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.

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.

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 API's 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 API's. The results of the prediction were compared with the inhibition values obtained from the in vivo rat model.