Electronic tongues artificial neural networks

Artificial neural networks (ANNs) have been widely applied in the electronic tongue literature both for classification and multivariate regression problems almost one-third of the papers on electronic tongues examined for this review show ANN applications (see Fig. 2.10). 

Chen et al. (2008) employed a commercial electronic tongue, based on an array of seven sensors, to classify 80 green tea samples on the basis of their taste grade, which is usually assessed by a panel test. PCA was employed as an explorative tool, while fc-NN and a back propagation artificial neural network (BP-ANN) were used for supervised classification. Both the techniques provide excellent results, achieving 100% prediction ability on a test set composed of 40 samples (one-half of the total number). In cases like this, when a simple technique, such as fc-NN, is able to supply excellent outcomes, the utilization of a complex technique, like BP-ANN, does not appear justified from a practical point of view. 

Moreno, L., Cartas, R., Merkogi, A., Alegret, S., Gutierrez, J.M., Leija, L., Hernandez, P.R., Munoz, R. Data Compression for a Voltammetric Electronic Tongue Modelled with Artificial Neural Networks. Anal. Lett. 38, 2189-2206 (2005)... 

Electronic noses and tongues are arrays of sensors used to characterize complex samples, with the former being arrays of gas sensors while the latter are composed of liquid sensors [1]. These devices are composed of a chemical sensing system and a pattern recognition (PR) system [usually an artificial neural network (ANN)]. The array sensing system allows different properties to be measured simultaneously [2], Each chemical, which reaches the sensor array, will produce a characteristic pattern and therefore a database of patterns will be built up for a series of chemicals [2],... 

Gutes et al. [113] have described an automated procedure based on voltammetric electronic tongue formed by a biosensor array for the determination of glucose in fruit juice samples. Linear sweep voltammetric signals were obtained with high selectivity and artificial neural networks were used as the modeling tool. 

Keywords Amperometry Artificial neural networks Biosensor arrays Electronic tongues Enzyme biosensors Potentiometry Voltammetry... 

Electronic tongue systems for remote environmental monitoring applications have been presented in several applications. A new approach in the chemical sensor field consists in the use of an array of nonspecific sensors coupled with a multivariate calibration tool which may form a node of a sensor network. The proposed arrays were made up of potentiometric sensors based on polymeric membranes, and the subsequent cross-response processing was based on a multilayer artificial neural network model as proposed by Mimendia et al. who described environmental monitoring of ammonium as a pollutant plus alkaline ions at different measuring sites in the states of Mexico and Hidalgo (Mexico), and monitoring of heavy metals (Cu ", Pb ", Zn ", and Cd " ) in open-air waste streams and rivers. 

An automated electronic tongue consisting of an array of potentiometric sensors and an artificial neural network (ANN) was developed to resolve mixtures of anionic surfactants. The sensor array was formed by five different flow-through sensors for anionic surfactants, based on polyvinyl chloride membranes having cross-sensitivity features. 

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