Abstract
This review covers electronic tongues based on amperometric sensors and applied in food analysis. A brief overview of the development of sensors is included and this is illustrated by descriptions of different types of amperometric sensors used in electronic tongues. Analysis of multivariate data is also an essential part of any electronic tongue. Pattern recognition techniques are described, with a particular emphasis to the most advanced methods, such as artificial neural network and genetic algorithms. Finally, uses of the electronic tongue in model analyses and in food, beverage and water monitoring applications are also discussed.
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