A Multivariate Statistical Approach to Determine the Most Effective Factors for Biological Monitoring of Pesticides Using Voltammetric Sensors

  • Monire Khadem Department of Occupational Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  • Farnoush Faridbod Center of Excellence in Electrochemistry, School of Chemistry, College of Science, University of Tehran, Tehran, Iran
  • Abbas Rahimi Foroushani Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  • Parviz Norouzi Center of Excellence in Electrochemistry, School of Chemistry, College of Science, University of Tehran, Tehran, Iran
  • Mohammad Reza Ganjali Center of Excellence in Electrochemistry, School of Chemistry, College of Science, University of Tehran, Tehran, Iran
  • Seyed Jamaleddin Shahtaheri Mail Department of Occupational Health Engineering, School of Public Health, Institute for Environmental Research, Tehran University of Medical Sciences, Tehran, Iran
  • Rasoul Yarahmadi Department of Occupational Health Engineering, School of Public Health, Iran University of Medical Sciences, Tehran, Iran
Keywords:
Pesticides; Molecularly imprinted polymer; Voltammetric sensor; Carbon paste electrode; Biological monitoring, Experimental design

Abstract

Despite the wide use of pesticides, there are increasing concerns about their occupational and environmental adverse effects. Therefore, it is very important to develop reliable methods for pesticides detection, extraction, and quantification in different samples. This study was aimed to develop an electrochemical nano-composite sensor based on molecularly imprinted polymer (MIP) for selective determination of pesticides. After synthesizing the MIPs and non-imprinted polymers (NIPs) for diazinon and dicloran pesticides, they were applied in the composition of carbon paste electrode. A fractional 28 factorial design was used to evaluate the effects of variables on the sensor response using the square wave voltammetry (SWV).

Very high recognition abilities were achieved using MIP-CP electrodes compared to the NIP-CP ones. The linear ranges obtained for diazinon and dicloran were 5×10-10 to 1×10-6, 1×10-9 to 1×10-6 mol L-1, and detection limits were 2.7×10-10 and 4.1×10-10 mol L-1, respectively. Modified sensors provided the prominent selectivity and sensitivity for quantification of pesticides in urine and water real samples, under optimized conditions. No special sample pre-treatment was required prior to the analysis. The experimental design verified the existence of interaction between factors. The variables including square wave frequency, square wave amplitude, and deposition potential indicated more significant effects on the sensor response than the other factors. In conclusion, besides the main effects, evaluation of the interaction between the variables is very important to look for the optimum conditions for pesticides analysis by voltammetric sensors.

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Published
2020-08-11
How to Cite
1.
Khadem M, Faridbod F, Rahimi Foroushani A, Norouzi P, Ganjali MR, Shahtaheri SJ, Yarahmadi R. A Multivariate Statistical Approach to Determine the Most Effective Factors for Biological Monitoring of Pesticides Using Voltammetric Sensors. Int J Occup Hyg. 12(1).
Section
Original Article(s)