Preparation of molecularly imprinted polymer with class-specific recognition for determination of 29 sulfonylurea herbicides in agro-products

文献类型： 外文期刊

第一作者： Feng, Gege

作者： Feng, Gege;Wang, Miao;Wang, Mengqiang;Li, Zhuang;Wang, Shanshan;Zheng, Lufei;Wang, Jing;She, Yongxin;Sun, Jianchun;Abd El-Aty, A. M.;Abd El-Aty, A. M.;Abd El-Aty, A. M.

作者机构：

关键词： Sulfonylurea herbicides; Molecularly imprinted polymer; Solid-phase extraction; Agro-products; Residue detection; LC-MS/MS

期刊名称：JOURNAL OF CHROMATOGRAPHY A （ 影响因子：4.049； 五年影响因子：3.861 ）

ISSN： 0021-9673

年卷期： 2021 年 1647 卷

页码：

收录情况： SCI

摘要： Molecularly imprinting polymers with high selectivity toward 29 sulfonylurea herbicides were synthesized by precipitation polymerization, using metsulfuron-methyl and chlorsulfuron as the template molecule, 4-vinylpyridine as the function monomer, divinylbenzene as the crosslinking agent, and acetonitrile as porogen. The imprinted polymers were characterized and measured by scanning electron microscopy (SEM) and equilibrium adsorption experiments. The molecularly imprinted polymers displayed specific recognition for the tested 29 sulfonylurea herbicides, and the maximum apparent binding capacity was found to be 18.81 mg/g. The synthesized polymer was used as a solid-phase extraction (SPE) column coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS) for determination of the tested analytes in agro-products. Within the range of 2-100 mu g/L, the tested analytes have achieved a good linear association with correlation coefficient (R-2) > 0.999. The calculated limits of detection (LODs, S/N=3) as along with limits of quantification (LOQs, S/N= 10) were in the ranges of 0.005-0.07 mu g/L and 0.018-0.23 mu g/L, respectively. Under different spiking levels, the recovery rates were ranged from 74.8% - 110.5%, and the relative standard deviation (RSDs) were < 5.3%. Finally, the feasibility of the proposed methodology was successfully applied for detection of sulfonylurea herbicides in crops, vegetables, and oils samples. (c) 2021 Elsevier B.V. All rights reserved.

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