An electrochemical probe containing gold, platinum and rhodium working electrodes was used to monitor yoghurt production in a pilot facility. Three commercial starting cultures at 40, 42 and 44 C transformed milk having 1.5% fat content to mild yoghurt products. The electrochemical changes in the broth during fermentation were recorded as current responses from pulse voltammetry over the electrodes. Principal component analysis of the responses generated two-dimensional score plots describing the qualitative fermentation progressions. Two distinct fermentation pathways were observed leading to similar final products. The pH was recorded during the fermentations and the data was used as reference values for creating a partial least squares model for prediction of pH as an example of a quantitative application for the sensor. The relative mean squared error for validation of the model using four probes interchangeably was about 2%. The probe was constructed of materials approved for use in the food industry and did not require a standard glass reference electrode.
An electronic tongue based on voltammetry and multivariate signal analysis has been evaluated as a tool for characterisation of the chemistry of the wet-end of a paper machine. Measurements were performed on head-box furnish samples from a tissue machine. PLS models, based on electronic tongue data, were made of five reference parameters - pH, conductivity, cationic demand, zeta potential and turbidity. The correlation coefficients for predicted values were for all parameters higher than 0.88. Highly correlated reference parameters might be part of the explanation for the high correlation factors. Still the results, being based on data without e.g. drift compensation, indicate that the electronic tongue has very promising features as a tool for wet-end control. Flexibility, fast response and wide sensitivity spectra make the electronic tongue suitable for a variety of applications.
Global glycosylation changes of serum proteins in type 1 diabetic patients have in this paper been investigated based on the interaction of the saccharide moiety of serum proteins with different lectins. Lectins are proteins, which bind carbohydrates specifically and reversibly. Panels with lectins of various carbohydrate specificities were immobilized on gold surfaces. Sera from healthy individuals, newly diagnosed type 1 diabetes patients and type 1 diabetes patients having had the disease for 4–6 years, respectively, were applied to the lectin panel. The biorecognition was evaluated with null ellipsometry. Data obtained were related to an internal standard of lactoferrin. Multivariate data analysis (MVDA) techniques were used to analyze data.
Principal component analysis showed that the lectin panel enabled discrimination between sera from the three different above-mentioned groups. Using an artificial neuronal net (ANN), it was possible to correctly categorize unknown serum samples into one of the three groups.
Serum proteins of different species and of different human blood groups exhibit various protein glycosylation patterns. Sera from human, pig, sheep and guinea pig have been applied to a panel of eight different lectins immobilized on a gold wafer. The biorecognition has been evaluated with scanning ellipsometry and the two-dimensional matrices obtained have been treated with image analysis and MVDA for evaluation. The results showed a clear difference in protein binding pattern between the different species and thereby separation of the different sera could be made. Dendograms indicate that human and pig sera are the most related of the four different sera investigated.
In this work simple microcontact printed gold-wafers were used to make a lectin panel for investigation and separation of different meat juices from fresh meat of cattle, chicken, pig, cod, turkey and lamb. Seven different lectins were thus attached to gold surfaces using the streptavidin-biotin method. Lectins recognize and bind specifically to carbohydrate structures present on different proteins. The bio-recognition was evaluated with null ellipsometry and the data obtained was related to an internal standard of lactoferrin. The data was evaluated with multivariate data analysis techniques to identify possible separation or grouping of data. Scanning ellipsometry was used for visualization of the binding pattern of the lectins and the meat juice proteins. The 2-dimensional images obtained could be used to visualize the protein distribution, furthermore, to exclude anomalies. The results showed that the different meat juices could be separated from each other. Using a simple model based on an artificial neuronal net, it was also possible to classify meat juices from the mammals investigated.
In this work, simple microcontact printed gold-wafers were used to make a lectin panel for investigation and discrimination of different meat juices from fresh meat of cattle, chicken, pig, cod, turkey and lamb. Seven different lectins were thus attached to gold surfaces using the streptavidin–biotin method. Lectins recognize and bind specifically to carbohydrate structures present on different proteins. The biorecognition was evaluated with null ellipsometry and the data obtained was related to an internal standard of lactoferrin. The data was evaluated with multivariate data analysis techniques to identify possible discrimination or grouping of data. Scanning ellipsometry was used for visualization of the binding pattern of the lectins and the meat juice proteins. The two-dimensional images obtained could be used to visualize the protein distribution, furthermore, to exclude anomalies. The results showed that the different meat juices from the six different species: cattle, chicken, pig, cod, turkey and lamb could be discriminated from each other. The results showed to be more repetitive for the mammalian meat juices. Using a simple model based on an artificial neuronal net, it was also possible to classify meat juices from the mammals investigated.
A self-polishing voltammetric sensor was recently developed and has been applied to samples of urea, milk and sewage water. The polishing device continuously grinds a platinum ring electrode, offering a reproducible and clean electrode surface. Principal component analysis (PCA) and partial least squares (PLS) techniques were applied to interpret the data and to build prediction models. In an evaluation of samples with different urea concentrations, the grinding step allows for repeatable measurements, similar to those after electrochemical cleaning. Furthermore, for the determination of sewage water concentrations in drinking water and for the evaluation of different fat contents in milk samples, the polishing eliminates sensor drift produced by electrode fouling. The results show that the application of a self-polishing unit offers a promising tool for electrochemical studies of difficult analytes and complex media. (C) 2014 Elsevier B.V. All rights reserved.
Pulsed voltammetry has been applied to drinking water monitoring. This non-selective technique facilitates detection of several different threats to the drinking water. A multivariate algorithm shows that anomaly detection is possible with a minimum of false alarms. Multivariate analysis can also be used to classify different types of substances added to the drinking water. Low concentrations of sewage water contaminating the drinking water can be detected. A network of such sensors is envisaged to facilitate real-time and on-line monitoring of drinking water distribution networks.
A method for diesel detection in surface water in the low ppb range is presented. Even though standard commercial metal oxide gas sensors with detection limits in the ppm range are used, extraction of volatile compounds from the water enables a detection limit of about 2 ppb diesel in the water. The technique can be used for surface water monitoring. The standard technique of ultraviolet fluorescence detection has an interference problem with humic substances. This is not a problem with the suggested technique. Results from lab measurements as well as field tests at a water utility in the Stockholm region in Sweden are presented. (C) 2016 Published by Elsevier Ltd.
The EVENT project concerns drinking water surveillance and includes sensors and algorithms that detect anomalies in the drinking water properties, communication of the evaluated sensor data to a crises management system and presentation of information that is relevant for the end users of the crises management system. We have chosen to focus on a sensor technique based on an "electronic tongue", since this robust type of non-selective sensor, can detect a plurality of anomalies without the need of a specific sensor for each type of event. Measurements of natural variations and contamination events are presented and discussed.
Angle and spectra resolved surface plasmon resonance (SPR) images of gold and silver thin films with protein deposits is demonstrated using a regular computer screen as light source and a web camera as detector. The screen provides multiple-angle illumination, p-polarized light and controlled spectral radiances to excite surface plasmons in a Kretchmann configuration. A model of the SPR reflectances incorporating the particularities of the source and detector explain the observed signals and the generation of distinctive SPR landscapes is demonstrated. The sensitivity and resolution of the method, determined in air and solution, are 0.145 nm pixel-1, 0.523 nm, 5.13 × 10-3 RIU degree-1 and 6.014 × 10-4 RIU, respectively, encouraging results at this proof of concept stage and considering the ubiquity of the instrumentation. © 2008 Elsevier B.V. All rights reserved.
Flavour impressions of aqueous solutions of nonanoic acid, octan-2-one and octanal were investigated. In a pre-study, the psychophysical functions of single component solutions were estimated and good agreements to Fechner’s law were obtained. The findings guided the choice of concentrations used in the main flavour interaction study. In this study, binary mixture interactions of nonanoic acid – octanal and octan-2-one – octanal were investigated in terms of perceived intensity and quality. Ten assessors judged the mixture solutions for flavour intensity by applying a free magnitude estimation procedure and describing their perceived quality impressions. The five assessors who were able to describe the perceived qualities in a consistent and logic way considered both mixtures being heterogeneous. Only three assessors scored intensities of the included single component solutions well in agreement with Fechner’s law. These three assessors’ intensity scorings of the mixtures did not deviate from those of a hypothetic additive model in a clear way. The intensity scorings of most of the other assessors were strongly dominated by one of the two components whereas some assessor did not score systematic at all.
The ability of a commercial emission analysis system to evaluate a sensory related attribute was investigated. Since food applications are very complex, a simplified model system consisting of aqueous thyme solutions was evaluated. Sensory odour assessments were made as well as instrumental analysis applying the emission analyser, based on gas sensor arrays, (a so called electronic nose) and headspace gas chromatography. The operation of the emission analyser was found critical and could be optimised thanks to the detailed chemical information obtained by the chromatography. This information also guided a proper evaluation of the emission analyser raw data and predictions of the relative thyme concentrations of the solutions. In that way the emission analyser separated the thyme solutions even better than the assessors applying sensory odour analysis. Since the results seem encouraging the strategy developed and knowledge gained may well be used for investigating more complex systems closer to real applications.
A voltammetric electronic tongue with automated operation based on the flow injection (FIA) technique was applied to the characterization of wastewaters coming from the paper mill industry. A metallic multielectrode array - formed by platinum, gold and rhodium electrodes - was employed as the detection system, while the measurements were based on large amplitude pulse voltammetry (LAPV). LAPV consisted in scans of pulses from to 0 to 1.8 V at 0.2 V steps. Five current values were recorded for each pulse, so a set of 300 current values (three electrodes × 20 pulses × five values) was recorded for each sample. Samples were first discriminated using Principal Component Analysis (PCA), while Artificial Neural Networks were used for the characterization and prediction of chemical oxygen demand, conductivity and pH. The system may be used for the quick identification and monitoring of the quality of used waters in these industrial facilities. © 2005 Elsevier B.V. All rights reserved.
An electronic tongue (ET) based on pulse voltammetry is used to predict concentrations of bisulfites in wine samples. The ET array consists of four working electrodes (gold, rhodium, platinum and stainless steel) encapsulated into a stainless steel cylinder used at the same time as both the body of the ET system and the pseudoreference/counter electrode. The ET device is additionally equipped with a self-polishing system. Multivariate analysis including Cross validation and partial least square (PLS) techniques are applied for data management and prediction models building. Ascorbic acid and histamine have also been included in the predictive analysis.
Polymer membranes are used to increase the selectivity to certain gases of metal silicon dioxide-semiconductor (MOS) structures. Other parameters which influence the selectivity of MOS structures are the type of gate metal, its microstructure (dense or porous) and the operating temperature of the device. Photoresists as membranes can be patterned by photolithographic methods. Membranes, 1-2-mu-m thick, of positive and negative photoresist are applied on MOS capacitors with 6 nm iridium as the gate metal, operated at 150-degrees-C. The influence of the membranes on the response to three gases, hydrogen, ammonia and ethanol, has been investigated. The hydrogen response decreases bv about half with the use of a photoresist membrane. The ammonia response shows a characteristic change in the kinetics, while the ethanol response almost disappears. Positive and negative resist influence the gas response in similar ways, in spite of their different molecular structures.
Data evaluation and classification have been made on measurements by an electronic nose on the headspace of samples of different types of bacteria growing on petri dishes. The chosen groups were: Escherichia coli, Enterococcus sp., Proteus mirabilis, Pseudomonas aeruginosa, and Staphylococcus saprophytica. An approximation of the response curve by time was made and the parameters in the curve fit were taken as important features of the data set. A classification tree was used to extract the most important features. These features were then used in an artificial neural network for classification. Using the ‘leave-one-out’ method for validating the model, a classification rate of 76% was obtained
In this work different electrode materials were investigated as sensors in a voltammetric electronic tongue. Basically, the electronic tongue is based on the combination of nonspecific sensors (electrodes) and pattern recognition tools, for example principal component analysis (PCA). Copper. glassy carbon, nickel, palladium, silver, tin, titanium and zirconium together with more traditional electrode materials such as gold, iridium, and platinum were studied. Cyclic voitammetry was applied to study typical model reactions in solutions containing different electroactive compounds, like ascorbic acid, glucose, histidine and potassium hexacyanoferrate(II). Different sensitivity and selectivity were obtained with the electrodes. Large responses were for example found for the amino acid and the carbohydrate using the copper, nickel and silver electrode. Some of the electrodes were employed in multicomponent solutions, i.e., liquid washing detergents from different suppliers together with differential pulse voltammetry. Responses from the electrodes in combination with PCA showed that they separated the detergents to different extents. This was further used when information from the sensors was merged together for successful discrimination of the detergents. It was found that two detergents close to each other in the score plot were from the same supplier. Furthermore. scanning electron microscopy (SEM) was used to monitor surface changes at the nonnoble electrodes (copper, nickel, and silver).
In this article, drift correction algorithms were used in order to remove linear drift in multivariate spaces of two data sets obtained by an electronic tongue based on voltammetry. The electronic tongue consisted of various metal electrodes (Au, Ir, Pt, Rh) combined with pattern recognition tools, such as principal component analysis. The first data set contained different types of liquid, from well defined to more complex solutions. The second data set contained different black and green teas. Component correction (CC) was compared to a simple additive correction. In CC, the drift direction of measured reference solutions in a multivariate space was subtracted from other types of solution. In additive correction, responses from reference samples were subtracted from other samples. CC showed similar or better performance in reducing drift compared to additive correction for the two data sets. The additive correction method was dependent on the fact that the differences in between samples of a reference solution were similar to the changes in between samples of other liquids, which was not the case with CC.
The use of experimental design as a tool to optimise electrochemically cleaned electrodes applied in a voltammetric electronic tongue is described. A simple and quick activation of electrode surfaces is essential for this type of device, especially for on-line applications in industrial processes. The electronic tongue consisted of four metal electrodes, e.g. Au, Ir, Pt, and Rh in a three-electrode configuration. Current was measured as a function of large potential pulses of decreasing amplitude applied to each electrode. Preliminary results showed that electrochemical cleaning activated the electrode surfaces to similar extent as polishing. Settings of potential and time for each electrode was determined with experimental design in a solution containing 1.0 mM K 4[Fe(CN)6] in 0.1 M phosphate buffer (pH 6.8). Electrode surfaces were deactivated in-between measurements in a complex liquid, like tea. Optimal settings for potential and time in the electrochemical cleaning procedure at each electrode were chosen at recoveries of 100% (compared to polished electrodes). The recoveries were larger than 100% when too large potentials and times were applied. This could be explained by the fact that the electrode areas increased and therefore also the current responses. Principal component analysis (PCA) was used to investigate the stability of the electrode settings at 100% recoveries. No obvious trends of drift in the signals were found. © 2004 Elsevier B.V. All rights reserved.
In this paper, three data compression methods are investigated to determine their ability to reduce large data sets obtained by a voltammetric electronic tongue without loss of information, since compressed data sets will save data storage and computational time. The electronic tongue is based on a combination of non-specific sensors and pattern recognition tools, such as principal component analysis (PCA). A series of potential pulses of decreasing amplitude are applied to one working electrode at a time and resulting current transients are collected at each potential step. Voltammograms containing up to 8000 variables are subsequently obtained. The methods investigated are wavelet transformation (WT) and hierarchical principal component analysis (HPCA). Also, a new chemical/physical model based on voltammetric theory is developed in order to extract interesting features of the current transients, revealing different information about species in solutions. Two model experiments are performed, one containing solutions of different electroactive compounds and the other containing complex samples, such as juices from fruits and tomatoes. It is shown that WT and HPCA compress the data sets without loss of information, and the chemical/physical model improves the separations slightly. HPCA is able to compress the two data sets to the largest extent, from 8000 to 16 variables. When data sets are scaled to unit variance, the separation ability improves even further for HPCA and the chemical/physical model. © 2001 Elsevier Science B.V.
A new sensor technology, an electronic tongue based on voltammetry has been developed at Linköping University. Three different metallic working electrodes are used in combination with a set of voltage "pulses", a waveform, to separate different samples. In this paper, three different waveforms are investigated. This is done through a study with nine different teas. Multivariate data analysis ((MVDA), principal component analysis (PCA)) is used to evaluate the data (the recorded current responses). The waveforms are large amplitude pulse voltammetry (LAPV), small amplitude pulse voltammetry (SAPV), and staircase voltammetry. Each method discriminated between the tea samples to some extent, but differently from each other. Best discrimination is achieved when the combination LAPV and staircase are merged together. When SAPV is included in the combination a worse separation is observed. It is clearly the case that more waveforms do not automatically lead to more information. © 2001 Elsevier Science B.V.
A study that investigates if it is possible to discriminate between the different rinses in a household washing machine with a voltammetric electronic tongue is concluded. The voltammetric electronic tongue applies a potential pulse train over two electrodes and measures the produced current. Multivariate data analysis is used to treat the data. In this paper, a simplified electronic tongue, with only 5% of the original current responses, is used. The rinses from 20 machine wash runs with four different prerequisites are investigated. Principal component analysis (PCA) and Soft-independent modelling of class analogy (SIMCA) are used in order to classify the rinses. In PCA, only one of the rinses is classified erroneous, and in SIMCA none of the rinses are classified only to the wrong class, although 38% of the rinses are classitied to more than one class. (c) 2005 Elsevier B.V. All rights reserved.
An electronic tongue based on voltammetry and a multichannel lipid membrane taste sensor based on potentiometry are compared using two aqueous examples: detergents and teas. The electronic tongue consists of four electrodes of different metals, a reference electrode and a counter electrode. The measurement principle is based on pulse voltammetry in which current is measured during the change of the amplitude of the applied potential. The taste sensor is based on eight different lipid/polymer membranes. The voltage difference between the electrodes and an Ag/AgCl reference electrode is measured when the current is close to zero. The responses from the two sensors systems are treated separately with multivariate data analysis based on principal component analysis and then merged to examine if further information could be extracted. It is shown that although the two sensor systems are about equal in separation ability in the two cases, extra information can be gained by combination of the two sensor systems. © 2001 Elsevier Science B.V. All rights reserved.
A semiconductor gas sensor array combined with a routine for pattern recognition - a so-called electronic nose - for the detection of gas emissions from the leather used in car compartments is described. The gas sensors are 10 metal oxide semiconductor field effect transistors (MOSFETs) with gates of thin, catalytic metals, and five semiconducting metal oxide sensors. The sensor array data are processed by multivariate means using principal component analysis (PCA) and are shown to give similar and add additional information compared to gas chromatography-mass spectrometry (GC- MS) and a human sensory panel. The total volatile organic compound concentration as measured by GC did not differ between good and bad samples and could therefore not be used as a quality control tool, whilst the electronic nose together with pattern recognition could readily discover the deviating samples with unusual emitting gases. This set-up could be useful in on-line quality monitoring systems to detect anomalies in incoming car interior trim materials.
A combination of charcoal and particle filters has previously been shown to reduce effectively the smell of diesel exhaust. In this paper it is shown that the smell of diesel exhaust can successfully be predicted by the concentration of total volatile organic compounds and the concentration of certain carbonyl compounds. Projection to latent structures was utilised for model building. An electronic nose consisting of MOSFET and MOS sensors could less successfully predict the smell, but identified the same filter combination as being most efficient. The car cabin air during urban driving was also monitored, both by the means of MOSFET sensors and by chemiluminescence. The pollution level inside the car is shown to be elevated by about 30% compared to outside the car. A combination filter together with an air inlet sensor switch is shown to reduce the NOx levels inside the car by 30% compared to outside, with the ability to significantly decrease the peak levels. Copyright © 2002 S. Karger AG, Basel.
The use of sensor arrays and pattern recognition applied to the obtained signal patterns for environmental monitoring are discussed in some detail. Different types of electronic tongues are described and evaluated for monitoring purposes. More specifically the performance of multielectrode arrays used for voltammetric analysis of aqueous samples is described. It is, e.g. shown how such an 'electronic tongue' can be used to monitor the quality of water in a production plant for drinking water. It is pointed out that the concepts of 'electronic noses' and 'electronic tongues' often predict a quality of a sample rather than giving exact information about concentrations of individual species. (C) 2001 Elsevier Science B.V.
The thermal conversion of biomass fuel mixes in fluidized beds can cause agglomeration. To counteract agglomeration, bed material is gradually exchanged with virgin bed material, and this results in increased disposal of used bed material. Furthermore, the bed material exchange represents a costly option, as it involves a cost for virgin bed material, for landfill, and for unplanned downtime of the plant. This paper presents a novel method for the evaluation of bed material quality: the electronic tongue (ET). Evaluation of bed material quality can contribute toward decreasing the cost of unnecessary exchanges of bed material. The proposed method was tested on bed material sampled on an almost daily basis from a commercial fluidized bed boiler during several months of operation. A two-electrode ET was used for the evaluation of the bed material quality. The analysis relied on pulsed voltammetry measurements and multivariate data analysis with Principal Component Analysis (PCA). The results suggest that it is possible to follow bed material changes and that the ET, after further development, may be used to optimize the material flows connected to the bed material. Further research is being conducted to optimize the ETs performance and its application in monitoring bed material.
The properties of gas-sensitive semiconductor devices with catalytic metal gates are reviewed, with emphasis on field-effect structures sensitive to hydrogen-containing molecules like H2, NH3, H2S, alcohols, ethylene etc.
A brief review of some of the developed device structures are given. The principles of hydrogen sensors with Pd gates are described in some detail. Ammonia-sensitive field-effect devices with thin catalytic metal gates are discussed. Applications of gas-sensitive field-effect devices for studies of catalytic reactions together with electron spectroscopy in UHV systems, for medical diagnosis, in leak detectors and as biosensors are reviewed.
Some of the ongoing studies at our laboratory of gas-sensitive field-effect devices with catalytic metal gates are reviewed. More particularly, we discuss the use of such devices in so-called electronic noses due to the possibility of changing the selectivity patterns of the devices by the choice of catalytic metal and operation temperature. Several examples of the application of electronic noses consisting of field-effect devices in combination with metal oxide-based sensors are given. Finally, a summary is given of some remaining scientific problems and studies related to the understanding and development of gas-sensitive field-effect devices.
THERE is much interest in the use of chemical sensor arrays, in conjunction with pattern-recognition routines, for developing artificial olfactory devices-electronic noses-which can characterize the chemical composition of gas mixtures 1-5. Here we describe a technique that uses a continuous sensing surface and a detection method involving a scanning pulsed light source, to generate images that represent a fingerprint of the gases detected. The detector is a large-area field-effect device with a number of different catalytic metals constituting the detecting surface (the devices active gate) 6,7. A pulsed light beam scanned across this surface generates a photocapacitive current that varies with the value of the surface potential 8,9. A continuous sensing surface of this type provides information that would require an array of hundreds of discrete sensors. The technique also provides a new means of studying the coupling between the electronic properties of catalytic metals and chemical reactions taking place on their surfaces.
The properties of gas-sensitive field-effect devices with catalytic metal gates are described. We demonstrate especially how the selectivity of these sensors depends on parameters such as the choice of catalytic metal, the structure of the catalytic metal film and the operation temperature of the device. The sensitivity towards molecules like hydrogen, ammonia, ethanol and ethylene is demonstrated. The selectivity pattern of devices with catalytic metal gates is discussed in relation to the fabrication of multisensor arrays and the development of 'artificial olfactory senses'.
Hydrogen- and ammonia-sensitive metal-oxide semiconductor (MOS) structures are described. Special attention is paid to ammonia-sensitive MOS devices with thin (ca. 3 nm) iridium or platinum gates. It is shown how these devices can be used in combination with immobilized enzymes to develop bioprobes or biosensing systems. The temperature dependence of the gas sensitivity of MOS structures with catalytic metal gates is considered. It is demonstrated that at low temperatures (30-40 <latex>$^\circ$</latex>C)iridium gates have a faster response to ammonia than platinum gates, and that Ir-MOS structures thus are better suited for the development of biosensors. It is also shown that at high temperatures (190-200 <latex>$^\circ$</latex>C) platinum gates can be used to detect unsaturated hydrocarbons such as ethylene. Gas evolution from ripening fruits was monitored with such a sensor. Some biosensing applications of ammonia sensitive Ir-gate MOS devices are described; for example, the determination of urea and creatinine. The devices are used both to measure a pulse of ammonia in a flowthrough system and to measure in situ steady-state responses as a bioprobe. The special features of gas sensors used for biosensing purposes are summarized.
The present contribution contains an overview of the development of gas sensitive field-effect devices in Linköping during the last 25 years. It is completely centred to the work at the Laboratory of Applied Physics at Linköping University, and is therefore not a proper review of a research field where many important contributions have been made by several other research groups. © 2006 Elsevier B.V. All rights reserved.
A personal description of the history of gas-sensitive field-effect devices is given. It is shown how the originally described palladium-gate metal-oxide-semiconductor field-effect transistor has developed into sensing surfaces enabling the production of response images to odours. Images obtained for the odour from different cheeses are presented as examples of such artificial olfactory images.
Bacterial infection and inflammation result in massive changes in serum glycoproteins. These changes were investigated by the interaction of the saccharide glycoprotein moiety with lectins. A panel of eight lectins (Canavalia ensiformis, Bandeiraea simplicifolia BS-I, Arachis hypogaea, Phytolacca americana, Phaseolus vulgaris, Artocarpus integrifolia, Triticum vulgaris and Pisum sativum) was used to differentiate human serum glycoproteins obtained from patients with various bacterial infections. Lectin functionalised sensing layers were created on gold-coated wafers and lectin-glycoprotein interactions were monitored by surface plasmon resonance. The interaction of the lectin panel with serum glycoproteins produces unique patterns. Principal component analysis (PCA) was used to analyse the patterns. The actual panel of eight lectins enabled discrimination between sera obtained from patients sick with bacterial infection and healthy patients. Extended lectin panels have the potential to distinguish between types of bacterial infection and identify specific disease state. © 2002 Elsevier Science B.V. All rights reserved.
A voltammetric electronic tongue (ET) and a conductivity meter were used to predict amounts of detergents in process water from washing machines. The amount of detergent in over sixty samples was also determined by a HPLC reference method. Prediction was more accurate for the electronic tongue, but both techniques could be used. The composition of the detergent, e.g. supporting electrolyte, is an important factor for the ability to predict the detergent quantity by conductivity. Also two different surfactants, alkyl benzyl sulfonate (ABS) and etoxylated fatty alcohol (EOA), were fingerprinted by the HPLC. Their behaviour during the wash cycle differs from each other, ABS rinses away in the same proportions as the supporting electrolyte, but EOA appears to stay within the machine and laundry. Prediction models for ABS are accurate both with ET and conductivity meter, mostly due to the correlation with supporting electrolyte. The behaviour of EOA, with almost no correlation to the supporting electrolyte makes it difficult to predict using conductivity but ET prediction models give promising indications of its capabilities. © 2008 Elsevier B.V. All rights reserved.
A self polishing voltammetric electronic tongue was evaluated for simultaneousl prediction of urea and glucose concentrations in phosphate buffer in a flow system. The voltammetric electronic tongue consisted of three working electrodes (gold, platinum and rhodium) and a counter electrode, also acting as reference electrode. The flowsystem contained five valves, controlled by a computer and a peristaltic pump. Two batches of sample standards were used; one for calibration and the other for validation. The system could predict concentrations of urea and glucose in the interval 0 – 20 mM in the validation batch. No significant difference between the two batches was seen. The self polishing approach makes the system in principle maintenance free. With a large potential use in hemodialysis.
An investigation to obtain reproducible measurements with a pulse voltammetric electronic tongue has lead to the development of self polishing device. A grit paper covered bar rotating over the working electrodes is performing the polishing, to avoid measurements while the polishing bar covers the electrodes an angular decoder is fitted. Measurements in buffer, 2 mM K3[Fe(CN)6] and a buffered tea samples shows that polishing reduces drift, sensitivity decreases with electrode fouling, pre-treatment or conditioning of electrodes post polishing must be optimised concerning the analyte. Also found was that drift due to electrode fouling is a repeatable mechanism which pattern can be used to increase information about the analyte. © 2006 Elsevier B.V. All rights reserved.
A general problem for all electronic tongues (and for most other sensor systems), especially when measuring in crude and complex media, is electrode fouling. The possibility of using a selfpolishing voltammetric electronic tongue has been investigated using cyclic voltammetry. The tested compounds were potassium hexacyanoferrat(II) (K4Fe(CN)6) and urea, respectively. Effects of short term drift, directly after polishing before the electrode is completely equilibrated, are repeatable.
The ethanol concentration in realistic breath samples was analyzed using an electronic nose. Conditions were selected so that the samples would reflect those collected in a real drunk driver situation. Hence, parameters such as intake of food and beverage, tobacco habits, as well as the order of participating volunteers were allowed to be variable. The setup was unexpectedly robust towards inter- and intrapersonal variations in breath samples as well as long-term variations. The standard error (16 mol ppm) was the limiting factor but the statistical detection limit was well below 0.1 ppm. The standard error corresponds to between 9% (Austria) and 36% (Sweden) of lowest legally accepted levels. Even though this is regarded as a significant error, there are several options of optimization. Incorporating feature extraction and forward selection together with artificial neural network for prediction of the ethanol concentration showed, besides increasing the accuracy, to be a valuable tool generating feedback of possible improvements of the sensor array.
Analyses of exhaled air by means of electronic noses offer a large diagnostic potential. Such analyses are non-invasive; samples can also be easily obtained from severely ill patients and repeated within short intervals. Lung cancer is the most deadly malignant tumor worldwide, and monitoring of lung cancer progression is of great importance and may help to decide best therapy. In this report, twenty-two patients with diagnosed lung cancer and ten healthy volunteers were studied using breath samples collected several times at certain intervals and analysed by an electronic nose. The samples were divided into three sub-groups; group d for survivor less than one year, group s for survivor more than a year and group h for the healthy volunteers. Prediction models based on partial least square and artificial neural nets could not classify the collected groups d, s and h, but separated well group d from group h. Using artificial neural net, group d could be separated from group s. Excellent predictions and stable models of survival day for group d were obtained, both based on partial least square and artificial neural nets, with correlation coefficients 0.981 and 0.985, respectively. Finally, the importance of consecutive measurements was shown.
The feasibility of employing an electronic tongue to measure the growth of mold in a liquid medium was studied. We used the electronic tongue developed at Linköping University, which is based on pulsed voltammetry and consists of an array of different metal electrodes. Instead of focusing on a single parameter, this device provides information about the condition or quality of a sample or process. Accordingly, the data obtained are complex, and multivariate methods such as principal component analysis (PCA) or projection to latent structures (PLS) are required to extract relevant information. A gas chromatographic technique was developed to measure ergosterol content in mold biomass and was subsequently used as a reference method to investigate the ability of the electronic tongue to measure the growth of mold in liquid media. The result shows that the electronic tongue can monitor mold growth in liquids. In PLS analysis, the electronic tongue signals correlate well with the amount of ergosterol in the mold biomass as well as the microbially induced changes in the pH of the medium. © 2002 Elsevier Science B.V. All rights reserved.
An electronic tongue based on pulsed voltammetry over an array of electrodes with different selectivity and sensitivity patterns was used to recognize six different microorganisms: one yeast, two bacteria, and three molds. Measurements were performed during the whole growth period, from the lag phase to the stationary phase. The electrode array was dipped into the malt extract growth medium and voltage was applied over the electrodes in pulses of different amplitude and the resulting current data was sampled and collected in a matrix. Evaluation of the electronic tongue data was made with principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA). PCA was performed on data from the lag, the logarithmic, and also the stationary growth phase. In the lag growth phase no recognition of species was visible in the PCA score plots. After further growth however all the included microbial species could be recognized from each other. The ability to predict membership of new replicates of the species to the right classes was verified with SIMCA. © 2003 Elsevier Science B.V. All rights reserved.
Arrays of microband electrodes were developed by screen printing followed by cutting, which enabled the realization of microband arrays at the cut edge. The microband arrays of different designs were characterized by physical and electro-chemical methods. In both cases, the methods showed that the microband width was around 5 mm. Semi-steady-state cyclic voltammetry responses were observed for redox probes, and chronocoulometric measurements showed the establishment of convergent diffusion regimes characterized by current densities similar to those of a single microelectrode. The analytical performance of the electrode system and its versatility were illustrated with two electrochemical assays: detection of ascorbic acid through direct oxidation and a mediated glucose biosensor fabricated by dip coating. Due to convergent mass transport, both systems showed an enhancement in their analytical characteristics. The developed approach can be adapted to automated electrode recovery.
This review examines basic principles and applications of voltammetric electronic tongues. It is introduced by a description of the concept of electronic tongues or taste sensors followed by a general overview of electrochemical measurement principles that have been used for electronic tongues. A special emphasis is given on measurement principles for voltammetric electronic tongues, also including pulse voltammetry and variable reduction. Applications of voltammetric electronic tongue are described, such as in the food industry, environmental analysis, paper and pulp industry, household appliances and agriculture. Future developments of the concept, such as self polishing or miniaturized devices are also described. Finally, a continuous measurement system for chemical oxygen demand (COD), which has been commercialized, is depicted.
The concept of electronic tongues or taste sensors has developed rapidly during recent years due to their large potential. They are based on electrochemical sensors combined with multivariate data analysis. Voltammetric electronic tongues have proven valuable in many applications. Due to their ruggedness and simplicity, they have been found especially suitable for on-line monitoring of industrial processes. A voltammetric electronic tongue, specially designed for use in the dairy industry is described. It consisted of four working electrodes (gold, platinum, rhodium and stainless steel), embedded in PEEK (TM). It was mounted in a housing of stainless steel, which was inserted in the process line for direct on-line measurements. The voltammetric electronic tongue was used to follow different sources of milk coming into the process and to monitor the cleaning process. (c) 2005 Elsevier B.V. All rights reserved.
A hybrid electronic tongue is described based on a combination of potentiometry, voltammetry and conductivity. It was used for classification of six different types of fermented milk. Using ion-selective electrodes, pH, carbon dioxide and chloride ion concentrations were measured. The voltammetric electronic tongue consisted of six working electrodes of different metals (gold, iridium, palladium, platinum, rhenium and rhodium) and an Ag/AgCl reference electrode. The measurement principle is based on pulse voltammetry in which current transients are measured due to the onset of voltage pulses at decreasing potentials. The data obtained from the measurements were treated by multivariate data processing based on principal components analysis and an artificial neural net. The hybrid tongue could separate all six samples. Also, the nature of the micro-organisms in the different fermentations was reflected in the principal component analysis. Copyright (C) 2000 Elsevier Science B.V.