Electronic Tongue and Neural Networks, Biologically Inspired Systems Applied to Classifying Coffee Samples
Electronic Tongue and Neural Networks, Biologically Inspired Systems Applied to Classifying Coffee Samples作者机构：Grupo de Investigación DANM/Desarrollo y Aplicación de Nuevos Materiales Universidad Pontificia Bolivariana Montería Colombia Grupo de Investigación GIE Universidad Pontificia Bolivariana Montería Córdoba
出 版 物：《American Journal of Analytical Chemistry》 (美国分析化学（英文）)
年 卷 期：2014年第5卷第4期
页 面：266-274页
学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学]
主 题：Electronic Tongue Coffee Electrochemical Sensors
摘 要：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.
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