Jan 30, 2014 01:03 PM EST By Jaleesa Baulkman, UniversityHerald Reporter

Researchers have managed to create an electronic tongue that can distinguish between different varieties of beer, the oldest and most widely consumed alcoholic drink in the world.

Scientists at the Autonomous University of Barcelona have created an electronic tongue with 82 percent accuracy that can analyze several brands of beer.  The idea for the electronic organ is based on the human sense of taste, researchers said in a press release.

"The concept of the electronic tongue consists in using a generic array of sensors, in other words with generic response to the various chemical compounds involved, which generate a varied spectrum of information with advanced tools for processing, pattern recognition and even artificial neural networks," Manel del Valle, main author of the study, said in a statement.

The array of sensors in the electronic tongue was formed of 21 ion-selective electrodes, including some with response to ammonium, sodium, others with response to nitrate and chloride.

In their study, researchers recorded the multidimensional response generated by the array of sensors and how this was influenced by the type of beer considered. They found it to be 82 percent accurate, although it was not effective for classifying the beer.

"Using more powerful tools - supervised learning - and linear discriminant analysis did enable us to distinguish between the main categories of beer we studied: Schwarzbier, lager, double malt, Pilsen, Alsatian and low-alcohol, and with a success rate of 81.9 percent," Del Valle said.

Researchers also noted that the varieties of beers that the tongue is not trained to recognize, such as beer/soft drink mixes or foreign makes, were not identified, which means "the system does not recognize brands for which it was not trained."

The study concludes that these tools could be used to give robots a sense of taste, and even supplant panels of tasters in the food industry to improve the quality and reliability of products for consumption.

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