The device automatically produces classifications similar to those of a sommelier and can be useful in detecting defects during the elaboration of these wines.

Cava varies in type according to the amount of sugar added with the expedition liqueur after secondary fermentation (which produces carbonic gas). Therefore it is useful to know the exact amount of sugar added, since this is what determines the type of cava which will be produced. The resulting classifications are: Brut Nature (<3 g/L, no sugar added), Extra Brut (<6 g/L), Brut (<12 g/L), Extra Dry (12-17 g/L), Dry (17-35 g/L), Medium-Dry (33-50 g/L) and Sweet (>50 g/L).

In order to design the electronic tongue, researchers from the UAB Group of Sensors and Biosensors, led by professor Manel del Valle, identified different cava samples using voltammetric measurements. Thanks to a combination of chemical measurement systems and advanced mathematical procedures -- principal component analysis (PCA), discrete wavelet transform (DWT), and artificial neural network (ANN) -- researchers achieved to copy the human taste system and distinguish between different types of cava, thus obtaining a classification similar to that of a sommelier. Through the use of the second order standard addition method (SOSAM) it was possible to quantify the amount of sugar added in the cava production process, demonstrating the efficiency of these processing tools.

The electronic tongue currently can identify three types of cava: Brut, Brut Nature and Medium-Dry. However, with proper training it will be able to identify all types available on the market.

Researchers of the UAB Group of Sensors and Biosensors, considered one of the world's leading groups in its sector, has spent years working on the development of electronic tongues. It currently is working on perfecting the device through the incorporation of biosensors.

Electronic tongues are bio-inspired systems created with the aim of reproducing human perception senses. The device contains a sensor matrix (with differentiated, broad and complementary response) to obtain chemical information from samples as are obtained by the human senses. Next, the perception of taste is based on the generation of sensory patterns of the nerves activated by the brain and nerve print recognition; this last step is achieved with the use of computerised systems which interpret data obtained by the sensor matrix. As in biological mechanisms, a learning and training process is needed so that the electronic tongue can be capable of recognising the properties that must be identified.

Source: Science Daily