Science

Electronic tongue gets a taste for beer

Electronic tongue gets a taste for beer
An electronic tongue is able to distinguish between varieties of beer with a success rate of almost 82 percent (Photo: Shutterstock)
An electronic tongue is able to distinguish between varieties of beer with a success rate of almost 82 percent (Photo: Shutterstock)
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The 21 ion-selective electrodes that go into the electronic tongue (Photo: Manel Del Valle)
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The 21 ion-selective electrodes that go into the electronic tongue (Photo: Manel Del Valle)
An electronic tongue is able to distinguish between varieties of beer with a success rate of almost 82 percent (Photo: Shutterstock)
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An electronic tongue is able to distinguish between varieties of beer with a success rate of almost 82 percent (Photo: Shutterstock)

When we first covered the electronic tongue developed by a team led by Professor Manel Del Valle at Universitat Autònoma de Barcelona, it was enjoying a glass or two of cava wine. Now the researchers have turned to beer, and report that their electronic tongue can correctly identify different beer varieties with a success rate of almost 82 percent.

As its name suggests, the electronic tongue is based on the human sense of taste with an array of sensors serving as substitute taste buds. This sensor array is made up of 21 ion-selective electrodes, including some of which respond to ions with fewer electrons than protons known as cations (ammonium and sodium) and some of which respond to anions that have more electrons than protons (nitrate, chloride, etc.).

The 21 ion-selective electrodes that go into the electronic tongue (Photo: Manel Del Valle)
The 21 ion-selective electrodes that go into the electronic tongue (Photo: Manel Del Valle)

"The concept of the electronic tongue consists in using a generic array of sensors," says Del Valle, "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."

When put to the test, the electronic tongue was able to distinguish between the main categories of beer being studied with a success rate of 81.9 percent. These categories included Schwarzbier, lager, double malt, Pilsen, Alsatian and low-alcohol. Although the categorization followed the declared alcohol content of the beers, Del Valle points out that the sensors don't respond directly to the presence of ethanol, but only the ions present in the solution.

The researchers say the technology could be used to give robots a sense of taste and to improve the quality and reliability of food products by replacing food taster panels in the food industry.

The team's study appears in the journal Food Chemistry.

Source: Plataforma SINC

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