Development of a bioelectronic tongue modified with gold nanoparticles for dairy analysis

Electronic tongues (ETs) have attracted considerable interest due to their capability to discriminate and analyse foods and beverages and to their potential to contribute to quality management. ETs are based on sensor arrays with low selectivity and high cross-selectivity combined with statistical tools that analyse the outputs from multiple sensors. Compared to other analytical methodologies, this type of device has interesting practical characteristics such as possible online application, no need for pretreatment of samples, and the capability to assess several chemical compounds in a single analysis. The aim of this work was to construct an all-solid-state potentiometric e-tongue with an array of sensors based on polymeric membranes, to be applied in the dairy industry.

In order to obtain an array of sensors with improved sensitivity, the membranes have been modified with gold nanoparticles. In addition, enzymes as galactose oxidase, urease and lactate dehydrogenase have been covalent bonded to the PVC surface to increase the selectivity of the sensor.

The responses of the sensors towards standard solutions indicate that sensors modified with gold nanoparticles and covalently associated enzymes showed a greater ability to differentiate between increasing concentrations of products of interest found in milk (urea, lactic acid, galactose, etc.) Moreover, the electronic tongue developed was able to perform the discrimination of milk with different nutritional characteristics using statistical analysis (PCA) showing as a result five differentiated groups, which were also ordered according to the fat content of the samples. In addition, the results of the study showed that the electronic tongue developed could be used as a prediction system for different chemical parameters, such as pH, acidity, protein or fat, of future milk samples by applying partial least squares analysis with regression coefficients above 0.90 for two variables in the parameters studied.