DOI QR코드

DOI QR Code

Discrimination of the drinking water taste by potentiometric electronic tongue and multivariate analysis

전자혀 및 다변량 분석법을 활용한 먹는물의 구별 방법

  • Eunju Kim (Institute of Civil Engineering and Building Technology, The Department of Land, Water and Environment Research) ;
  • Tae-Mun Hwang (Institute of Civil Engineering and Building Technology, The Department of Land, Water and Environment Research) ;
  • Jae-Wuk Koo (Institute of Civil Engineering and Building Technology, The Department of Land, Water and Environment Research) ;
  • Jaeyong Song (Incheon Institute of Public Health and Environment) ;
  • Hongkyeong Park (Water Quality Institute Waterworks Headquarters Incheon Metropolitan City) ;
  • Sookhyun Nam (Institute of Civil Engineering and Building Technology, The Department of Land, Water and Environment Research)
  • 김은주 (한국건설기술연구원 환경연구본부) ;
  • 황태문 (한국건설기술연구원 환경연구본부) ;
  • 구재욱 (한국건설기술연구원 환경연구본부) ;
  • 송재용 (인천광역시 보건환경연구원) ;
  • 박홍경 (인천시 상수도사업본부 맑은물연구소) ;
  • 남숙현 (한국건설기술연구원 환경연구본부)
  • Received : 2023.11.15
  • Accepted : 2023.12.11
  • Published : 2023.12.15

Abstract

Organoleptic parameters such as color, odor, and flavor influence consumer perception of drinking water quality. This study aims to evaluate the taste of the selected bottled and tap water samples using an electronic tongue (E-tongue) instead of a sensory test. Bottled and tap water's mineral components are related to the overall preference for water taste. Contrary to the sensory test, the potentiometric E-tongue method presented in this study distinguishes taste by measuring the mineral components in water, and the data obtained can be statistically analyzed. Eleven bottled water products from various brands and one tap water from I city in Korea were evaluated. The E-tongue data were statistically analyzed using multivariate statistical tools such as hierarchical clustering analysis (HCA), principal component analysis (PCA), and partial least squares discriminant analysis (PLS-DA). The results show that the E-tongue method can clearly distinguish taste discrimination in drinking water differing in water quality based on the ion-related water quality parameters. The water quality parameters that affect taste discrimination were found to be total dissolved solids (TDS), sodium (Na+), calcium (Ca2+), magnesium (Mg2+), sulfate (SO42-), chloride (Cl-), potassium (K+) and pH. The distance calculation of HCA was used to quantify the differences between 12 different types of drinking water. The proposed E-tongue method is a practical tool to quantitatively evaluate the differences between samples in water quality items related to the ionic components. It can be helpful in quality control of drinking water.

Keywords

Acknowledgement

본 연구는 환경부의 재원으로 한국환경산업기술원의 상하수도 혁신 기술개발사업의 지원을 받아 연구 되었습니다(2020002700004).

References

  1. American Public Health Association. APHA, AWWA, WEA. (2005). Standard Methods for the Examination of Water and Wastewater. 21st ed.; American Public Health Association: Washington, DC, USA.
  2. Aminu, M. and Ahmad N.A. (2020). Complex chemical data classification and discrimination using locality preserving partial least squares discriminant analysis, ACS Omega, 5, 26601-26610. https://doi.org/10.1021/acsomega.0c03362
  3. Arfao, A.T., Onana. M.F., Koji, E., Moungang, L.M., Ewoti, O.V., Emadjeu, J.B.T., Tchakonte, S., Njoya, A,M., Ngando, T.S. and Mosie, N. (2021). Using principal component analysis to assess water, quality from the landing stages in coastal region, Am. J. Water Resour., 29(1), 23-31.
  4. Belkhiri, L. and Mouni, L. (2014). Geochemical characterization of surface water and groundwater in Soummam Basin, Algeria. Nat. Resour., 23(4), 393-407. https://doi.org/10.1007/s11053-014-9243-y
  5. Beullens, K., Meszaros, P., Vermeir, S., Kirsanov, D., Legin, A., Buysens, S., Cap, N., Nicolai, B.M. and Lammertyn, J. (2008). Analysis of tomato taste using two types of electronic tongues, Sens. Actuators B Chem., 131(1), 10-17. https://doi.org/10.1016/j.snb.2007.12.024
  6. Braga, G.S., Pater, L.G. and Fonseca, F.J. (2012). Performance of an electronic tongue during monitoring 2-methylisoborneol and geosmin in water samples, Sens. Actuators B, 171-172, 181-189. https://doi.org/10.1016/j.snb.2012.02.092
  7. Burlingame, G.A., Whelton, A. and Dietrich, A.M. (2007). Understanding the basics of tap water taste, Article in American Water Works Association, 5.
  8. Callen, M.S., Martinez, Grasa, G., Lpez, J.M. and Murillo, R. (2022). Principal component analysis and partial least square regression models to understand sorption enhanced biomass gasification, Biomass Convers. Biorefin., 15.
  9. Capitan, M.G., Fontserè, M.B. and Jorquera, C.J. (2019). Organoleptic analysis of drinking water using an electronic tongue based on electrochemical microsensors, Sensors, 19(6), 1435.
  10. Cho, S. and Moazzem, M.S. (2022). Recent applications of potentiometric electronic tongue and electronic nose in sensory evaluation, Prev. Nutr. Food Sci., 27(4), 354-364. https://doi.org/10.3746/pnf.2022.27.4.354
  11. Cuartero, M., Ruiz, A., Galian, M. and Ortuno, J. (2022). Potentiometric electronic tongue for quantitative ion analysis in natural mineral waters, Sensors, 22, 6204.
  12. Dias, L.G., Fernandes, A., Veloso, A.C.A., Machado, A., Pereira, J.A. and Peres, A.M. (2014). Single-cultivar extra virgin olive oil classification using a potentiometric electronic tongue, Food Chem., 160, 321-329. https://doi.org/10.1016/j.foodchem.2014.03.072
  13. Dietrich, A.M. and Burlingame, G.A. (2015). Critical review and rethinking of USEPA Secondary Standards for maintaining Organo-leptic quality of drinking water, Environ. Sci. Technol., 49(2), 708-720. https://doi.org/10.1021/es504403t
  14. Doria, M.F. (2006). Bottled water versus tap water: understanding consumers' preferences, J. Water Health, 4(2), 271-276. https://doi.org/10.2166/wh.2006.0023
  15. European Commitee for Standardization. (2006). Water Quality. Determination of the Threshold Odour Number (TON) and Threshold Flavour Number (TFN), CSN EN 1622; BSI: Brussels, Belgium.
  16. Gallardo, J., Alegret, S. and Valle, M.D. (2005). Application of a potentiometric electronic tongue as a classification tool in food analysis, Talanta, 66(5), 1303-1309. https://doi.org/10.1016/j.talanta.2005.01.049
  17. Ghrissi, H., Veloso, A.C.A., Marx I.M.G., Dias, T. and Peres, A.M. (2021). A potentiometric electronic tongue as a discrimination tool of water-food indicator/contamination bacteria, Chemosensors, 9, 143.
  18. Iliev, B., Lindquist, M., Robertsson, L. and Wide, P. (2006). A fuzzy technique for food and water quality assessment with an electronic tongue, Fuzzy Sets Syst., 157(9), 1155-1168. https://doi.org/10.1016/j.fss.2005.12.014
  19. Koster, E.P. (1981). Sensory evaluation of drinking water by consumer panels, Sci. Total Environ., 18, 155-166. https://doi.org/10.1016/S0048-9697(81)80056-3
  20. Heras, J.Y., Pallarola, D. and Battaglini, F. (2010). Electronic tongue for simultaneous detection of endotoxins and other contaminants of microbiological origin, Biosens. Bioelectron., 25, 2470-2476. https://doi.org/10.1016/j.bios.2010.04.004
  21. Kovacs, Z., Sipos, L., Szollosi, D., Kokai, Z., Szekely, G. and Fekete, A. (2011). Electronic tongue and sensory evaluation for sensing apple juice taste attributes, Sens. Lett., 9, 1273-1281. https://doi.org/10.1166/sl.2011.1687
  22. Krasner, S.W. (1988). Flavor-profile analysis: An objective sensory technique for the identification and treatment of off-flavors in drinking water, Water Sci. Technol., 20(8-9), 31-36. https://doi.org/10.2166/wst.1988.0221
  23. Lawless, H. (1995). Dimensions of sensory quality: A critique, Food Qual. Prefer., 6(3), 191-199. https://doi.org/10.1016/0950-3293(94)00023-O
  24. Liu, M., Wang, J., Li, D. and Wang, M. (2012). Electronic tongue coupled with physicochemical analysis for the recognition of orange beverages, J. Food Qual., 35, 429-441. https://doi.org/10.1111/jfq.12004
  25. Lvova, L., Guanais Goncalves, C., Petropoulos, K., Micheli, L., Volpe, G., Kirsanov, D., Legin, A., Viaggiu, E., Congestri, R., Guzzella, L., Pozzoni, F., Palleschi, G., Di Natale, C. and Paolesse, R. (2016). Electronic tongue for microcystin screening in waters, Biosens. Bioelectron., 80, 154-160. https://doi.org/10.1016/j.bios.2016.01.050
  26. Manez, R.M., Soto, J., Breijo E.G., Gil, L., Ibanez, J. and Llobet, E. (2005). An ''electronic tongue'' design for the qualitative analysis of natural waters, Sens. Actuators B Chem., 104(2), 302-307. https://doi.org/10.1016/j.snb.2004.05.022
  27. Nam, S.H., Lee, J.W., Kim, E.J., Koo, J.W. and Shin, Y.H. and Hwang, T.M. (2023). Electronic tongue for the simple and rapid determination of taste and odor compounds in water, Chemosphere, 338, 139511.
  28. Platikanov, S., Hernandez, A., Gonzalez, S., Cortina, J.L. and Tauler, R. (2017). Predicting consumer preferences for mineral composition of bottled and tap water, Talanta, 162, 1-9. https://doi.org/10.1016/j.talanta.2016.09.057
  29. Ouyang, Q., Zhao, J.W. and Chen, Q.S. (2014). Instrumental intelligent test of food sensory quality as mimic of human panel test combining multiple cross-perception sensors and data fusion, Anal. Chim. Acta., 841, 68-76. https://doi.org/10.1016/j.aca.2014.06.001
  30. Qian, N. (2018). Bottled water or tap water? A Comparative study of drinking water choices on university campuses, water, 10(1), 59.
  31. Rudnitskaya, A., Polshin, E., Kirsanov, D., Lammertyn, J., Nicolai, B., Saison, D., Delvaux, F.R., Delvaux, F. and Legin, A. (2009). Instrumental measurement of beer taste attributes using an electronic tongue, Anal. Chim. Acta., 646, 111-118. https://doi.org/10.1016/j.aca.2009.05.008
  32. Sghaier, K., Barhoumi, H., Maaref, A. and Siadat, M. (2009). Classification and discrimination of different Tunisian water samples using an electronic tongue, Sens. Lett., 7(5), 683-688. https://doi.org/10.1166/sl.2009.1131
  33. Sipos, L., Kovacs, Z., Kiss, V.S., Csiki, T., Kokai, Z., Fekete, A. and Heberger K. (2012). Discrimination of mineral waters by electronic tongue, sensory evaluation and chemical analysis, Food Chem., 135(4), 2947-2953. https://doi.org/10.1016/j.foodchem.2012.06.021
  34. Teillet, E., Schlich, P., Urbano, C., Cordelle, S. and Guichard, E. (2010). Sensory methodologies and the taste of water, Food Qual. Prefer., 21(8), 967-976. https://doi.org/10.1016/j.foodqual.2010.04.012
  35. Vlasov, Y.G., Legin, A.V., Rudnitskaya, A.M,, Amico. A,D. and Natale, C.D. (2000). Electronic tongue-new analytical tool for liquid analysis on the basis of non-specific sensors and methods of pattern recognition, Sens. Actuators B Chem., 65(1-3), 235-236. https://doi.org/10.1016/S0925-4005(99)00323-8
  36. Ward, J.H. (1963). Hierarchical grouping to optimize an objective function, J. Am. Stat. Assoc., 58, 236-244. https://doi.org/10.1080/01621459.1963.10500845
  37. Winquist, F. (2008). Voltammetric electronic tongues-basic principles and applications, Microchim. Acta., 163, 3-10. https://doi.org/10.1007/s00604-007-0929-2
  38. Wold, S., Sjostrom, M. and Eriksson, L. (2001). PLS-regression: a basic tool of chemometrics, Chemometr, Intell. Lab. Syst., 58(2), 109-130. https://doi.org/10.1016/S0169-7439(01)00155-1
  39. Yaroshenko, I., Kirsanov, D., Kartsova, L., Bhattacharyya, N., Sarkar, S. and Legin, A. (2014). On the application of simple matrix methods for electronic tongue data processing: Case study with black tea samples, Sens. Actuator B Chem., 191, 67-74. https://doi.org/10.1016/j.snb.2013.09.093