Voltammetric e-Tongue Based on a Single Sensor and Variable Selection for the Classification of Teas
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This work presents a simple and low-cost strategy to obtain voltammetric tongues by using a single voltammetric sensor aided by variable selection techniques. A usual electronic tongue consists of an array of physical sensors followed by data compression before pattern recognition modeling. Alternatively, a single voltammetric sensor can also act as an array of pseudo-sensors—applied potentials in a voltammogram—that can be properly selected to perform a given discrimination. The applicability of this strategy was evaluated in the discrimination of teas. Teas prepared for immediate intake (simulating a home-made tea cup) were analyzed with staircase voltammetry at an epoxy-graphite electrode. Voltammograms were submitted to variable selection previously to linear discriminant analysis (LDA) to identify the applied potentials that improve discrimination of teas according to variety, country of origin, and manufacturer. Successive projections algorithm (SPA), genetic algorithm (GA), and stepwise (SW) formulation were the variable selection techniques evaluated. Best results were achieved with SPA/LDA models, with correct classification rates for the prediction set close to 100%.
KeywordsTea Voltammetric electronic tongue Multivariate classification Successive projections algorithm
We are grateful to the Brazilian agency Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for financial support (research fellowship and scholarship). The authors would like to thank Dr. Marcelo Pistonesi from Universidad Nacional del Sur, Bahía Blanca, Argentina, for providing tea samples from Argentina, and Dr. Mário C. U. Araújo for providing tea samples from Brazil.
This study was funded by the National Institute of Advanced Analytical Science and Technology (INCTAA), CNPq grant number 573894/2008-6, FAPESP grant number 2008/57808-1, and CNPq grant number 300884/2009-5.
Compliance with Ethical Standards
Conflict of Interest
Author Dayvison R. Rodrigues declares that he has no conflict of interest. Author Diana S. M. de Oliveira declares that she has no conflict of interest. Author Marcio J. C. Pontes declares that he has no conflict of interest. Author Sherlan G. Lemos declares that he has no conflict of interest.
Informed consent is not applicable in this study.
This article does not contain any studies with human participants or animals performed by any of the authors.
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