Visual immunosensor assay with double T line for on-site sensitive fipronil pesticide detection in water, soil and honeysuckle.

J Hazard Mater

State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi, Jiangsu 214122, PR China; International Joint Research Laboratory for Biointerface and Biodetection, and School of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu 214122, PR China; Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, Wuxi, Jiangsu 214122, PR China. Electronic address:

Published: February 2025

Fipronil (FPN) is one of widely used pesticides in the fields of plants cultivation and animal husbandry, caused widespread pollution in multiple environmental media including water, soil, and plants, posing serious risks to ecological environment and human health. However, the complexity of environmental substrates and low pesticide content pose challenges for their detection. To overcome these challenges, the development of high specificity, convenient, and broad-applicability rapid detection methods is crucial. In this study, computer simulated semi-antigens and then novel FPN-immunogens were designed and synthesized by modifying carrier proteins to expose them to specific sites, so as to prepare monoclonal antibodies with high specificity and sensitivity to FPN. Afterwards, a sensitive and visual quantitative detection strip was developed based on a double T-linear AuNP-labeled immunosensor with a calculated limit of detection (cLOD) of 1.23 μg/kg in water, 6.46 μg/kg in soil and 13.7 μg/kg in honeysuckle, meanwhile the recoveries were in the range of 92.3∼108.5 %. Excellent stability and accuracy have been demonstrated by comparing the liquid chromatograph-tandem mass spectrometer methods. The proposed method can be widely applied for rapid screening and on-site quantitative analysis of FPN pesticide pollutants in various complex environmental scenarios.

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http://dx.doi.org/10.1016/j.jhazmat.2025.137634DOI Listing

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