Development of Analytical Methods with multivariate calibration tools for determination of Neonicotinoids in honey

VIGNATI, MACARENA; MORESSI, MARCELA B; ROBLEDO, SEBASTIAN; MARIOLI, JUAN MIGUEL; D'ERAMO, FABIANA*

Foz do Iguazú

Congreso; 7to Congreso Latinoamericano de pesticidas; 2019

Neonicotinoids are a new class of insecticides with widespread use in veterinary medicine and crop production1. In Argentina, more than a dozen neonicotinoid active principles have been approved. Among them, the best known for their high toxicity are imidacloprid (IM) and thiamethoxam (TM).The impact of residues of neonicotinoids on the environment and its effect on human health has caused widespread attention. On the other hand, these pesticides have been implicated in the decline of honeybees? populations2. Therefore, rapid and sensitive determination of these insecticides in matrix like honey is significantly critical for both human health and environmental pollution.The main purpose of this work is to develop a sensitive and low-cost electrochemical method for the determination of IM and TM in honey samples, employing square wave voltammetry and chemometrics tools such as nonlinear multivariate calibration method3.For this purpose, a glassy carbon was used as working electrode, a silver wire as reference electrode and a platinum sheet as counter electrode, a phosphate buffer solutions were employed as a supporting electrolyte. Standard solutions for the quantitative studies were prepared by mixing aliquots of different concentrations of IM and TM in buffer solution. A set of five binary mixtures of different concentrations was prepared in honey with the purpose of evaluating the matrix effect on the proposed method. To adjust the pH of the sample solution, all samples were diluted 10% with buffer solution. The operating conditions and influencing parameters (involving several chemical and instrumental parameters) were first optimized by cyclic voltammetry. Thus, the effects of the scan rate, pH of the supporting electrolyte and analyte concentration on the electrochemical response of the above mentioned pesticides were studied. A pH value of 7.0 was selected as the working pH. The results show that the electrochemical responses of the two compounds are very similar and that the voltammetric traces present a high degree of overlap under all the experimental conditions. Therefore, two chemometric tools were tested to obtain the multivariate calibration model. One method was the partial least squares regression (PLS-1), which as sumes a linear behaviour. The other non linear method was an artificial neural network (ANN). In this last case we used a supervised, feed-forward network with Levenberg ? Marquardt back propagation training. From the accuracies and precisions analysis between nominal and estimated concentrations calculated by using both methods, it was inferred that the ANN method was a good model to quantify IM and TM in honey samples. The proposed method was applied for analysis of the IM and TM in honey samples. The results obtained indicate satisfactory applicability of the proposed methods, which yielded good recoveries (90-110%). The analytical methodology was simple, fast and does not require pre-treatment of the sample.