数字农科院2.0

An intelligent self-powered sensing platform for ultrasensitive and precise detection of acetamiprid based on DNA cascade amplification combined with a capacitor

文献类型： 外文期刊

作者： Yu Ya;Lian Chen;Chenchen Jin;Zhongdan Liang;Cuiwen Jiang;Liang Wei;Lufei Zheng;Feiyan Yan

作者机构：

关键词： Acetamiprid detection;Cascaded signal amplification;Graphdiyne;Self-powered sensor

期刊名称： Microchemical Journal

ISSN： 0026-265X

年卷期： 2025 年 218 卷

页码：

收录情况： SCIE（2025版）

摘要： Acetamiprid is a widely used agricultural insecticide that plays a significant role in protecting the growth of crops. At present, the construction of acetamiprid analysis technology that is sensitive, accurate, miniaturized and intelligent is not only a topic of great practical significance, but also faces many technical challenges. In this study, a portable intelligent self-powered sensing system featuring multiple signal amplification effects is developed through the combination of capacitors, enzyme biofuel cells, and nucleic acid amplification technology for the ultrasensitive and precise detection of acetamiprid. By employing graphdiyne as the substrate material, the enzyme loading capacity and electron transfer efficiency of the electrode are significantly enhanced. In the presence of acetamiprid, the cascade signal amplification of catalytic hairpin assembly and hybridization chain reaction is triggered, which produces a good deal of long DNA duplex structure for embedding in [Ru(NH3)6]3+ signal receptors, thereby generating a remarkable electrochemical signal, meanwhile, the specific binding ability of the acetamiprid object to the aptamer ensures the high selectivity of the detection. Additionally, the utilization of an external capacitor further elevates the sensitivity of the sensor by 9.59 times. The sensor can detect acetamiprid in a linear range from 1 fg/L to 50 pg/L, with a detection limit of 0.25 fg/L (S/N = 3). The sensor shows great stability and selectivity, with no major interference from common pesticides even at 100-fold higher concentrations. When the sensor is applied to the detection of cucumber and tomato samples, the recovery rates range from 91.2 to 98.6 %, and its accuracy is verified by standard method. This study offers a reliable new approach for the ultrasensitive and reliable detection of acetamiprid in real samples. Predictably, such a multi-technology integration strategy can be extended to more application scenarios.

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