Different organophosphorus pesticides (OPs) normally vary in the level of toxicity to human health, but common electrochemical identification methods usually require complex electrode fabrication processes and high detection cost. To overcome these problems, a pesticide residues identification method based on multilayer paper‐based microfluidic chip was proposed. The microfluidic chip integrates the enzyme inhibition and a label‐free screen‐printed carbon electrode (SPCE). Three different pesticides were selected as study objects, respectively, avermectin, phoxim, dimethoate. This chip realizes on‐chip identification via analyzing impedance time‐sequence spectrum data aroused by the enzyme inhibition during the 15 min period. A classification model based on principal component analysis (PCA) and support vector machines (SVMs) was established to evaluate these data. Furthermore, the real‐world sample (lettuce) was tested to verify the feasibility of the proposed detection method. The results showed that the classification accuracy was achieved around 93% in multiple experiments. Therefore, the method has good stability and specificity in rapid identification of different pesticides.

中文翻译：

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通过酶抑制的阻抗时序谱鉴定多层纸基微流控芯片上的农药残留

不同的有机磷农药（OPs）对人体健康的毒性水平通常会有所不同，但是常见的电化学鉴定方法通常需要复杂的电极制造工艺和较高的检测成本。为了克服这些问题，提出了一种基于多层纸基微流控芯片的农药残留鉴定方法。微流控芯片集成了酶抑制和无标签的丝网印刷碳电极（SPCE）。选择三种不同的农药作为研究对象，分别是阿维菌素，辛硫磷，乐果。该芯片通过分析15分钟内酶抑制引起的阻抗时序谱数据来实现片上识别。建立了基于主成分分析（PCA）和支持向量机（SVM）的分类模型来评估这些数据。此外，还对真实样品（生菜）进行了测试，以验证所提出的检测方法的可行性。结果表明，在多个实验中，分类精度均达到了93％左右。因此，该方法在快速鉴别不同农药中具有良好的稳定性和特异性。