A Multi-Enzyme Cascade Response for the Colorimetric Recognition of Organophosphorus Pesticides Utilizing Core-Shell Pd@Pt Nanoparticles with High Peroxidase-like Activity

Author:

Majid Zainabu1,Zhang Qi1,Yang Zhansen1,Che Huilian12ORCID,Cheng Nan1ORCID

Affiliation:

1. Beijing Laboratory for Food Quality and Safety, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China

2. Key Laboratory of Precision Nutrition and Food Quality, Key Laboratory of Functional Dairy, Ministry of Education, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China

Abstract

In modern agricultural practices, organophosphorus pesticides or insecticides (OPs) are regularly used to restrain pests. Their limits are closely monitored since their residual hinders the capability of acetylcholinesterase (AChE) and brings out a threatening accumulation of the neurotransmitter acetylcholine (ACh), which affects human well-being. Therefore, spotting OPs in food and the environment is compulsory to prevent human health. Several techniques are available to identify OPs but encounter shortcomings like time-consuming, operating costs, and slow results achievement, which calls for further solutions. Herein, we present a rapid colorimetric sensor for quantifying OPs in foods using TMB as a substrate, a multi-enzyme cascade system, and the synergistic property of core-shell Palladinum@Platinum (Pd@Pt) nanoparticles. The multi-enzyme cascade response framework is a straightforward and effective strategy for OPs recognition and can resolve the previously mentioned concerns. Numerous OPs, including Carbofuran, Malathion, Parathion, Phoxim, Rojor, and Phosmet, were successfully quantified at different concentrations. The cascade method established using Pd@Pt had a simple and easy operation, a lower detection limit range of (1–2.5 ng/mL), and a short detection time of about 50 min. With an R2 value of over 0.93, OPs showed a linear range of 10–200 ng/mL, portraying its achievement in quantifying pesticide residue. Lastly, the approach was utilized in food samples and recovered more than 80% of the residual OPs.

Funder

Chinese Universities Scientific Fund

Young Elite Scientists Sponsorship Program by BAST

2115 Talent Development Program of China Agricultural University

Publisher

MDPI AG

Subject

Plant Science,Health Professions (miscellaneous),Health (social science),Microbiology,Food Science

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