This paper presents a mini-electronic tongue that used a polymeric sensor array made from polypyrrole to discriminate between coffee samples of different geographical origin. The electronic tongue consisted of a system with a voltammetric sensor array coupled to a multichannel measuring device (multi-potentiostat) that was controlled by a multivariable data collection and processing application. The samples analyzed comprised two types: a series of substances with different chemical and taste properties and a group of samples of coffee of the Arabica variety harvested from different geographical areas of Colombia. The electronic tongue demonstrated the ability to discriminate between solutions with different gustatory properties. In the analysis of the coffee samples, each sensor showed a particular voltammetric response to each of the samples studied. A principal component analysis was undertaken, which resulted in clear discrimination between each of the coffee samples. It was concluded that the portable electronic tongue equipped with polymer sensors is able to discriminate between samples of coffee of different geographical origin.

Background. Coffee samples adulterated with roasted corn and roasted soybean were analyzed using a voltammetric electronic tongue equipped with a polypyrrole sensor array. Materials and methods. Coffee samples were adulterated in concentrations of 2%, 5%, 10% and 20% of roasted corn and roasted soybean; 5 replicates of each were used. The discrimination capacity of a voltammetric electronic tongue elaborated with a polypyrrole sensor array, was evaluated by principal component analysis and cluster analysis, while the capacity to perform quantitative determinations was carried out by partial least squares. Results. The results obtained by the application of principal component analysis showed an excellent ability to discriminate adulterated samples. Additionally, the classifications obtained by cluster analysis was concordant with those obtained by principal component analysis. On the other hand, the evaluation of the ability to quantitatively analyze the adulterated samples showed that the polypyrrole sensor array provides sufficient information to allow quantitative determinations by partial least squares regression. Conclusion. It could be concluded that the voltammetric electronic tongue used in this work allows the sufficient analysis of coffee samples adulterated with roasted corn and roasted soybean.

One of the methods to reduce environmental impacts is to use renewable resources such as biomass or even waste. In this work, a novel power generation system in biomass-powered steam cycles was proposed, comprising biomass gasification, a steam turbine, a pump and a condenser. A biomass feedstock (rice husk) was used in the gasifier as input fuel. The devised system was analyzed taking into account the sustainability evaluation that includes thermodynamic and environmental parameters. An energetic, exergetic and exergoecological analysis was carried out. In addition, a detailed sensitivity analysis was performed to assess the effects of varying operating parameters on system efficiency. According to the results, the energy and exergetic efficiencies of the system had a value of 23,680% and 12,830%, respectively, where the boiler and the turbine presented the highest average environmental impact per input and output exergy. The components with the highest environmental impact index associated with exergy destruction were the condenser and the boiler, representing 99,82%, demonstrating profit margins in the formation of pollutants and exergy destruction. The entire system had a total ecological impact of 2,614 mPt/s and can be reduced mainly by improving its exergetic efficiency. Exergoecological assessments can be used to support power generation in complex cycles, especially to reduce the generation of environmental pollution.

Abstract. The aim of this work was to evaluate a smart electronic tongue device as an alternative for qualitative and quantitative monitoring of drinking water. The smart electronic tongue consisted of a voltametric polypyrrole sensor array, linked with a multi-channel electronic system (multipotentiostat) based on PSoC (programable system on chip) technology controlled by a smartphone with a data acquisition and control app. This device was used in the monitoring of drinking water from the Sincelejo city water supply system; also, water samples collected and analyzed by the public health agency were used. The voltammetric measurements carried out with the smart electronic tongue showed cross-sensitivity of the polypyrrole sensor array, which allowed the discrimination of the samples through of principal component analysis by artificial neural networks. In addition, the voltammetric signals registered with the smart electronic tongue allowed, through partial least square (PLS) by artificial neural networks analysis, estimating the concentrations of some important analytes in the evaluation of the physicochemical quality of drinking water with R2 values higher than 0.70. The results allowed to conclude that the smart electronic tongue can be a valuable analytical tool that allows, in a single measure, to perform qualitative and quantitative chemical analysis (alkalinity, calcium, residual chlorine, chlorides, total hardness, phosphates, magnesium, and sulfates), it is also a fast, portable method that can complement traditional analyzes.