Lenguas electrónicas para monitorizar el envejecimiento de la cerveza

Título: Monitoring the aging of beers using a bioelectronic tongue

Resumen :

This paper deals with the implementation and the application of a bioelectronic tongue including three enzymatic biosensors based on tyrosinase and phthalocyanines as electron mediators, to evaluate the changes that occur during the aging of beers. For this purpose, alcoholic and non alcoholic beers, packaged in can and bottle, have been analyzed using cyclic voltammetry. The electrochemical signals showed significant changes during the aging process. The features extracted from the cyclic voltammograms have been used to perform Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). Data have revealed a clear discrimination among the beer classes in the aging process and the results were confirmed by Probabilistic Neural Networks (PNN) with Radial Basis Functions (RBF) and FeedForward Networks with Backpropagation (BP) learning method. The bioelectronic tongue has demonstrated a good capability to discriminate and classify the beer types satisfactorily in such a way, for all beer treatments, full classification accuracy was found.

Autores : Ghasemi-Varnamkhasti, M.; Rodriguez-Mendez, M.L.; Mohtasebi, S.S.; Apetrei, C.; Lozano, J.; Ahmadi, H.; Razavi, S.H.; de Saja, J.A.

Direcciones :

1. Universidad de Teherán, Fac Agr Engn & Technol, Agr Machinery Engn (Iran)

2. Universidad de Valladolid, departamento de Química Inorgánica, ETS Ingenieros Ind, (España)

3. Dunarea de Jos Univ Galati, Fac Sci & Environm, Dept Chem Phys & Environm, Galati (Rumania)

4. Universidad de Extremadura, Grp Invest Sistemas Sensoriales (España)

5. Universidad de Teheran, Fac Agr Engn & Technol, Dept Food Sci & Engn (Iran)

6. Universidad de Valladolid, Fac Sci, Condensed Matter Phys Dept (España)