A novel application of cellobiose dehydrogenase (CDH) as sensing element for a Bioelectronic Tongue (BioET) system has been tested. In this work CDHs from various fungi, which exhibit different substrate specificities, were used to discriminate between lactose and glucose in presence of the interfering matrix compound Ca(2+) in various mixtures. This work exploits the advantage of an electronic tongue system with practically zero pre-treatment of samples and operation at low voltages in a direct electron transfer mode. The Artificial Neural Network (ANN) used in the BioET system to interpret the voltammetric data was able to provide a correct prediction of the concentrations of the analytes considered. Correlation coefficients in the comparison of obtained vs. expected concentrations were highly significant, especially for lactose (R(2)=0.975) and Ca(2+) (R(2)=0.945). This BioET application has a high potential especially for the food and dairy industry and also, if further miniaturised in screen printed format, for its in-situ use.

Second generation ethanol is produced from the carbohydrates released from the cell wall of bagasse and straw of sugarcane. The objective of this work is the characterization and application of a voltammetric electronic tongue using an array of

A facile and quick synthesis of palladium decorated multi-walled carbon nanotubes is presented in this work. The developed protocol allowed a quasi-homogeneous distribution of the metal nanoparticles on the surface of the nanotubes, and a controlled size of the nanoparticles in a range between 3.5 and 4.5 nm. After the characterization of the hybrid nanocomposite a first attempt on a possible application was made. The preliminary test, an ink-like nanocomposite as a modifier on the surface of a carbon screen-printed electrode, was performed in order to detect L-Tyrosine. Preliminary results are promising. A catalytic effect on the oxidation peak of the L-Tyrosine was shown and furthermore a low limit of detection, 1.46 x 10(-10) M, was reached.

This work reports the characterization and application of a voltammetric electronic tongue using an array of glassy carbon electrodes modified with multi‐walled carbon nanotubes containing metal (Pd, Au, Cu) and oxy‐hydroxide nanoparticles (MetalsOOH of Ni, Co) towards the determination of total sugar content in products related with sugarcane‐bioethanol production. The prediction model based on Artificial Neural Networks (ANN) has given satisfactory results for the carbohydrate sum and the obtained response had shown an adequate accuracy. Voltammetric data was first adapted for the computation using the Fast Fourier transform, and results from the electronic tongue approach were compared with use of different electrodes alone. Final performance was better using uniquely the Ni oxy‐hydroxide modified electrode, especially in the quantification of ethanol, a side‐effect of counter‐balancing its interference.