A Pencil-Drawn Electronic Tongue for Environmental Applications.

We report on the development of a simple and cost-effective potentiometric sensor array that is based on manual "drawing" on the polymeric support with the pencils composed of graphite and different types of zeolites. The sensor array demonstrates distinct sensitivity towards a variety of inorganic ions in aqueous media. This multisensor system has been successfully applied to quantitative analysis of 100 real-life surface waters sampled in Mahananda and Hooghly rivers in the West Bengal state (India). Partial least squares regression has been utilized to relate responses of the sensors to the values of different water quality parameters. It has been found that the developed sensor array, or electronic tongue, is capable of quantifying total hardness, total alkalinity, and calcium content in the samples, with the mean relative errors below 18%.

Plutonium (IV) Quantification in Technologically Relevant Media Using Potentiometric Sensor Array.

The quantification of plutonium in technological streams during spent nuclear fuel (SNF) reprocessing is an important practical task that has to be solved to ensure the safety of the process. Currently applied methods are tedious, time-consuming and can hardly be implemented in on-line mode. A fast and simple quantitative plutonium (IV) analysis using a potentiometric sensor array based on extracting agents is suggested in this study. The response of the set of specially designed PVC-plasticized membrane sensors can be related to plutonium content in solutions simulating real SNF-reprocessing media through multivariate regression modeling, providing 30% higher precision of plutonium quantification than optical spectroscopy.

Potentiometric E-Tongue System for Geosmin/Isoborneol Presence Monitoring in Drinkable Water.

A potentiometric E-tongue system based on low-selective polymeric membrane and chalcogenide-glass electrodes is employed to monitor the taste-and-odor-causing pollutants, geosmin (GE) and 2-methyl-isoborneol (MIB), in drinkable water. The developed approach may permit a low-cost monitoring of these compounds in concentrations near the odor threshold concentrations (OTCs) of 20 ng/L. The experiments demonstrate the success of the E-tongue in combination with partial least squares (PLS) regression technique for the GE/MIB concentration prediction, showing also the possibility to discriminate tap water samples containing these compounds at two concentration levels: the same OTC order from 20 to 100 ng/L and at higher concentrations from 0.25 to 10 mg/L by means of PLS-discriminant analysis (DA) method. Based on the results, developed multisensory system can be considered a promising easy-to-handle tool for express evaluation of GE/MIB species and to provide a timely detection of alarm situations in case of extreme pollution before the drinkable water is delivered to end users.

Real-Time Water Quality Monitoring with Chemical Sensors.

Water quality is one of the most critical indicators of environmental pollution and it affects all of us. Water contamination can be accidental or intentional and the consequences are drastic unless the appropriate measures are adopted on the spot. This review provides a critical assessment of the applicability of various technologies for real-time water quality monitoring, focusing on those that have been reportedly tested in real-life scenarios. Specifically, the performance of sensors based on molecularly imprinted polymers is evaluated in detail, also giving insights into their principle of operation, stability in real on-site applications and mass production options. Such characteristics as sensing range and limit of detection are given for the most promising systems, that were verified outside of laboratory conditions. Then, novel trends of using microwave spectroscopy and chemical materials integration for achieving a higher sensitivity to and selectivity of pollutants in water are described.

A Simple Procedure to Assess Limit of Detection for Multisensor Systems.

Currently, there are no established procedures for limit of detection (LOD) evaluation in multisensor system studies, which complicates their correct comparison with other analytical techniques and hinders further development of the method. In this study we propose a simple and visually comprehensible approach for LOD estimation in multisensor analysis. The suggested approach is based on the assessment of evolution of mean relative error values in calibration series with growing analyte concentration. The LOD value is estimated as the concentration starting from which MRE values become stable from sample to sample. This intuitive procedure was successfully tested with a variety of real data from potentiometric multisensor systems.

Electronic Tongues for Inedible Media.

"Electronic tongues", "taste sensors", and similar devices (further named as "multisensor systems", or MSS) have been studied and applied mostly for the analysis of edible analytes. This is not surprising, since the MSS development was sometimes inspired by the mainstream idea that they could substitute human gustatory tests. However, the basic principle behind multisensor systems-a combination of an array of cross-sensitive chemical sensors for liquid analysis and a machine learning engine for multivariate data processing-does not imply any limitations on the application of such systems for the analysis of inedible media. This review deals with the numerous MSS applications for the analysis of inedible analytes, among other things, for agricultural and medical purposes.

Rapid Evaluation of Integral Quality and Safety of Surface and Waste Waters by a Multisensor System (Electronic Tongue).

The paper describes a wide-range practical application of the potentiometric multisensor system (MS) (1) for integral safety evaluation of a variety of natural waters at multiple locations, under various climatic conditions and anthropogenic stress and (2) for close to real consistency evaluation of waste water purification processes at urban water treatment plants. In total, 25 natural surface water samples were collected around St. Petersburg (Russia), analyzed as is, and after ultrasonic treatment. Toxicity of the samples was evaluated using bioassay and MS. Relative errors of toxicity assessment with MS in these samples were below 20%. The system was also applied for fast determination of integral water quality using chemical oxygen demand (COD) values in 20 samples of water from river and ponds in Kolkata (India) and performed with an acceptable precision of 20% to 22% in this task. Furthermore, the MS was applied for fast simultaneous evaluation of COD, biochemical oxygen demand, inorganic phosphorous, ammonia, and nitrate nitrogen at two waste water treatment plants (over 320 samples). Reasonable precision (within 25%) of such analysis is acceptable for rapid water safety evaluation and enables fast control of the purification process. MS proved to be a practicable analytical instrument for various real-world tasks related to water safety monitoring.

Signal Smoothing with PLS Regression.

Smoothing of instrumental signals is an important prerequisite in data processing. Various smoothing methods were suggested through the last decades each having their own benefits and drawbacks. Most of the filtering methods are based on averaging in a certain window (e.g., Savitzky-Golay) or on frequency-domain representation (e.g., Fourier filtering). The present study introduces novel approach to signal filtering based on signal variance through PLS (projections on latent structures) regression. The influence of filtering parameters on the smoothed spectrum is explained and real world examples are shown.

Electronic Tongue for Brand Uniformity Control: A Case Study of Apulian Red Wines Recognition and Defects Evaluation †.

The potentiometric electronic tongue system has been tested as a potential analytical tool for brand uniformity control of monoculture Apulian red wines (Primitivo and Negroamaro). The sensor array was composed of eight porphyrin coatings obtained by electrochemical polymerization process and was employed for both wines discrimination and quantitative detection of wine defect compounds: "off-odour" 3-(methylthio)-propanol; isoamyl alcohol fusel oil; benzaldehyde (marker of the yeast activity) and acetic acid (marker of vinegar formation). PLS-DA applied to Electronic tongue output data has permitted a correct discrimination of more than 70% of analysed wines in respect to the original brand affiliation. Satisfactory PLS1 predictions were obtained in real wine samples; with R² = 0.989 for isoamyl alcohol and R² = 0.732 for acetic acid. Moreover; the possibility to distinguish wine samples on the base of permitted levels of fault compounds content was shown.

Microwave-Assisted Development of Orally Disintegrating Tablets by Direct Compression.

Orally disintegrating tablets (ODTs) are challenged by the need for simple technology to ensure good mechanical strength coupled with rapid disintegration. The objective of this work was to evaluate microwave-assisted development of ODTs based on simple direct compression tableting technology. Placebo ODTs comprising directly compressible mannitol and lactose as diluents, super disintegrants, and lubricants were prepared by direct compression followed by exposure to >97% relative humidity and then microwave irradiation for 5 min at 490 W. Placebo ODTs with hardness (>5 kg/cm2) and disintegration time (<60 s) were optimized. Palatable ODTs of Lamotrigine (LMG), which exhibited rapid dissolution of LMG, were then developed. The stability of LMG to microwave irradiation (MWI) was confirmed. Solubilization was achieved by complexation with beta-cyclodextrin (ß-CD). LMG ODTs with optimal hardness and disintegration time (DT) were optimized by a 23 factorial design using Design Expert software. Taste masking using sweeteners and flavors was confirmed using a potentiometric multisensor-based electronic tongue, coupled with principal component analysis. Placebo ODTs with crospovidone as a superdisintegrant revealed a significant increase in hardness from ∼3 to ∼5 kg/cm2 and a decrease in disintegration time (<60 s) following microwave irradiation. LMG ODTs had hardness >5 kg/cm2, DT < 30s, and rapid dissolution of LMG, and good stability was optimized by DOE and the design space derived. While ß-CD complexation enabled rapid dissolution and moderate taste masking, palatability, which was achieved including flavors, was confirmed using an electronic tongue. A simple step of humidification enabled MWI-facilitated development of ODTs by direct compression presenting a practical and scalable advancement in ODT technology.

A sample-effective calibration design for multiple components.

The experimental design of mixtures for multivariate calibration is introduced. The idea of this design is based on uniform distribution of experimental points in a concentration hypercube. Unlike the already reported uniform designs this one is pretty simple and not computationally demanding. The suggested approach does not employ the concept of fixed "levels" and allows for designs with any number of experimental mixtures and any number of components depending on "time and money" considerations for each particular calibration experiment. The performance of the design is assessed with a UV-Vis spectroscopic experiment for simultaneous quantification of four inorganic components in complex mixtures. The performance of the PLS regression models derived from the design is compared with that of cyclic permutation and Kennard-Stone designs. The suggested approach allows for comparable or higher prediction accuracy with the lower number of experimental points.

Quantification of phosphatides in sunflower oils using a potentiometric e-tongue.

Consisting of two fatty acyl groups, phospholipids are a vital part of vegetable oils and the source of essential fatty acids. Moreover, phospholipids influence oxidative and flavor stability and color evolution of vegetable oils, and their quantification has a significant role in the quality assessment of oils. In this study, we proposed a new highly efficient, affordable, environmentally friendly, and simple approach for the evaluation of phospholipid concentrations based on potentiometric multisensor systems coupled with chemometric data processing. Support vector machines, partial least squares, and multiple linear regressions were used to predict phosphatide concentrations based on potentiometric multisensor system responses. Application of multivariate regression tools yielded the following root mean square errors of prediction: 0.005 mg/100 g of oil in the range 0.0-59.4 mg/100 g for refined oils; 0.008 mg/100 g in the range 0.0-100 mg/100 g for low phosphatide oils and 0.24 mg/100 g in the range 100-2270 mg/100 g for high phosphatide oils. This approach can be considered as a rapid and straightforward method to quantify the phosphatides in sunflower oils.

Development of QDs-based nanosensors for heavy metal detection: A review on transducer principles and in-situ detection.

Heavy metal pollution has severe threats to the ecological environment and human health. Thus, it is urgent to achieve the rapid, selective, sensitive and portable detection of heavy metal ions. To overcome the defects of traditional methods such as time-consuming, low sensitivity, high cost and complicated operation, QDs (Quantum dots)-based nanomaterials have been used in sensors to significantly improve the sensing performance. Due to their excellent physicochemical properties, high specific surface area, high adsorption and reactive capacity, nanomaterials could act as potential probes or offer enhanced sensitivity and create a promising nanosensors platform. In this review, the rapidly advancing types of QDs for heavy metal ions detection are first summarized. Modified with ligands, nanomaterials, or biomaterials, QDs are assembled on sensors by the interaction of electrostatic adsorption, chemical bonding, steric hindrance, and base-pairing. The stability of QDs-based nanosensors is improved by doping the elements to QDs, providing the reference substance, optimizing the assemble strategies and so on. Then, according to transducer principles, the two most typical sensor categories based on QDs: optical and electrochemical sensors are highlighted to be discussed. In the meanwhile, portable devices combining with QDs to adapt the practical detection in complex situations are summarized. The deficiencies and future challenges of QDs in toxicity, specificity, portability, multi-metal co-detection and degradation during the detection are also pointed out. In the end, the development trends of QDs-based nanosensors for heavy metal ions detection are discussed. This review presents an overall understanding, recent advances, current challenges and future outlook of QDs-based nanosensors for heavy metal detection.

Developing non-invasive bladder cancer screening methodology through potentiometric multisensor urine analysis.

We report on the feasibility study exploring the potential of a simple electrochemical multisensor system as a tool for distinguishing between urine samples from patients with confirmed bladder cancer (36 samples) and healthy volunteers (51 samples). The potentiometric sensor responses obtained in urine samples were employed as the input data for various machine learning classification algorithms (logistic regression, random forest, extreme gradient boosting classifier, support vector machine, and voting classifier). The performance metrics of the classifiers were evaluated via Monte-Carlo cross-validation. The best model combining all the acquired data from the people aged 19-88 with different tumor grades and malignancies, including patients with recurrent bladder cancer, yielded 72% accuracy, 71% sensitivity, and 58% specificity. It was found that these metrics can be improved to 76% accuracy, 80% sensitivity, and 75% specificity when only a limited age group (50-88 years of age) is considered. Taking into account the simplicity of the proposed screening method, this technique appears to be a promising tool for further research.

A multi-channel handheld automatic spectrometer for wide range and on-site detection of okadaic acid based on specific aptamer binding.

Okadaic acid (OA) is one of the marine toxins that are widely distributed and harmful to humans. However, the current detection methods for OA involve complex procedures, need long detection time, and rely on large-scale laboratory equipment. In this work, a multi-channel handheld automatic spectrometer (MHAS) based on a spectral sensor was developed with the advantages of small size, simple operation and low cost. It could achieve rapid detection within 30 s and a wide spectral detection range of 470-780 nm with a broadband LED as the light source and a microplate containing 8 wells as a sample cell. Moreover, through the combination of gold nanoparticles (AuNPs) and aptamer-OA34, a highly sensitive and rapid system for OA detection was established with a LOD of 1.80 µg L-1 and a wide detection range of 20-10 000 µg L-1, which is comparable to a microplate reader. Compared with other studies, the proposed MHAS realized rapid on-site detection of OA with a wider detection range, shorter detection time and higher portability. Therefore, the MHAS promises to be a stable and efficient optical detection instrument for on-site detection in the fields of food safety, disease diagnosis and environmental monitoring.

Multiplexed all-solid-state ion-sensitive light-addressable potentiometric sensor (ISLAPS) system based on silicone-rubber for physiological ions detection.

Light-addressable potentiometric sensor (LAPS) has been widely used in biomedical applications since its advent. As a member of the potentiometric sensors, ion-sensitive LAPS (ISLAPS) can be obtained by modifying ion selective sensing membrane on the sensor surface. Compared with the conventional ion-selective electrodes (ISEs) with liquid contact, the all-solid-state ISEs have more advantages such as easy maintenance, more convenient for miniaturization and practical applications. However, the commonly used ion-sensitive membrane (ISM) matrix like PVC has many limitations such as poor adhesion to silicone-based sensor and easy overflow of the plasticizer from the membrane. In this work, LAPS was combined with a variety of ionophore-doped all-solid-state silicone-rubber ISMs for the first time, to establish a program-controlled multiplexed ISLAPS system for physiological ions (Na+, K+, Ca2+ and H+) detection. The silicone-rubber ISMs have better adhesion to silicon-based sensors without containing plasticizers, which can avoid the plasticizer pollution and improve the long-term stability. A layer of poly(3-octylthiophene-2,5-diyl) (P3OT) was pre-modified on the sensor surface to inhibit the formation of an aqueous layer and improve the sensor lifetime. With the aid of a translation stage, the light spot automatically illuminated the detection sites in sequence, and the response of the four ions could be obtained in one measurement within 1 min. The proposed multiplexed ISLAPS has good sensitivity with micromolar limit of detection (LOD), good selectivity and long-term stability (more than 3 months). The results of the real Dulbecco's Modified Eagle Medium (DMEM) sample detection proved that the ISLAPS system can be used for the physiological ions detection, and is promising to realize a multi-parameter microphysiometer.

Instrumental measurement of bitter taste in red wine using an electronic tongue.

An electronic tongue (ET) based on potentiometric chemical sensors was assessed as a rapid tool for the quantification of bitterness in red wines. A set of 39 single cultivar Pinotage wines comprising 13 samples with medium to high bitterness was obtained from the producers in West Cape, South Africa. Samples were analysed with respect to a set of routine wine parameters and major phenolic compounds using Fourier transform infrared-multiple internal reflection spectroscopy (WineScan) and high-performance liquid chromatography, respectively. A trained sensory panel assessed the bitterness intensity of 15 wines, 13 of which had a bitter taste of medium to high intensity. Thirty-one wine samples including seven bitter-tasting ones were measured by the ET. Influence of the chemical composition of wine on the occurrence of the bitter taste was evaluated using one-way analysis of variance. It was found that bitter-tasting wines had higher concentrations of phenolic compounds (catechin, epicatechin, gallic and caffeic acids and quercetin) than non-bitter wines. Sensitivity of the sensors of the array to the phenolic compounds related to the bitterness was studied at different pH levels. Sensors displayed sensitivity to all studied compounds at pH 7, but only to quercetin at pH 3.5. Based on these findings, the pH of wine was adjusted to 7 prior to measurements. Calibration models for classification of wine samples according to the presence of the bitter taste and quantification of the bitterness intensity were calculated by partial least squares-discriminant analysis (PLS-DA) regression. Statistical significance of the classification results was confirmed by the permutation test. Both ET and chemical analysis data could discriminate between bitter and control wines with the correct classification rates of 94% and 91%, respectively. Prediction of the bitterness intensity with good accuracy (root mean square error of 2 and mean relative error of 6% in validation) was possible only using ET data.

Calibration Transfer for LED-Based Optical Multisensor Systems.

Multivariate calibration transfer is widely used to expand the applicability of the existing regression model to new analytical devices of the same or similar type. The present research proves the feasibility of calibration model transfer between a full-scale laboratory spectrometer and an optical multisensor system based on only four light-emitting diodes with different wavelengths. The model transfer between two multisensor systems of this kind has also been studied. Both possibilities were successfully performed without any significant loss of precision using a designed set of training and transfer samples. Direct standardization and slope and bias correction protocols for model transfer were tested and compared. The best model transfer between two optical multisensor systems was obtained using direct standardization.

Prostate cancer screening using chemometric processing of GC-MS profiles obtained in the headspace above urine samples.

The development of screening methods for various types of cancer is of utmost importance as the early diagnostics of these diseases significantly increases the chances for patient's successful medical treatment and recovery. In this study we have developed the procedure for chromatographic profiling of urine samples based on solid-phase microextraction and GC-MS. 50 urine samples (20 from the patients with biopsy conformed prostate cancer and 30 from control group) were studied in the optimized experimental conditions. Application of chemometric classification algorithms such as k-nearest neighbors and partial least squares-discriminant analysis allowed construction of predictive models yielding very high sensitivity, specificity and accuracy values all close to 100%. This gives a good promise for further validation of this approach with a broader sample sets.

Distinguishing paracetamol formulations: Comparison of potentiometric "Electronic Tongue" with established analytical techniques.

Fast and inexpensive analytical tools for identification of the origin of pharmaceutical formulations are important to ensure consumers safety. This study explores the potential of potentiometric multisensor systems ("electronic tongues") in this type of application. 72 paracetamol samples purchased in different countries and produced by various companies were studied via infrared spectroscopy (IR), near infrared spectroscopy (NIR), nuclear magnetic resonance spectroscopy (NMR) and multisensor system (ET). A variety of chemometric tools was applied to explore and compare the information yielded by these methods. It was found that ET is capable of distinguishing paracetamol formulations from different producers. The chemical information derived from potentiometric sensor responses has something in common with that derived from NIR and IR; however, it is orthogonal to that from NMR. ET can be a valuable tool in express quality assessment of drugs.