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