Haptens Optimization Using Molecular Modeling and Paper-Based Immunosensor for On-Site Detection of Carbendazim in Vegetable Products

利用分子建模和纸基免疫传感器优化半抗原,用于现场检测蔬菜产品中的多菌灵

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Abstract

Carbendazim is a benzimidazole fungicide widely used in the prevention and control of vegetable diseases. However, if misused, it may result in residues in agricultural products, not only reducing vegetable quality but also posing potential risks to human health. Currently, the on-site rapid detection technology for carbendazim still faces challenges, including insufficient antibody specificity and low sensitivity, which hinder its ability to meet practical regulatory requirements. Therefore, this study screened a rational hapten structure by applying a computer-aided hapten design and obtained a specific antibody. Compared to previous studies, the cross-reactivity rate of the antibody with thiabendazole-methyl was less than 0.1%, and the cross-reactivity rate with 2-aminobenzimidazole was 52.7% lower than that of the existing reported antibodies, which significantly improved the detection specificity of the method. Based on a high-specificity antibody, a gold nanoparticle-based lateral flow immunoassay (AuNPs-LFIA) for carbendazim was established. The detection limits of green beans and leeks are 3.80 μg/kg and 1.80 μg/kg, respectively, which still maintain high specificity in complex samples. Good agreement was also demonstrated between the results of blind samples detected by AuNPs-LFIA and LC-MS/MS, respectively. The establishment of AuNPs-LFIA provides an effective solution for the rapid and specific detection of carbendazim.

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