Voltammetric e-tongue for the quantification of total polyphenol content in olive oils

Evaluation of Olive Oil Quality with Electrochemical Sensors and Biosensors: A Review

Electrochemical sensors, sensor arrays and biosensors, alongside chemometric instruments, have progressed remarkably of late, being used on a wide scale in the qualitative and quantitative evaluation of olive oil. Olive oil is a natural product of significant importance, since it is a rich source of bioactive compounds with nutritional and therapeutic properties, and its quality is important both for consumers and for distributors. This review aims at analysing the progress reported in the literature regarding the use of devices based on electrochemical (bio)sensors to evaluate the bioactive compounds in olive oil. The main advantages and limitations of these approaches on construction technique, analysed compounds, calculus models, as well as results obtained, are discussed in view of estimation of future progress related to achieving a portable, practical and rapid miniature device for analysing the quality of virgin olive oil (VOO) at different stages in the manufacturing process.

Continuous monitoring of propofol in human serum with fouling compensation by support vector classifier

We present a new method for electrochemical sensing, which compensates the fouling effect of propofol through machine learning (ML) model. Direct and continuous monitoring of propofol is crucial in the development of automatic systems for control of drug infusion in anaesthesiology. The fouling effect on electrodes discourages the possibility of continuous online monitoring of propofol since polymerization of the surface produces sensor drift. Several approaches have been proposed to limit the phenomenon at the biochemical interface; instead, here, we present a novel ML-based calibration procedure. In this paper, we analyse a dataset of 600 samples acquired through staircase cyclic voltammetry (SCV), resembling the scenario of continuous monitoring of propofol, both in PBS and in undiluted human serum, to demonstrate that ML-based model solves electrode fouling of anaesthetics. The proposed calibration approach is based on Gaussian radial basis function support vector classifier (RBF-SVC) that achieves classification accuracy of 98.9% in PBS, and 100% in undiluted human serum. The results prove the ability of the ML-based model to correctly classify propofol concentration in the therapeutic range between 1μM and 60μM with levels of 10μM, continuously up to ten minutes, with one sample every 30s.

Electrochemical Sensors Coupled with Multivariate Statistical Analysis as Screening Tools for Wine Authentication Issues: A Review

Consumers are increasingly interested in the characteristics of the products they consume, including aroma, taste, and appearance, and hence, scientific research was conducted in order to develop electronic senses devices that mimic the human senses. Thanks to the utilization of electroanalytical techniques that used various sensors modified with different electroactive materials coupled with pattern recognition methods, artificial senses such as electronic tongues (ETs) are widely applied in food analysis for quality and authenticity approaches. This paper summarizes the applications of electrochemical sensors (voltammetric, amperometric, and potentiometric) coupled with unsupervised and supervised pattern recognition methods (principal components analysis (PCA), linear discriminant analysis (LDA), partial least square (PLS) regression, artificial neural network (ANN)) for wine authenticity assessments including the discrimination of varietal and geographical origins, monitoring the ageing processes, vintage year discrimination, and detection of frauds and adulterations. Different wine electrochemical authentication methodologies covering the electrochemical techniques, electrodes types, functionalization sensitive materials and multivariate statistical analysis are emphasized and the main advantages and disadvantages of using the proposed methodologies for real applications were concluded.

Voltammetric Electronic Tongues in Food Analysis

A critical revision is made on recent applications of voltammetric electronic tongues in the field of food analysis. Relevant works are discussed dealing with the discrimination of food samples of different type, origin, age and quality and with the prediction of the concentration of key substances and significant indexes related to food quality.

Application of an electronic tongue as a single-run tool for olive oils' physicochemical and sensory simultaneous assessment

Olive oil is highly appreciated due to its nutritional and organoleptic characteristics. However, a huge compositional variation is observed between olive oils, requiring the use of diverse analytical techniques for its classification including titration, spectrophotometry and chromatography, as well as sensory analysis. Chemical analysis is usually time-consuming, expensive and require skilled technicians, while the sensorial ones are dependent upon individual subjective evaluations, even if performed by trained panellists. This work evaluated and demonstrated the feasibility of using a potentiometric electronic tongue, comprising non-specific lipid polymeric and cross-sensitive sensor membranes, coupled with chemometric tools based on different sub-sets of sensors (from 11 to 14 sensors), to predict key quality parameters of olive oils based on single-run assays. The multivariate linear models established for 23 centenarian olive trees from different cultivars allowed predicting peroxide value, oxidative stability, total phenols and tocopherols contents, CIELAB scale parameters (L*, a* and b* values), as well as 11 gustatory-retronasal positive attributes (green, sweet, bitter, pungent, tomato and tomato leaves, apple, banana, cabbage, fresh herbs and dry fruits) with satisfactory accuracy (0.90 ± 0.07 ≤ R² ≤ 0.98 ± 0.02 for the repeated K-fold-CV procedure, which ensured that 25% of the data was used for internal-validation purposes). The electronic tongue device had an accuracy statistically similar to that achieved with standard analytical techniques, pointing out the versatility of the device for the fast and simultaneous chemical and sensory analysis of olive oil.

Oxidative Transformations of Lignans

Numerous oxidative transformations of lignan structures have been reported in the literature. In this paper we present an overview on the current findings in the field. The focus is put on transformations targeting a specific structure, a specific reaction, or an interconversion of the lignan skeleton. Oxidative transformations related to biosynthesis, antioxidant measurements, and total syntheses are mostly excluded. Non-metal mediated as well as metal mediated oxidations are reported, and mechanisms based on hydrogen abstractions, epoxidations, hydroxylations, and radical reactions are discussed for the transformation and interconversion of lignan structures. Enzymatic oxidations, photooxidation, and electrochemical oxidations are also briefly reported.

Electrochemical Sensor-Based Devices for Assessing Bioactive Compounds in Olive Oils: A Brief Review

Electrochemical bioinspired sensor devices combined with chemometric tools have experienced great advances in the last years, being extensively used for food qualitative and quantitative evaluation, namely for olive oil analysis. Olive oil plays a key role in the Mediterranean diet, possessing unique and recognized nutritional and health properties as well as highly appreciated organoleptic characteristics. These positive attributes are mainly due to olive oil richness in bioactive compounds such as phenolic compounds. In addition, these compounds enhance their overall sensory quality, being mainly responsible for the usual olive oil pungency and bitterness. This review aims to compile and discuss the main research advances reported in the literature regarding the use of electrochemical sensor based-devices for assessing bioactive compounds in olive oil. The main advantages and limitations of these fast, accurate, bioinspired voltammetric, potentiometric and/or amperometric sensor green-approaches will be addressed, aiming to establish the future challenges for becoming a practical quality analytical tool for industrial and commercial applications.

E-nose, e-tongue and e-eye for edible olive oil characterization and shelf life assessment: A powerful data fusion approach

The aim of this work was to investigate the applicability of e-senses (electronic nose, electronic tongue and electronic eye) for the characterization of edible olive oils (extra virgin, olive and pomace) and for the assessment of extra virgin olive oil and olive oil quality decay during storage at different temperatures. In order to obtain a complete description of oil samples, physico-chemical analyses on quality and nutritional parameters were also performed. Data were processed by PCA and a targeted data processing flow-sheet has been applied to physico-chemical and e-senses dataset starting from data pre-processing introducing an innovative normalization method, called t0 centering. On e-senses data a powerful mid-level data fusion approach has been employed to extract relevant information from different analytical sources combining their individual contributions. On physico-chemical data, an alternative approach for grouping extra virgin olive oil and olive oil samples on the basis of their freshness was applied and two classes were identified: fresh and oxidized. A k-NN classification rule was developed to test the performance of e-senses to classify samples in the two classes of freshness and the average value of correctly classified samples was 94%. Results demonstrated that the combined application of e-senses and the innovative data processing strategy allows to characterize edible olive oils of different categories on the basis of their sensorial properties and also to follow the evolution during storage of extra-virgin olive oil and olive oil sensorial properties thus assessing the quality decay of oils.

Olive Oil Total Phenolic Contents and Sensory Sensations Trends during Oven and Microwave Heating Processes and Their Discrimination Using an Electronic Tongue

Olive oil has unique organoleptic attributes and its consumption is associated with nutritional and health benefits, which are mainly related to its rich composition in phenolic and volatile compounds. The use of olive oil in heat-induced cooking leads to deep reduction of phenolic and volatile concentrations and to changes of the sensory profiles. This work confirmed that oven and microwave heating significantly reduced total phenolic contents (P value < 0.0001, one-way ANOVA), more pronounced in the latter, together with a significant reduction of the intensity of fruity, sweet, bitter, pungent, and green attributes (P value < 0.0001, Kruskal-Wallis test), particularly for fruity and green sensations. Besides, bitter, fruity, green, and pungent intensities showed a linear dependency with the total phenolic contents (0.8075≤R-Pearson ≤ 0.9694). Finally, the potentiometric electronic tongue together with linear discriminant analysis-simulated annealing algorithm allowed satisfactory discrimination (sensitivities of 94±4%, for repeated K-fold cross-validation) of olive oils subjected to intense microwave heating (5–10 min, 160–205°C) from those processed under usual cooking conditions (oven heating during 15–60 min or microwave heating during 1.5–3 min, 72–165°C). This could be due to the different responses of the electronic tongue towards olive oils with diverse phenolic and sensory profiles.

Distinguishment, identification and aroma compound quantification of Portuguese olive oils based on physicochemical attributes, HS-GC/MS analysis and voltammetric electronic tongue

BACKGROUND

In this paper, various extra-virgin and virgin olive oils samples from different Portuguese markets were studied. For this purpose, a voltammetric electronic tongue (VE-tongue), consisting of two kinds of working electrode within the array, together with physicochemical analysis and headspace gas chromatography coupled with mass spectrometry (HS-GC-MS), were applied. In addition, preliminary considerations of relationships between physicochemical parameters and multisensory system were reported.

RESULTS

The physicochemical parameters exhibit significant differences among the analyzed olive oil samples that define its qualities. Regarding the aroma profile, 14 volatile compounds were characterized using HS-GC-MS; among these, hex-2-enal, hexanal, acetic acid, hex-3-ene-1-ol acetate and hex-3-en-1-ol were semi-quantitatively detected as the main aroma compounds in the analyzed samples. Moreover, pattern recognition methods demonstrate the discrimination power of the proposed VE-tongue system. The results reveal the VE-tongue's ability to classify olive oil samples and to identify unknown samples based of built models. In addition, the correlation between VE-tongue and physicochemical analysis exhibits a remarkable prediction model aimed at anticipating carotenoid content.

CONCLUSION

The preliminary results of this investigation indicate that physicochemical and HS-GC-MS analysis, together with multisensory system coupled with chemometric techniques, presented a satisfactory performance regarding olive oil sample discrimination and identification. © 2017 Society of Chemical Industry.

Electronic Tongue-A Tool for All Tastes?

Electronic tongue systems are traditionally used to analyse: food products, water samples and taste masking technologies for pharmaceuticals. In principle, their applications are almost limitless, as they are able to almost completely reduce the impact of interferents and can be applied to distinguish samples of extreme complexity as for example broths from different stages of fermentation. Nevertheless, their applications outside the three principal sample types are, in comparison, rather scarce. In this review, we would like to take a closer look on what are real capabilities of electronic tongue systems, what can be achieved using mixed sensor arrays and by introduction of biosensors or molecularly imprinted polymers in the matrix. We will discuss future directions both in the sense of applications as well as system development in the ever-growing trend of low cost analysis.

Perception of olive oils sensory defects using a potentiometric taste device

The capability of perceiving olive oils sensory defects and intensities plays a key role on olive oils quality grade classification since olive oils can only be classified as extra-virgin if no defect can be perceived by a human trained sensory panel. Otherwise, olive oils may be classified as virgin or lampante depending on the median intensity of the defect predominantly perceived and on the physicochemical levels. However, sensory analysis is time-consuming and requires an official sensory panel, which can only evaluate a low number of samples per day. In this work, the potential use of an electronic tongue as a taste sensor device to identify the defect predominantly perceived in olive oils was evaluated. The potentiometric profiles recorded showed that intra- and inter-day signal drifts could be neglected (i.e., relative standard deviations lower than 25%), being not statistically significant the effect of the analysis day on the overall recorded E-tongue sensor fingerprints (P-value = 0.5715, for multivariate analysis of variance using Pillai's trace test), which significantly differ according to the olive oils' sensory defect (P-value = 0.0084, for multivariate analysis of variance using Pillai's trace test). Thus, a linear discriminant model based on 19 potentiometric signal sensors, selected by the simulated annealing algorithm, could be established to correctly predict the olive oil main sensory defect (fusty, rancid, wet-wood or winey-vinegary) with average sensitivity of 75 ± 3% and specificity of 73 ± 4% (repeated K-fold cross-validation variant: 4 folds×10 repeats). Similarly, a linear discriminant model, based on 24 selected sensors, correctly classified 92 ± 3% of the olive oils as virgin or lampante, being an average specificity of 93 ± 3% achieved. The overall satisfactory predictive performances strengthen the feasibility of the developed taste sensor device as a complementary methodology for olive oils' defects analysis and subsequent quality grade classification. Furthermore, the capability of identifying the type of sensory defect of an olive oil may allow establishing helpful insights regarding bad practices of olives or olive oils production, harvesting, transport and storage.

Prediction of wastewater quality using amperometric bioelectronic tongues

Wastewater samples from a Swedish chemi-thermo-mechanical pulp (CTMP) mill collected at different purification stages in a wastewater treatment plant (WWTP) were analyzed with an amperometric enzyme-based biosensor array in a flow-injection system. In order to resolve the complex composition of the wastewater, the array consists of several sensing elements which yield a multidimensional response. We used principal component analysis (PCA) to decompose the array's responses, and found that wastewater with different degrees of pollution can be differentiated. With the help of partial least squares regression (PLS-R), we could link the sensor responses to the Microtox® toxicity parameter, as well as to global organic pollution parameters (COD, BOD, and TOC). From investigating the influences of individual sensors in the array, it was found that the best models were in most cases obtained when all sensors in the array were included in the PLS-R model. We find that fast simultaneous determination of several global environmental parameters characterizing wastewaters is possible with this kind of biosensor array, in particular because of the link between the sensor responses and the biological effect onto the ecosystem into which the wastewater would be released. In conjunction with multivariate data analysis tools, there is strong potential to reduce the total time until a result is yielded from days to a few minutes.

Chemometric applications to assess quality and critical parameters of virgin and extra-virgin olive oil. A review

Today virgin and extra-virgin olive oil (VOO and EVOO) are food with a large number of analytical tests planned to ensure its quality and genuineness. Almost all official methods demand high use of reagents and manpower. Because of that, analytical development in this area is continuously evolving. Therefore, this review focuses on analytical methods for EVOO/VOO which use fast and smart approaches based on chemometric techniques in order to reduce time of analysis, reagent consumption, high cost equipment and manpower. Experimental approaches of chemometrics coupled with fast analytical techniques such as UV-Vis spectroscopy, fluorescence, vibrational spectroscopies (NIR, MIR and Raman fluorescence), NMR spectroscopy, and other more complex techniques like chromatography, calorimetry and electrochemical techniques applied to EVOO/VOO production and analysis have been discussed throughout this work. The advantages and drawbacks of this association have also been highlighted. Chemometrics has been evidenced as a powerful tool for the oil industry. In fact, it has been shown how chemometrics can be implemented all along the different steps of EVOO/VOO production: raw material input control, monitoring during process and quality control of final product.

SPR imaging based electronic tongue via landscape images for complex mixture analysis

Electronic noses/tongues (eN/eT) have emerged as promising alternatives for analysis of complex mixtures in the domain of food and beverage quality control. We have recently developed an electronic tongue by combining surface plasmon resonance imaging (SPRi) with an array of non-specific and cross-reactive receptors prepared by simply mixing two small molecules in varying and controlled proportions and allowing the mixtures to self-assemble on the SPRi prism surface. The obtained eT generated novel and unique 2D continuous evolution profiles (CEPs) and 3D continuous evolution landscapes (CELs) based on which the differentiation of complex mixtures such as red wine, beer and milk were successful. The preliminary experiments performed for monitoring the deterioration of UHT milk demonstrated its potential for quality control applications. Furthermore, the eT exhibited good repeatability and stability, capable of operating after a minimum storage period of 5 months.