Simultaneous Detection of Carbendazim and Carbaryl Pesticides on Graphene-Biochar Electrodes Using Response Surface Optimization
Authors: Sussuchi Eliana Midori , SantAnna Mércia V. S. , Carvalho Sanny W. M. M. , Carregosa Ingred S. C. , Santos Ewerton 
Published: February 2020

The development of modified electrodes with biochar and reduced graphene oxide (rGO) is promising for the environmental monitoring of pesticides. The synergistic combination of the composite material is based on its textural properties and electronic conductivity [1-2]. In this work, carbon paste electrodes modified with rGO and biochar produced from biomass Eichhornia crassipes at 400 ° C (EPCM/rGO-BIO400) were used. The electrodes were sensitive to the detection of carbendazim (CBZ) and carbaryl (CBR) pesticides. The optimizations of the electrochemical parameters involved univariate and multivariate conditions. The optimizations were univariate for the following variables: support electrolyte (phosphate buffer), pH 4.0 and amount of modification (27%). For the determination of these conditions, the highest intensities of anodic peak currents were considered. Multivariate analysis planning was applied to optimize the accumulation time and the scan rate. In total, 11 experiments comprising of 4 factorial points, 4 axial points and 3 central points were evaluated. They were conducted in a random order in case of any system error [3]. The evaluated factors were accumulation time (AT: from 26 to 874 µA) and scan rate (SR: from 20 to 44 mV s-1). Both designs were perform at fixed level of CBZ and CBR, 8.0 x 10-6 and 1.0 x 10-4 mol L-1, respectively. Based on the experiments results, the corresponding quadratic polynomial was obtained: Y(RMF) = 1.530 + 0.335AT – 0.185AT2 + 0.156SR

The quadratic coefficient for SR and linear interaction were not included due to their effects were smaller than principal factor ones. Significant adequacy of the model was confirmed at the p<0.05 level of probability with the R2 (0.95028) and Radj (0.92897). In additional, F-test and p-value were applied to obtain a significant fitted model and not significant lack of fit. Figure 1 show response surface plot of RMF response to CBZ and CBR in function of evaluated factors. The higher response was obtained using 722 s and 44 mV s-1. Thus, the optimization of all the parameters favored the intensity and resolution of the analytical signal. The method presented a linear behavior in the of 2.0 x 10-7 to 2.7 x 10-6 mol L-1 range for CBZ (R2 = 0.998), and a linear behavior in the of 2.0 x 10-5 to 7.0 x 10-5 mol L-1 range for CBR (R2 = 0.934), sensitivity (LOD = 1.5 x 10-7 mol L-1 and LOQ = 4.5 x 10-7 mol L-1 for CBZ; LOD = 9.4 x 10-6
mol L-1 and LOQ = 2.9 x 10-5 mol L-1 for CBR) (Figure 2). Afterwards, the constructed method will be applied for the determination of CBZ and CBR in real sample.

Acknowledgements: FAPITEC, CNPq, CAPES, Corrosion and Nanotechnology Laboratory – NUPEG and CLQM (Center of Chemistry Laboratories Multi-users) from Federal University of Sergipe for the analysis support.

[1] Y. Zhang, B. Cao, L. Zhao, L. Sun, Y. Gao, J. Li, F. Yang, Appl.
Surf. Sci. 427 (2018) 147-155.

[2] C. Kalinke, A. S. Mangrich, L. H. Marcolino-Junior, M. F. Bergamini, Electroanalysis. 28 (2016) 764–769.

[3] L. A. Portugal, H. S. Ferreira, W. N. L. Santos, S. L. C. Ferreira, Microchem. J. 87 (2007) 77-80.

Figure 1