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Arrieta, A.A., Rodríguez Méndez, M.L., De Saja, J.A. and Blanco, C.A. (2010) Prediction of Bitterness and Alcoholic Strength in Beer Using an Electronic Tongue. Food Chemistry, 123, 642-646.
http://dx.doi.org/10.1016/j.foodchem.2010.05.006

has been cited by the following article:

• TITLE: Electronic Tongue and Neural Networks, Biologically Inspired Systems Applied to Classifying Coffee Samples

  AUTHORS: Álvaro A. Arrieta Almario, Rosa L. Tarazona Cáceres

  KEYWORDS: Electronic Tongue; Coffee; Electrochemical Sensors

  JOURNAL NAME: American Journal of Analytical Chemistry, Vol.5 No.4, March 21, 2014

  ABSTRACT: In this paper, the possibility to use an electronic tongue based on a polypyrrole sensor array in classifying coffee samples has been studied. Each sensor shows a distinguished electrochemical response when exposed to the studied solutions, providing signals with a high degree of cross-selectivity. The sensor array electrochemical response is related to the interaction of the ionic and non-ionic solution compounds and to the surface of the sensors polymeric matrix. Furthermore, the electronic tongue was used to perform an analysis on coffee samples. In this case, each sensor showed a particular response to each coffee sample. Data obtained from the registered signals were used to perform a discrimination of the samples. The analysis with neural networks of the principal components (NNPC) done on the electronic tongue response to five types of commercial coffee, allows to achieve a clear differentiation of samples.