Ali Ramadan, Elfadil Hassabelrasoul, Sirag Nizar, Alshaman Reem, Albalawi Abdullah S, Albalawi Nwaeam, Albalawi Amjad, Alharbi Salma, Al-Anzi Alanoud, Alatawi Shatha, Alhuaiti Yusra, Aldwsari Nawaf, El-Wekil Mohamed M
Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Tabuk, 71491, Tabuk, Saudi Arabia.
Division of Microbiology, Immunology and Biotechnology, Department of Natural Products and Alternative Medicine, Faculty of Pharmacy, University of Tabuk, Tabuk, Saudi Arabia.
Mikrochim Acta. 2025 Jul 2;192(8):469. doi: 10.1007/s00604-025-07326-3.
Regulatory agencies have identified zineb (ZNB) as a potential health hazard due to its toxicological profile and environmental persistence. Therefore, establishing a highly selective and ultrasensitive method for ZNB detection is crucial for environmental monitoring, food safety assurance, and effective pesticide regulation enforcement. Herein, a selective electrochemical sensor was engineered based on a molecularly-imprinted polymer (MIP) film designed for targeted analyte recognition. The sensing platform integrates bimetallic cobalt-manganese metal-organic frameworks (CoMn-MOFs) with reduced graphene oxide (rGO) to enhance conductivity and surface activity. Initially, GO was synthesized and subsequently reduced to conductive rGO utilizing sodium borohydride via a modified Hummers' method, forming a high-conductivity matrix for efficient electron transfer. Second, CoMn-MOFs were incorporated to significantly enhance the active surface area and facilitate electron transfer. A selective MIP layer was formed on the electrode surface via electro-polymerization, enabling precise molecular recognition of ZNB. The resulting MIP/rGO/CoMn-MOFs-modified glassy carbon electrode (GCE) exhibited excellent analytical performance, including a broad linear range (0.01-200 nM), a low LOD (4.0 pM), and high selectivity against potential interferents. When applied to real food and water samples, the sensor achieved high accuracy, with recoveries ranging from 95.5% to 105.6% and RSDs between 1.87% and 4.00%. The method was validated using the standard addition technique, confirming its applicability for accurate ZNB quantification in complex food and water matrices. These findings validate the sensor's potential as a practical, rapid, and environmentally friendly platform for monitoring ZNB residues in agricultural and environmental contexts.
监管机构已将代森锌(ZNB)认定为一种潜在的健康危害,因其毒理学特性和环境持久性。因此,建立一种高选择性和超灵敏的ZNB检测方法对于环境监测、食品安全保障以及有效的农药监管执法至关重要。在此,基于用于目标分析物识别的分子印迹聚合物(MIP)膜设计了一种选择性电化学传感器。该传感平台将双金属钴 - 锰金属有机框架(CoMn - MOFs)与还原氧化石墨烯(rGO)相结合,以提高导电性和表面活性。首先,合成氧化石墨烯(GO),随后通过改良的Hummers方法利用硼氢化钠将其还原为导电的rGO,形成用于高效电子转移的高导电基质。其次,引入CoMn - MOFs以显著增加活性表面积并促进电子转移。通过电聚合在电极表面形成选择性MIP层,实现对ZNB的精确分子识别。所得的MIP/rGO/CoMn - MOFs修饰玻碳电极(GCE)表现出优异的分析性能,包括宽线性范围(0.01 - 200 nM)、低检测限(4.0 pM)以及对潜在干扰物的高选择性。当应用于实际食品和水样时,该传感器具有高准确度,回收率在95.5%至105.6%之间,相对标准偏差在1.87%至4.00%之间。该方法通过标准加入技术进行验证,证实了其在复杂食品和水基质中准确定量ZNB的适用性。这些发现验证了该传感器作为一种实用、快速且环保的平台在农业和环境背景下监测ZNB残留的潜力。