Electrochemical Biosensors for the Detection of Carbendazim in Water Sources

作者
Hossein Khosropour,Mansoureh Keramat,Wanida Laiwattanapaisal
出处
期刊:Analysis & sensing [Wiley]
卷期号:6 (4)
标识
DOI:10.1002/anse.202500239
摘要

The industrialization of agriculture has led to a significant exploitation of pesticides and fungicides worldwide. Carbendazim (CBZ), one of the common fungicides used in farming, forestry, and aquaculture, has been criticized for causing environmental contamination, i.e., leaving behind persistent residues in the environment. The development of ultrasensitive technologies for CBZ detection is necessary to ensure food/drinking water safety and to comply with environmental requirements. Due to the high sensitivity, rapid response, simple instrumentation, and ease of operation, the development of electrochemical (bio)sensors for various molecular targets has become increasingly popular in the past two decades. Together with the use of low‐cost and portable carbon electrodes (e.g., glassy carbon, screen‐printed carbon) makes electrochemical biosensors ideal for on‐site and real‐time water quality monitoring. Direct electrochemical sensing of CBZ based on its oxidation redox current has been widely studied, with improved performance achieved by modifying electrodes. In the meantime, the discovery of highly specific CBZ aptamers (nucleic acid receptors) from in vitro selections enabled the development of electrochemical “aptasensors” with much improved sensitivity and selectivity. We have critically reviewed the recent developments in electrochemical CBZ sensing since 2021, aiming to connect material characteristics and detection techniques with sensing performance. We discussed direct electrochemical sensing mechanisms, followed by a classification of nanomaterial‐modified electrodes based on their dominant functional roles (e.g., conductivity enhancement, electrocatalysis, and adsorption). Finally, advanced molecular recognition‐based strategies, including MIP and aptamer‐based systems, were presented to highlight selectivity‐driven sensor design.
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