Pedot modified electrodes in amperometric sensing for analysis of red wine samples

Electrochemical sensors for fast classification of different Cannabis sativa L. samples according to total Δ9-tetrahydrocannabinol content

In this work, we investigated the ability of an electrochemical sensor to recognize Cannabis sativa L. samples with different total content of Δ9-tetrahydrocannabinol (Δ9-THC), determined by the levels of the psychoactive cannabinoid and of its biosynthetic precursor Δ9-tetrahydrocannabinolic acid (Δ9-THCA), using a multivariate approach. The voltammetric responses recorded with screen-printed electrodes modified with carbon black reflected the compositional differences from the different samples, in terms of cannabinoids of the vegetal material. PLS-DA models allowed for the correct classification of most C. sativa samples into the classes of legal and illegal samples according to total Δ9-THC content, based on threshold limits defined by the EU/US (0.3 % w/w) and Italian (0.6 % w/w) regulations. Satisfactory results were achieved in both cases, obtaining classification efficiency values in prediction of the external test set equal to 85 % and 100 % for the EU/US and Italian thresholds, respectively. The obtained results suggest the possibility to consider the proposed method as a starting point for the implementation of an automated device for rapid prescreening of total Δ9-THC content directly on site.

Comparative study of in-vitro autofluorescence of normal versus non-melanoma-skin-cancer cells at different excitation wavelengths

In this experimental study the autofluorescence of squamous carcinoma cells, stimulated by 6 different excitation wavelengths in the range 280-533 nm, has been compared with the autofluorescence of normal control keratinocytes. Skin cells were cultivated in vitro, to isolate their characteristic autofluorescence form the more complex one that would be originated by the complete skin tissue. Autofluorescence spectra in the visible range were complemented by absorption measurements. It was observed that the control cells showed characteristic emission (and absorption) structures due to typical endogenous chromophores [FAD and NAD(P)H, lipo-pigments, porphyrins], that were severely dumped in pathological cells. The autofluorescence spectra were then elaborated by multivariate analysis: after a first exploratory data analysis by means of Principal Component Analysis, the whole dataset was used to develop classification models using partial least squares-discriminant analysis, to differentiate between normal and pathological cells. This permitted us to identify the most suitable fluorescence spectral interval, in the 550-670 nm range, to discriminate between normal and pathological behavior, independently on the excitation wavelength.

E-Tongues/Noses Based on Conducting Polymers and Composite Materials: Expanding the Possibilities in Complex Analytical Sensing

Conducting polymers (CPs) are extensively studied due to their high versatility and electrical properties, as well as their high environmental stability. Based on the above, their applications as electronic devices are promoted and constitute an interesting matter of research. This review summarizes their application in common electronic devices and their implementation in electronic tongues and noses systems (E-tongues and E-noses, respectively). The monitoring of diverse factors with these devices by multivariate calibration methods for different applications is also included. Lastly, a critical discussion about the enclosed analytical potential of several conducting polymer-based devices in electronic systems reported in literature will be offered.

Simultaneous Detection of Glucose and Fructose in Synthetic Musts by Multivariate Analysis of Silica-Based Amperometric Sensor Signals

Silica-based electrodes which permanently include a graphite/Au nanoparticles composite were tested for non-enzymatic detection of glucose and fructose. The composite material showed an effective electrocatalytic activity, to achieve the oxidation of the two analytes at quite low potential values and with good linearity. Reduced surface passivation was observed even in presence of organic species normally constituting real samples. Electrochemical responses were systematically recorded in cyclic voltammetry and differential pulse voltammetry by analysing 99 solutions containing glucose and fructose at different concentration values. The analysed samples consisted both in glucose and fructose aqueous solutions at pH 12 and in solutions of synthetic musts of red grapes, to test the feasibility of the approach in a real frame. Multivariate exploratory analyses of the electrochemical signals were performed using the Principal Component Analysis (PCA). This gave evidence of the effectiveness of the chemometric approach to study the electrochemical sensor responses. Thanks to PCA, it was possible to highlight the different contributions of glucose and fructose to the voltammetric signal, allowing their selective determination.

Analysis of musts and wines by means of a bio-electronic tongue based on tyrosinase and glucose oxidase using polypyrrole/gold nanoparticles as the electron mediator

A bioelectronic tongue (bioET) based on combinations of enzymes (tyrosinase and glucose oxidase) and polypyrrole (Ppy) or polypyrrole/AuNP (Ppy/AuNP) composites was build up and applied to the analysis and discrimination of musts and wines. Voltammetric responses of the array of sensors demonstrated the effectiveness of polymers as electron mediators and the existence of favorable synergistic effects between Ppy and the AuNPs. Using Principal Component Analysis and Parallel Factor Analysis it was possible to discriminate musts according to the °Brix and TPI (Total Polyphenol Index), and wines according to the alcoholic degree and TPI. Partial Least Squares provided good correlations between the bioET output and traditional chemical parameters. Moreover, Support Vector Machines permitted to predict the TPI and the alcoholic degree of wines, from data provided by the bioET in the corresponding grapes. This result opens the possibility to predict wine characteristics from the beginning of the vinification process.

Prediction of parameters related to grape ripening by multivariate calibration of voltammetric signals acquired by an electronic tongue

An electronic tongue (ET) consisting of two voltammetric sensors, namely a poly-ethylendioxythiophene modified Pt electrode and a sonogel carbon electrode, has been developed aiming at monitoring grape ripening. To test the effectiveness of device and measurement procedures developed, samples of three varieties of grapes have been collected from veraison to harvest of the mature grape bunches. The derived musts have been then submitted to electrochemical investigation using Differential Pulse Voltammetry technique. At the same time, quantitative determination of specific analytical parameters for the evaluation of technological and phenolic maturity of each sample has been performed by means of conventional analytical techniques. After a preliminary inspection by principal component analysis, calibration models were calculated both by partial least squares (PLS) on the whole signals and by the interval partial least squares (iPLS) variable selection algorithm, in order to estimate physico-chemical parameters. Calibration models have been obtained both considering separately the signals of each sensor of the ET, and by proper fusion of the voltammetric data selected from the two sensors by iPLS. The latter procedure allowed us to check the possible complementarity of the information brought by the different electrodes. Good predictive models have been obtained for estimation of pH, total acidity, sugar content, and anthocyanins content. The application of the ET for fast evaluation of grape ripening and of most suitable harvesting time is proposed.

Determination of polyphenol content and colour index in wines through PEDOT-modified electrodes

Poly(3,4-ethylenedioxythiophene)-modified electrodes have been used for the estimation of the polyphenolic content and of the colour index of different samples of wines. Synthetic wine solutions, prepared with different amount of oenocyanins, have been analysed spectrophotometrically and electrochemically in order to find a correlation between the total polyphenolic content or colour index and the current peak. The regression curves obtained have been used as external calibration lines for the analysis of several commercial wines, ranging from white to dark red wines. In this way, a rapid estimation of the total polyphenolic content and of the colour index may be accomplished from a single voltammetric measurement. Furthermore, principal component analysis has also been used to evaluate the effect of total polyphenolic content and colour index on the whole voltammetric signals within a selected potential range, both for the synthetic solutions and for the commercial products. Graphical abstract Electrochemical sensors for the rapid determination of colour index and polyphenol content in wines.

Handling large datasets of hyperspectral images: reducing data size without loss of useful information

Hyperspectral Imaging (HSI) is gaining increasing interest in the field of analytical chemistry, since this fast and non-destructive technique allows one to easily acquire a large amount of spectral and spatial information on a wide number of samples in very short times. However, the large size of hyperspectral image data often limits the possible uses of this technique, due to the difficulty of evaluating many samples altogether, for example when one needs to consider a representative number of samples for the implementation of on-line applications. In order to solve this problem, we propose a novel chemometric strategy aimed to significantly reduce the dataset size, which allows to analyze in a completely automated way from tens up to hundreds of hyperspectral images altogether, without losing neither spectral nor spatial information. The approach essentially consists in compressing each hyperspectral image into a signal, named hyperspectrogram, which is created by combining several quantities obtained by applying PCA to each single hyperspectral image. Hyperspectrograms can then be used as a compact set of descriptors and subjected to blind analysis techniques. Moreover, a further improvement of both data compression and calibration/classification performances can be achieved by applying proper variable selection methods to the hyperspectrograms. A visual evaluation of the correctness of the choices made by the algorithm can be obtained by representing the selected features back into the original image domain. Likewise, the interpretation of the chemical information underlying the selected regions of the hyperspectrograms related to the loadings is enabled by projecting them in the original spectral domain. Examples of applications of the hyperspectrogram-based approach to hyperspectral images of food samples in the NIR range (1000-1700 nm) and in the vis-NIR range (400-1000 nm), facing a calibration and a defect detection issue respectively, demonstrate the effectiveness of the proposed approach.

Polythiophenes and polythiophene-based composites in amperometric sensing

This overview of polythiophene-based materials provides a critical examination of meaningful examples of applications of similar electrode materials in electroanalysis. The advantages arising from the use of polythiophene derivatives in such an applicative context is discussed by considering the organic conductive material as such, and as one of the components of hybrid materials. The rationale at the basis of the combination of two or even more individual components into a hybrid material is discussed with reference to the active electrode processes and the consequent possible improvements of the electroanalytical performance. In this respect, study cases are presented considering different analytes chosen among those that are most frequently reported within the classes of organics and inorganics. The use of a polythiophene matrix to stably fix biological elements at the electrode surface for the development of catalytic biosensors and genosensors is also discussed. Finally, a few possible lines along which the next research in the field could be fruitfully pursued are outlined. Furthermore, the work still to be done to exploit the possibilities offered by novel products of organic synthesis, even along paths already traced in other fields of electrochemistry, is discussed.

Electrochemical sensing of total antioxidant capacity and polyphenol content in wine samples using amperometry online-coupled with microdialysis

This work describes the method for total antioxidant capacity (TAC) and/or total content of phenolics (TCP) analysis in wines using microdialysis online-coupled with amperometric detection using a carbon microfiber working electrode. The system was tested on 10 selected wine samples, and the results were compared with total reactive antioxidant potential (TRAP), oxygen radical absorbance capacity (ORAC), and chemiluminescent determination of total antioxidant capacity (CL-TAC) methods using Trolox and catechin as standards. Microdialysis online-coupled with amperometric detection gives similar results to the widely used cyclic voltammetry methodology and closely correlates with ORAC and TRAP. The problem of electrode fouling is overcome by the introduction of an electrochemical cleaning step (1-2 min at the potential of 0 V vs Ag/AgCl). Such a procedure is sufficient to fully regenerate the electrode response for both red and white wine samples as well as catechin/Trolox standards. The appropriate size of microdialysis probes enables easy automation of the electrochemical TAC/TCP measurement using 96-well microtitration plates.

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).