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分散液液微萃取结合微流控纸基分析装置用于水样中有机磷和氨基甲酸酯类农药的测定。

Dispersive liquid-liquid microextraction coupled with microfluidic paper-based analytical device for the determination of organophosphate and carbamate pesticides in the water sample.

机构信息

Center for Environmental Science, College of Natural and Computational Sciences, Addis Ababa University, P.O. Box: 1176, Addis Ababa, Ethiopia.

Department of Chemistry, Graduate School of Natural Science and Technology, Okayama University, Tsushimanana, Okayama, 700-8530, Japan.

出版信息

Anal Sci. 2022 Oct;38(10):1359-1367. doi: 10.1007/s44211-022-00167-7. Epub 2022 Jul 31.

Abstract

A microfluidic paper-based analytical device (µ-PAD) is a promising new technology platform for the development of extremely low-cost sensing devices. However, it has low sensitivity that might not enable to measure maximum allowable concentration of various pollutants in the environment. In this study, a dispersive liquid-liquid microextraction (DLLME) was developed as a preconcentration method to enhance the sensitivity of the µ-PAD for trace analysis of selected pesticides. Four critical parameters (volume of n-hexane and acetone, extraction time, NaCl amount) that affect the efficiency of DLLME have been optimized using response surface methodology. An acceptable mean recovery of 79-97% and 83-93% was observed at 1 µg L and 5 µg L fortification level, respectively, with very good repeatability (2.2-6.01% RSD) and reproducibility (5.60-10.41% RSD). Very high enrichment factors ranging from 317 to 1471 were obtained. The limits of detection for the studied analytes were in the range of 0.18-0.41 µg L which is much lower than the WHO limits of 5-50 µg L for similar category of analytes. Therefore, by coupling DLLME with µ-PAD, a sensitivity that allows to detect environmental threat and also that surpassed most of the previous reports have been achieved in this study. This implies that the preconcentration step has a paramount contribution to address the sensitivity problem associated with µ-PAD.

摘要

一种微流控纸基分析装置(µ-PAD)是开发极低成本传感装置的有前途的新技术平台。然而,它的灵敏度较低,可能无法测量环境中各种污染物的最大允许浓度。在这项研究中,开发了分散液 - 液微萃取(DLLME)作为一种预浓缩方法,以提高µ-PAD 对选定农药痕量分析的灵敏度。使用响应面法优化了影响 DLLME效率的四个关键参数(正己烷和丙酮的体积、萃取时间、NaCl 量)。在 1 µg L 和 5 µg L 加标水平下,观察到可接受的平均回收率为 79-97%和 83-93%,具有非常好的重复性(2.2-6.01%RSD)和重现性(5.60-10.41%RSD)。获得了从 317 到 1471 的非常高的富集因子。研究分析物的检出限范围为 0.18-0.41 µg L,远低于世界卫生组织对类似类别的分析物规定的 5-50 µg L 的限值。因此,通过将 DLLME 与 µ-PAD 耦合,在这项研究中实现了可以检测环境威胁的灵敏度,并且超过了大多数先前的报告。这意味着预浓缩步骤对解决 µ-PAD 相关的灵敏度问题有重要贡献。

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