dispersion and extraction rate, which made it a better extraction material. It was accompanied with high-performance liquid chromatography (SPE–HPLC) for the separation and determination of four benzoylurea pesticides (triflumuron, chlorbenzuron, teflubenzuron and diflubenzuron) in afforestation irrigation water and juice samples (grape, peach and apple juices). Under the optimal conditions, the linearity of the method ranged from 1 to 400 μg L−1 with a correlation coefficient (R2) ≥ 0.9994, while the detection limit was in the range of 0.40–0.56 μg L−1 for the four pesticides. The adopted material showed good reusability and can be used no less than 10 times. The intra-day and inter-day precision were in the range of 1.78–3.24% and 4.06–5.08%, respectively. The proposed method was then successfully applied for the detection of benzoylurea pesticides in the spiked samples with good recoveries (72.3–108.4%) and good precision (5.15%) due to π–π and hydrophobic interactions between the analytes and adsorbent. The results show that the composite had the potential to be used as a SPE adsorbent for the enrichment and extraction of benzene ring structures containing imide groups in actual samples.

Graphical abstract: TiO2@MOF-919(Fe–Cu) as a sorbent for the extraction of benzoylurea pesticides from irrigation water and fruit juices

Supplementary files

Article information

Article type
Paper
Submitted
24 شوال 1443
Accepted
17 ذو الحجة 1443
First published
20 ذو الحجة 1443

Anal. Methods, 2022,14, 3153-3159

TiO2@MOF-919(Fe–Cu) as a sorbent for the extraction of benzoylurea pesticides from irrigation water and fruit juices

L. Mei, T. Si, S. Wang, J. Zhu, H. Tang and X. Liang, Anal. Methods, 2022, 14, 3153 DOI: 10.1039/D2AY00842D

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