Artificial tongue potentiometric sensors

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. 

E-tongues have reportedly been used to obtain data for sourness, bitterness, and astringency for foodstuffs such as beers, wines, and teas. This involved detecting sensory attributes of bitter, sweet, sour, fruity, caramel, artificial, burnt, intensity, and body using potentiometric/amperometric chemical sensors along with the same pattern recognition techniques described above for the e-nose technology. 

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