Glyphosate Detection by Means of a Voltammelric Electronic Tongue and Discrimination of Potential Interferents

A new electronic tongue to monitor the presence of glyphosate (a non-selective systemic herbicide) has been developed. It is based on pulse voltammetry and consists in an array of three working electrodes (Pt, Co and Cu) encapsulated on a methacrylate cylinder. The electrochemical response of the se...

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Veröffentlicht in:Sensors (Basel, Switzerland) Switzerland), 2012-12, Vol.12 (12), p.17553-17568
Hauptverfasser: Bataller, R, Campos, I, Laguarda-Miro, N, Alcaniz, M, Soto, J, Martinaz-Manez, R, Gil, L, Garcia-Braijo, E, Ibanoz-Civera, J
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Sprache:eng
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Zusammenfassung:A new electronic tongue to monitor the presence of glyphosate (a non-selective systemic herbicide) has been developed. It is based on pulse voltammetry and consists in an array of three working electrodes (Pt, Co and Cu) encapsulated on a methacrylate cylinder. The electrochemical response of the sensing array was characteristic of the presence of glyphosate in buffered water (phosphate buffer 0.1 mol times dm super(-3), pH 6.7). Rotating disc electrode (RDE) studies were carried out with Pt, Co and Cu electrodes in water at room temperature and at pH 6.7 using 0.1 mol times dm super(-3) of phosphate as a buffer. In the presence of glyphosate, the corrosion current of the Cu and Co electrodes increased significantly, probably due to the formation of Cu super(2+) or Co super(2+) complexes. The pulse array waveform for the voltammetric tongue was designed by taking into account some of the redox processes observed in the electrochemical studies. The PCA statistical analysis required four dimensions to explain 95% of variance. Moreover, a two-dimensional representation of the two principal components differentiated the water mixtures containing glyphosate. Furthermore, the PLS statistical analyses allowed the creation of a model to correlate the electrochemical response of the electrodes with glyphosate concentrations, even in the presence of potential interferents such as humic acids and Ca super(2+). The system offers a PLS prediction model for glyphosate detection with values of 098, -2.3 x 10 super(-5) and 0.94 for the slope, the intercept and the regression coefficient, respectively, which is in agreement with the good fit between the predicted and measured concentrations. The results suggest the feasibility of this system to help develop electronic tongues for glyphosate detection.
ISSN:1424-8220
1424-8220
DOI:10.3390/s121217553