Simultaneous determination of phenolic compounds by means of an automated voltammetric “electronic tongue”

Electronic tongue applications for wastewater and soil analysis

Assessment of water and soil quality is critical for the health, economy, and sustainability of any community. The release of a range of life-threatening pollutants from agriculture, industries, and the residential communities themselves into the different water resources and soil requires of analytical methods intended for their detection. Given the challenge that represents coping with the monitoring of such a diverse and large number of compounds (with over 100,000 chemicals registered, yet in continuous increase), holistic solutions such as electronic tongues (ETs) are emerging as a promising tool for a sustainable, simple, and green monitoring of soil and water resources. In this direction, this review aims to present and critically provide an overview of the basic concepts of ETs, followed by some relevant applications recently reported in the literature in environmental analysis, more specifically, the monitoring of water and wastewater, their quality and the detection of water pollutants as well as soil analysis.

A Voltammetric Electronic Tongue for the Resolution of Ternary Nitrophenol Mixtures

This work reports the applicability of a voltammetric sensor array able to quantify the content of 2,4-dinitrophenol, 4-nitrophenol, and picric acid in artificial samples using the electronic tongue (ET) principles. The ET is based on cyclic voltammetry signals, obtained from an array of metal disk electrodes and a graphite epoxy composite electrode, compressed using discrete wavelet transform with chemometric tools such as artificial neural networks (ANNs). ANNs were employed to build the quantitative prediction model. In this manner, a set of standards based on a full factorial design, ranging from 0 to 300 mg·L^-1, was prepared to build the model; afterward, the model was validated with a completely independent set of standards. The model successfully predicted the concentration of the three considered phenols with a normalized root mean square error of 0.030 and 0.076 for the training and test subsets, respectively, and r ≥ 0.948.

Diverse applications of electronic-nose technologies in agriculture and forestry

Electronic-nose (e-nose) instruments, derived from numerous types of aroma-sensor technologies, have been developed for a diversity of applications in the broad fields of agriculture and forestry. Recent advances in e-nose technologies within the plant sciences, including improvements in gas-sensor designs, innovations in data analysis and pattern-recognition algorithms, and progress in material science and systems integration methods, have led to significant benefits to both industries. Electronic noses have been used in a variety of commercial agricultural-related industries, including the agricultural sectors of agronomy, biochemical processing, botany, cell culture, plant cultivar selections, environmental monitoring, horticulture, pesticide detection, plant physiology and pathology. Applications in forestry include uses in chemotaxonomy, log tracking, wood and paper processing, forest management, forest health protection, and waste management. These aroma-detection applications have improved plant-based product attributes, quality, uniformity, and consistency in ways that have increased the efficiency and effectiveness of production and manufacturing processes. This paper provides a comprehensive review and summary of a broad range of electronic-nose technologies and applications, developed specifically for the agriculture and forestry industries over the past thirty years, which have offered solutions that have greatly improved worldwide agricultural and agroforestry production systems.

BioElectronic Tongue for the quantification of total polyphenol content in wine

This work reports the application of a BioElectronic Tongue (BioET) in the estimation of polyphenol content in wine. The approach used an array of enzyme biosensors capable of giving a wide and complete response of the analyzed species, plus a chemometric processing tool able to interpret the chemical signals and extract meaningful data from the complex readings. In our case, the proposed BioET was formed by an array of four voltammetric enzymatic biosensors based on epoxy-graphite composites, one blank electrode and the other three bulk-modified with tyrosinase and laccase on one side, and copper nanoparticles on the other; these modifiers were used in order to incorporate differentiated or catalytic response to different polyphenols present in wine and aimed to the determination of its total polyphenol content value. The obtained voltammetric responses were pre-processed employing the Fast Fourier Transform (FFT); this was used to compress the relevant information whereas the obtained coefficients fed an Artificial Neural Network (ANN) model that accomplished the quantification of total polyphenol content. For comparison purposes, obtained polyphenol content was compared against the one assessed by two different reference methods: Folin-Ciocalteu and UV polyphenol index (I(280)); good prediction ability was attained with correlation coefficients higher than 0.949 when comparing against reference methods. Qualitative discrimination of individual polyphenols found in wine was also assessed by means of Principal Component Analysis which allowed the discrimination of the individual polyphenols under study.

Sensor Arrays and Electronic Tongue Systems

This paper describes recent work performed with electronic tongue systems utilizing electrochemical sensors. The electronic tongues concept is a new trend in sensors that uses arrays of sensors together with chemometric tools to unravel the complex information generated. Initial contributions and also the most used variant employ conventional ion selective electrodes, in which it is named potentiometric electronic tongue. The second important variant is the one that employs voltammetry for its operation. As chemometric processing tool, the use of artificial neural networks as the preferred data processing variant will be described. The use of the sensor arrays inserted in flow injection or sequential injection systems will exemplify attempts made to automate the operation of electronic tongues. Significant use of biosensors, mainly enzyme-based, to form what is already named bioelectronic tongue will be also presented. Application examples will be illustrated with selected study cases from the Sensors and Biosensors Group at the Autonomous University of Barcelona.

Resolution of phenolic antioxidant mixtures employing a voltammetric bio-electronic tongue

This work reports the application of a Bio-Electronic Tongue (BioET) system made from an array of enzymatic biosensors in the analysis of polyphenols, focusing on major polyphenols found in wine. For this, the biosensor array was formed by a set of epoxy-graphite biosensors, bulk-modified with different redox enzymes (tyrosinase and laccase) and copper nanoparticles, aimed at the simultaneous determination of the different polyphenols. Departure information was the set of voltammograms generated with the biosensor array, selecting some characteristic features in order to reduce the data for the Artificial Neural Network (ANN). Finally, after the ANN model optimization, it was used for the resolution and quantification of each compound. Catechol, caffeic acid and catechin formed the three-analyte case study resolved in this work. Good prediction ability was attained, therefore allowing the separate quantification of the three phenols with predicted vs. expected slope better than 0.970 for the external test set (n = 10). Finally, BioET has been also tested with spiked wine samples with good recovery yields (values of 104%, 117% and 122% for catechol, caffeic acid and catechin, respectively).

Recent advances in electronic tongues

This minireview describes the main developments of electronic tongues (e-tongues) and taste sensors in recent years, with a summary of the principles of detection and materials used in the sensing units. E-tongues are sensor arrays capable of distinguishing very similar liquids employing the concept of global selectivity, where the difference in the electrical response of different materials serves as a fingerprint for the analysed sample. They have been widely used for the analysis of wines, fruit juices, coffee, milk and beverages, in addition to the detection of trace amounts of impurities or pollutants in waters. Among the various principles of detection, electrochemical measurements and impedance spectroscopy are the most prominent. With regard to the materials for the sensing units, in most cases use is made of ultrathin films produced in a layer-by-layer fashion to yield higher sensitivity with the advantage of control of the film molecular architecture. The concept of e-tongues has been extended to biosensing by using sensing units capable of molecular recognition, as in films with immobilized antigens or enzymes with specific recognition for clinical diagnosis. Because the identification of samples is basically a classification task, there has been a trend to use artificial intelligence and information visualization methods to enhance the performance of e-tongues.

State-of-the-art of (bio)chemical sensor developments in analytical Spanish groups

(Bio)chemical sensors are one of the most exciting fields in analytical chemistry today. The development of these analytical devices simplifies and miniaturizes the whole analytical process. Although the initial expectation of the massive incorporation of sensors in routine analytical work has been truncated to some extent, in many other cases analytical methods based on sensor technology have solved important analytical problems. Many research groups are working in this field world-wide, reporting interesting results so far. Modestly, Spanish researchers have contributed to these recent developments. In this review, we summarize the more representative achievements carried out for these groups. They cover a wide variety of sensors, including optical, electrochemical, piezoelectric or electro-mechanical devices, used for laboratory or field analyses. The capabilities to be used in different applied areas are also critically discussed.

Characterization of an ion-selective polypyrrole coating and application to the joint determination of potassium, sodium and ammonium by electrochemical impedance spectroscopy and partial least squares method

A stable immobilization of ionophores (INPHs) was achieved by selectively electropolymerizing overoxidized pyrrol on the working electrode surface. The optimal conditions found allowed the immobilization of a huge amount of INPH which remained its recognition properties. A single sensing chip, containing a generic INPH or an INPH mixture, was employed to the joint quantification of potassium, ammonium and sodium in fertilizer samples. Electrochemical impedance spectroscopy (EIS) and partial least square (PLS) regression were used to obtain and process the data, respectively. The sensing element (INPH) and the exposure time were optimized. The best results were obtained by using the dibenzo-18-crown-6 INPH after waiting for 60s, the time required to stabilize the impedimetric measurement. Taking into account that a single chip was employed, acceptable relative errors were obtained in the determination of potassium and ammonium (17% and 9%, respectively) in real fertilizer samples, also containing sodium. Although sodium concentration could not be estimated with precision, it had to be introduced into the calibration set data in order to model its interference with the other two ions.

Sensor arrays for liquid sensing--electronic tongue systems

Electronic tongue systems are multisensor devices dedicated to automatic analysis of complicated composition samples and to the recognition of their characteristic properties. Recently, the number of publications covering this topic has significantly increased. Many possible architectures of such devices were proposed: potentiometric, voltammetric, as well as approaches embracing mass- and optical-sensors. For the analysis of sensor array data, various pattern recognition systems were proposed. All of these topics are summarized in this review. Moreover, additional problems are considered: miniaturization of electronic tongues and hybrid systems for liquid sensing.

Electronic tongues in flow analysis

This review presents the evolution of recent flow-based analytical systems, characterized by the use of arrays of sensors as a detection scheme. For the proper processing of the complex responses generated, the systems require the use of advanced chemometric treatment, in which received the term "electronic tongue". Applications employing the flow injection analysis (FIA) and sequential injection analysis (SIA) are described. Chronologically, the progresses made by different research groups are shown, emphasizing their final applications in real problem solving.

Chemometric Study of Maya Blue from the Voltammetry of Microparticles Approach

The use of the voltammetry of microparticles at paraffin-impregnated graphite electrodes allows for the characterization of different types of Maya Blue (MB) used in wall paintings from different archaeological sites of Campeche and YucatAn (Mexico). Using voltammetric signals for electron-transfer processes involving palygorskite-associated indigo and quinone functionalities generated by scratching the graphite surface, voltammograms provide information on the composition and texture of MB samples. Application of hierarchical cluster analysis and other chemometric methods allows us to characterize samples from different archaeological sites and to distinguish between samples proceeding from different chronological periods. Comparison between microscopic, spectroscopic, and electrochemical examination of genuine MB samples and synthetic specimens indicated that the preparation procedure of the pigment evolved in time via successive steps anticipating modern synthetic procedures, namely, hybrid organic-inorganic synthesis, temperature control of chemical reactivity, and template-like synthesis.

Simultaneous amperometric determination of lignin peroxidase and manganese peroxidase activities in compost bioremediation using artificial neural networks

The activities of lignin-degrading peroxidases are the primary decomposition indexes in compost bioremediation. In this paper, artificial neural networks (ANNs) have been combined with an enzyme sensor for simultaneous determination of lignin peroxidase (LiP) and manganese peroxidase (MnP) activities secreted by Phanerochaete chrysosporium in composting of municipal solid waste. The LiP and MnP activities were detected through catalytic redox of H2O2, hydroquinone and veratryl alcohol as substrates by an amperometric sensor immersed in the culture filtrate solution. Due to the dynamic, nonlinear and uncertain characteristics of the complex composting system, ANNs have been used as a chemometric tool for overlapping signal deconvolution and modelling to quantify the two enzyme activities separately. Feedforward backpropagation network was used for the training process. The effects of the transfer functions, the amount of current values, the number of hidden neurons and the optimization algorithm were investigated. The LiP activities in the filtrate varied from 8.14 to 29.79 U L(-1), and from 0.36 to 1.37 U L(-1) for MnP activities. A good prediction capability was obtained, with correlation coefficients of 0.9936 for LiP activity and 0.9976 for MnP activity between the expected and predicted values of the external test samples. The performance of the ANN model was compared with the linear regression model in respect to simulation accuracy, adaptability to uncertainty, etc. All the results show that the combination of amperometric enzyme sensor and artificial neural networks is a rapid, sensitive and robust method in the quantitative study of composting system.