MULTISENSOR SYSTEM APPLICATION FOR PREPARATIONS BITTERNESS EVALUATION IN TRADITIONAL CHINESE MEDICINE

I. S. Yaroshenko, D. O. Kirsanov, A. V. Legin, W. Ping, D. Ha, W. Hao, W. . Haitong, Y. . He


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Abstract

This paper deals with the study of preparations based on medicinal plants used in traditional Chinese medicine for treatment and prevention of a wide range of diseases. The purpose of this research was evaluation of the capabilities of a multisensor system for instrumental assessment of the samples bitterness. 33 samples of medicinal plants were evaluated by tasters according to bitterness intensity from 0 to 6. Methodology of the analysis was developed and repeated measurements of the samples were performed by multisensor system. Tasters’ assessments were used as reference data while multisensor system calibrating. A regression model built according to these data displayed good correlation of the system response with bitterness perceived by people. The parameters of the regression model give the possibility for concluding that the multisensor system is capable to predict the bitterness of the medicinal plants preparations with average precision equal to ±1 of the reference bitterness scale. Relative error of bitterness determination is 14%, which is a good result for such type of measurements (typical error of the taster’s assessment is, as a rule, in the range of 15-30 %).


Keywords: multisensor system, bitterness, correlation with human sensory perception, herbs

References
 1.     Hulanicki A., Glab S., Ingman F. Chemical sensors definition and classification. Pure and Applied Chemistry, 1991, vol. 63, no. 9, pp. 1247–1250.
2.     Otto M., Thomas J. Model studies on multiple channel analysis of free magnesium, calcium, sodium and potassium at physiological concentration levels with ion-selective electrodes. Analytical Chemistry, 1985, vol. 57, pp. 2647–2651.
3.     Esbensen K.H. Multivariate Data Analysis in Practice. 5th ed. CAMO Software AS: Oslo, Norway, 2001, 594 p.
4.     Legin A., Rudnitskaya A., Vlasov Y.G., Di Natale C., Davide F., D’Amico A. Tasting of beverages using an electronic tongue. Sensors and Actuators, B: Chemical, 1997, vol. 44, no. 1-3, pp. 291–296.
5.     Legin A., Rudnitskaya A., Lvova L., Vlasov Y., Di Natale C., D’Amico A. Evaluation of Italian wine by the electronic tongue: recognition, quantitative analysis and correlation with human sensory perception. Analytica Chimica Acta, 2003, vol. 484, no. 1, pp. 33–44. doi: 10.1016/S0003-2670(03)00301-5
6.     Rudnitskaya A., Nieuwoudt H.H., Muller N., Legin A., du Toit M., Bauer F. Instrumental measurement of bitter taste in red wine using an electronic tongue. Analytical and Bioanalytical Chemistry, 2010, vol. 397, no. 7, pp. 3051–3060. doi: 10.1007/s00216-010-3885-3
7.     Rudnitskaya A., Schmidtke L.M., Delgadillo I., Legin A., Scollary G. Study of the influence of micro-oxygenation and oak chip maceration on wine composition using an electronic tongue and chemical analysis. Analytica Chimica Acta, 2009, vol. 642, no. 1-2, pp. 235–245. doi: 10.1016/j.aca.2008.12.034
8.     Schmidtke L.M., Rudnitskaya A., Saliba A.J., Blackman J.W., Scollary G.R., Clark A.C., Rutledge D.N., Delgadillo I., Legin A. Sensory, chemical, and electronic tongue assessment of micro-oxygenated wines and oak chip maceration: assessing the commonality of analytical techniques. Journal of Agricultural and Food Chemistry, 2010, vol. 58, no. 8, pp. 5026–5033. doi: 10.1021/jf904104f
9.     Kirsanov D., Mednova O., Vietoris V., Kilmartin P.A., Legin A. Towards reliable estimation of an «electronic tongue» predictive ability from PLS regression models in wine analysis. Talanta, 2012, vol. 90, pp. 109–116. doi: 10.1016/j.talanta.2012.01.010
10.  Rudnitskaya A., Polshin E., Kirsanov D., Lammertyn J., Nicolai B., Saison D., Delvaux F.R., Delvaux F., Legin A. Instrumental measurement of beer taste attributes using an electronic tongue. Analytica Chimica Acta, 2009, vol. 646, pp. 111–118. doi: 10.1016/j.aca.2009.05.008
11.  Polshin E., Rudnitskaya A., Kirsanov D., Legin A., Saison D., Delvaux F., Delvaux F.R., Nicolai B.M., Lammertyn J. Electronic tongue as a screening tool for rapid analysis of beer. Talanta, 2010, vol. 81, no. 1-2, pp. 88–94. doi: 10.1016/j.talanta.2009.11.041
12.  Mottram T., Rudnitskaya A., Legin A., Fitzpatrick J.L., Eckersall P.D. Evaluation of a novel chemical sensor system to detect clinical mastitis in bovine milk. Biosensors and Bioelectronics, 2007, vol. 22, no. 11, pp. 2689–2693.doi: 10.1016/j.bios.2006.11.006
13.  Rudnitskaya A., Legin A. Sensor systems - electronic tongues and electronic noses for the monitoring of biotechnological processes. Journal of Industrial Microbiology and Biotechnology, 2008, vol. 35, no. 5, pp. 443–451. doi: 10.1007/s10295-007-0298-1
14.  Legin A., Kirsanov D., Rudnitskaya A., Iversen J.J.L., Seleznev B., Esbensen K.H., Mortensen J., Houmøller L., Vlasov Y. Multicomponent analysis of fermentation growth media using the electronic tongue (ET). Talanta, 2004, vol. 64, no. 3, pp. 766–772. doi: 10.1016/j.talanta.2004.04.001
15.  Kirsanov D., Khaydukova M., Tkachenko L., Legin A., Babain V. Potentiometric sensor array for analysis of complex rare Earth mixtures. Electroanalysis, 2012, vol. 24,no.1, pp. 121–130. doi: 10.1002/elan.201100439
16.  Legin A.V., Babain V.A., Kirsanov D.O., Mednova O.V. Cross-sensitive rare earth metal sensors based on extraction systems. Sensors and Actuators, B: Chemical, 2008, vol. 131, no. 1, pp. 29–36. doi: 10.1016/j.snb.2007.12.002
17.  Legin A.V., Kirsanov D.O., Babain V.A., Gall L.N., Gall N.R. Promising analytical techniques for HLW analysis. In: Radioactive Waste: Sources, Types and Management. Eds. Satoshi Yuan, Wenxu Hidaka. NY, USA, NOVA Science Publishers Inc, 2012, pp. 77–96.
18.  Rudnitskaya A., Ehlert A., Legin A., Vlasov Yu., Buttgenbach S. Multisensor system on the basis of an array of non-specific chemical sensors and artificial neural networks for determination of inorganic pollutants in model groundwater. Talanta, 2001, vol. 55, no. 2, pp. 425–431. doi: 10.1016/S0039-9140(01)00444-1
19.  Kirsanov D., Zadorozhnaya O., Krasheninnikov A., Komarova N., Popov A., Legin A. Water toxicity evaluation in terms of bioassay with an Electronic Tongue. Sensors and Actuators, B: Chemical, 2013, vol. 179, pp. 282–286. doi: 10.1016/j.snb.2012.09.106
20.  Legin A., Rudnitskaya A., Vlasov Y. Electronic tongues: new analytical perspective for chemical sensors. Comprehensive Analytical Chemistry, 2003, vol. 39, pp. 437–486. doi: 10.1016/S0166-526X(03)80115-0
21.  Kirsanov D., Babain V., Agafonova-Moroz M., Lumpov A., Legin A. Combination of optical spectroscopy and chemometric techniques – a possible way for on-line monitoring of SNF reprocessing. Radiochimica Acta, 2012, vol. 100,no.3, pp. 185–188. doi: 10.1524/ract.2012.1901
22.  Yaroshenko I., Kirsanov D., Kartsova L., Bhattacharyya N., Sarkar S., Legin A. On the application of simple matrix methods for electronic tongue data processing: case study with black tea samples. Sensors and Actuators, B: Chemical, 2014, vol. 191, pp. 67–74. doi: 10.1016/j.snb.2013.09.093
23.  Kirsanov D., Cetó X., Khaydukova M., Blinova Y., Del Valle M., Babain V., Legin A. A combination of dynamic measurement protocol and advanced data treatment to resolve the mixtures of chemically similar analytes with potentiometric multisensor system. Talanta, 2014, vol. 119, pp. 226–231. doi: 10.1016/j.talanta.2013.11.003
24.  Legin A., Rudnitskaya A., Clapham D., Seleznev B., Lord K., Vlasov Y. Electronic tongue for pharmaceutical analytics: quantification of tastes and masking effects. Analytical and Bioanalytical Chemistry, 2004, vol. 380, no. 1, pp. 36–45. doi: 10.1007/s00216-004-2738-3
25.  Rudnitskaya A., Kirsanov D., Blinova Y., Legin E., Seleznev B., Clapham D., Ives R.S., Saunders K.A., Legin A. Assessment of bitter taste of pharmaceuticals with multisensor system employing 3 way PLS regression. Analytica Chimica Acta, 2013, vol. 770, pp. 45–52. doi: 10.1016/j.aca.2013.02.006
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