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Biomimetic Electrochemical Sensor Based on Molecularly Imprinted Polymer for Dicloran Pesticide Determination in Biological and Environmental Samples Publisher



Khadem M1 ; Faridbod F2 ; Norouzi P2 ; Foroushani AR3 ; Ganjali MR2 ; Shahtaheri SJ4
Authors
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Authors Affiliations
  1. 1. Department of Occupational Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  2. 2. Center of Excellence in Electrochemistry, Faculty of Chemistry, University of Tehran, Tehran, Iran
  3. 3. Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  4. 4. Department of Occupational Health Engineering, School of Public Health, Institute for Environmental Research, Tehran University of Medical Sciences, Tehran, Iran

Source: Journal of the Iranian Chemical Society Published:2016


Abstract

Dicloran pesticide is used to inhibit the fungal spore germination for different crops. Because of the increasing application of pesticides, reliable and accurate analytical methods are necessary. The aim of this work is designing the highly selective sensor to determine the dicloran in biological and environmental samples. Multi-walls carbon nanotubes and a molecularly imprinted polymer (MIP) were used as modifiers in the sensor composition. A dicloran MIP and a nonimprinted polymer (NIP) were synthesized and applied in the carbon paste electrode. After the optimization of electrode composition, it was used to determine the concentration of analyte. Parameters affecting the sensor response were optimized, such as sample pH, electrolyte concentration and its pH, and the instrumental parameters of square wave voltammetry. The MIP-CP electrode showed very high recognition ability in comparison with NIP-CP. The obtained linear range was 1 × 10−6 to 1 × 10−9 mol L−1. The detection limit was 4.8 × 10−10 mol L−1. This sensor was used to determine the dicloran in real samples (human urine, tap and river water samples) without special sample preparation before analysis. All important parameters were optimized, improving the sensor response considerably. © 2016, Iranian Chemical Society.