Dmitry Kirsanov

Instrumental measurement of beer taste attributes using an electronic tongue

The present study deals with the evaluation of the electronic tongue multisensor system as an analytical tool for the rapid assessment of taste and flavour of beer. Fifty samples of Belgian and Dutch beers of different types (lager beers, ales, wheat beers, etc.), which were characterized with respect to the sensory properties, were measured using the electronic tongue (ET) based on potentiometric chemical sensors developed in Laboratory of Chemical Sensors of St. Petersburg University. The analysis of the sensory data and the calculation of the compromise average scores was made using STATIS. The beer samples were discriminated using both sensory panel and ET data based on PCA, and both data sets were compared using Canonical Correlation Analysis. The ET data were related to the sensory beer attributes using Partial Least Square regression for each attribute separately. Validation was done based on a test set comprising one-third of all samples. The ET was capable of predicting with good precision 20 sensory attributes of beer including such as bitter, sweet, sour, fruity, caramel, artificial, burnt, intensity and body.

Multicomponent analysis of fermentation growth media using the electronic tongue (ET).

A potentiometric electronic tongue (ET) consisting of eight cross-sensitive chemical sensors and a standard pH electrode has been applied for analysis of simulated fermentation solutions typical for fermentation processes with Aspergillus niger. The electronic tongue has been found capable of simultaneous determination of ammonium, citrate and oxalate in complex media with good precision (typical error within 8%). The system preserved high sensitivity to the targeted substances also in the presence of sodium azide, which is commonly used for suppressing microbial activity in real-world fermentation samples. Sensor performance was fast and reproducible which promises well for routine application of the electronic tongue for fermentation process monitoring.

Assessment of bitter taste of pharmaceuticals with multisensor system employing 3 way PLS regression

The application of the potentiometric multisensor system (electronic tongue, ET) for quantification of the bitter taste of structurally diverse active pharmaceutical ingredients (API) is reported. The measurements were performed using a set of bitter substances that had been assessed by a professional human sensory panel and the in vivo rat brief access taste aversion (BATA) model to produce bitterness intensity scores for each substance at different concentrations. The set consisted of eight substances, both inorganic and organic - azelastine, caffeine, chlorhexidine, potassium nitrate, naratriptan, paracetamol, quinine, and sumatriptan. With the aim of enhancing the response of the sensors to the studied APIs, measurements were carried out at different pH levels ranging from 2 to 10, thus promoting ionization of the compounds. This experiment yielded a 3 way data array (samples×sensors×pH levels) from which 3wayPLS regression models were constructed with both human panel and rat model reference data. These models revealed that artificial assessment of bitter taste with ET in the chosen set of APIs is possible with average relative errors of 16% in terms of human panel bitterness score and 25% in terms of inhibition values from in vivo rat model data. Furthermore, these 3wayPLS models were applied for prediction of the bitterness in blind test samples of a further set of APIs. The results of the prediction were compared with the inhibition values obtained from the in vivo rat model.

Cross-sensitive chemical sensors based on tetraphenylporphyrin and phthalocyanine

Abstract The properties of solvent polymeric membrane sensors based on 5,10,15,20-tetraphenylporphyrin (TPP) and phthalocyanine (PHC) have been investigated. The sensitivity and selectivity of sensors towards wide range of mono- and di-valent cations have been measured. The selectivity towards the transition metal ions for TPP-based sensor does not correspond to the cation lipophilicity sequence. The dependence of response on pH was studied. The cross-sensitivity parameters, including average response slope, signal-to-noise ratio and “non-selectivity” factor for all sensors were calculated and compared. The influence of plasticizer and ionic additive on the response of sensors was characterized using principal component analysis (PCA).

Novel diamides of 2,2′-dipyridyl-6,6′-dicarboxylic acid: synthesis, coordination properties, and possibilities of use in electrochemical sensors and liquid extraction

The procedure was proposed for the synthesis of various dipyridyldiamides. Their various properties in the series of rare-earth elements were studied. The possibility to use the synthe-sized compounds in polymer membranes of electrochemical sensors for the development of novel types of sensors was shown. A comparison of the influence of the ligand structure on the extraction and sensor characteristics was performed.

Determination of urine ionic composition with potentiometric multisensor system

The ionic composition of urine is a good indicator of patients general condition and allows for diagnostics of certain medical problems such as e.g., urolithiasis. Due to environmental factors and malnutrition the number of registered urinary tract cases continuously increases. Most of the methods currently used for urine analysis are expensive, quite laborious and require skilled personnel. The present work deals with feasibility study of potentiometric multisensor system of 18 ion-selective and cross-sensitive sensors as an analytical tool for determination of urine ionic composition. In total 136 samples from patients of Urolithiasis Laboratory and healthy people were analyzed by the multisensor system as well as by capillary electrophoresis as a reference method. Various chemometric approaches were implemented to relate the data from electrochemical measurements with the reference data. Logistic regression (LR) was applied for classification of samples into healthy and unhealthy producing reasonable misclassification rates. Projection on Latent Structures (PLS) regression was applied for quantitative analysis of ionic composition from potentiometric data. Mean relative errors of simultaneous prediction of sodium, potassium, ammonium, calcium, magnesium, chloride, sulfate, phosphate, urate and creatinine from multisensor system response were in the range 3-13% for independent test sets. This shows a good promise for development of a fast and inexpensive alternative method for urine analysis.

New polymeric chemical sensors for determination of lead ions

New polymeric electrochemical sensors for determining the content of lead were suggested. As the active substance of the polymeric membranes of the sensors was used N,N′-tetrabutyldipicolinamide, the compound exhibiting a high extractive capacity for heavy metal ions. The selectivity of the sensors with respect to lead ions in the presence of copper, cadmium, and zinc in a considerable excess was studied.

Mimicking Daphnia magna bioassay performance by an electronic tongue for urban water quality control

Toxicity is one of the key parameters of water quality in environmental monitoring. However, being evaluated as a response of living beings (as their mobility, fertility, death rate, etc.) to water quality, toxicity can only be assessed with the help of these living beings. This imposes certain restrictions on toxicity bioassay as an analytical method: biotest organisms must be properly bred, fed and kept under strictly regulated conditions and duration of tests can be quite long (up to several days), thus making the whole procedure the prerogative of the limited number of highly specialized laboratories. This report describes an original application of potentiometric multisensor system (electronic tongue) when the set of electrochemical sensors was calibrated against Daphnia magna death rate in order to perform toxicity assessment of urban waters without immediate involvement of living creatures. PRM (partial robust M) and PLS (projections on latent structures) regression models based on the data from this multisensor system allowed for prediction of toxicity of unknown water samples in terms of biotests but in the fast and simple instrumental way. Typical errors of water toxicity predictions were below 20% in terms of Daphnia death rate which can be considered as a good result taking into account the complexity of the task.

Three-point multivariate calibration models by correlation constrained MCR-ALS: A feasibility study for quantitative analysis of complex mixtures

When it comes to address quantitative analysis in complex mixtures, Partial Least Squares (PLS) is often referred to as a standard first-order multivariate calibration method. The set of samples used to build the PLS regression model should ideally be large and representative to produce reliable predictions. In practice, however, the large number of calibration samples is not always affordable and the choice of these samples should be handled with care as it can significantly affect the accuracy of the predictive model. Correlation constrained multivariate curve resolution (CC-MCR) is an alternative regression method for first-order datasets where, unlike PLS, calibration and prediction stages are performed iteratively and optimized under constraints until the decomposition meets the convergence criterion. Both calibration and test samples are fitted into a unique bilinear model so that the number of calibration samples is no longer a critical issue. In this paper we demonstrate that under certain conditions CC-MCR models can provide for reasonable predictions in quantitative analysis of complex mixtures even when only three calibration samples are employed. The latter are defined as samples having the minimum, the maximum and the average concentration, providing for a simple and rapid strategy to build reliable calibration model. The feasibility of three-point multivariate calibration approach was assessed with several case studies featuring mixtures of different analytes in presence of interfering species. Satisfactory predictions with relative errors in the range 3-15% were achieved and good agreement with classical PLS models built from a larger set of calibration samples was observed.

Two low-cost digital camera-based platforms for quantitative creatinine analysis in urine.

In clinical analysis creatinine is a routine biomarker for the assessment of renal and muscular dysfunctions. Although several techniques have been proposed for a fast and accurate quantification of creatinine in human serum or urine, most of them require expensive or complex apparatus, advanced sample preparation or skilled operators. To circumvent these issues, we propose two home-made platforms based on a CD Spectroscope (CDS) and Computer Screen Photo-assisted Technique (CSPT) for the rapid assessment of creatinine level in human urine. Both systems display a linear range (r(2) = 0.9967 and 0.9972, respectively) from 160 μmol L(-1) to 1.6 mmol L(-1) for standard creatinine solutions (n = 15) with respective detection limits of 89 μmol L(-1) and 111 μmol L(-1). Good repeatability was observed for intra-day (1.7-2.9%) and inter-day (3.6-6.5%) measurements evaluated on three consecutive days. The performance of CDS and CSPT was also validated in real human urine samples (n = 26) using capillary electrophoresis data as reference. Corresponding Partial Least-Squares (PLS) regression models provided for mean relative errors below 10% in creatinine quantification.