Hierarchical Clustering (HC) technique is demonstratively applied to analyze the distribution and classification of essential-oil components in oil and dense (subcritical/supercritical) CO2 phases. For this purpose, relative-equilibrium-distribution data obtained for the 24 characteristic components of origanum-oil (Origanum Munituflorum) at 35, 45, 55 ℃ and 20-110 atm pressure range are used. With 24 components and 25 different pressure levels at three different temperatures, the total number of data points amounts to 600, which is large compared to other similar works, making the task of drawing of conclusions by visual inspection quite tedious. As demonstrated in this work, the use of HC technique facilitates the classification of the distribution of essential-oil components. HC-based classification analysis helps to reveal that the distributions of monoterpenes are the most sensitive to changes in temperature and pressure, and they are more soluble in CO2 especially in the supercritical region. At 35 ℃, at higher pressures, due to high solvent density/power, almost all components show similar distributions in the CO2 and oil phases, indicating the loss of fractionation potential. Deterpenation by CO2 is more favorable at higher temperatures. Cophnetic correlation shows the significance level of data clustering. HC analysis proved to be a useful tool in classification of the components and in determination of component clusters in the dense-gas and liquid phases.

Supercritical Carbon Dioxide Essential Oil Origanum Oil Hierarchical Clustering Dendrogram Classification Equilibrium Distribution

Guenther E, The essential oils, 6th Ed., Vol.1 and Vol.2, Van Nostrand Co., New York (1952)
Stahl E, Quirin KW, Gerard D, Dense gases for extraction and refining, Springer-Verlag, Berlin (1987)
Choi YH, Kim J, Noh MJ, Park EM, Yoo KP, Korean J. Chem. Eng., 13(2), 216 (1996)
Reverchon E, J. Supercrit. Fluids, 10(1), 1 (1997)
Kose O, Akman U, Hortacsu O, J. Supercrit. Fluids, 18(1), 49 (2000)
Kubat H, Akman U, Hortacsu O, Chem. Eng. Process., 40(1), 19 (2001)
Lee CH, Lee YW, Kim JD, Row KH, Korean J. Chem. Eng., 18(3), 352 (2001)
Kang KY, Ahn DH, Wilkinson GT, Chun BS, Korean J. Chem. Eng., 22(3), 399 (2005)
Reverchon E, De Marco I, J. Supercrit. Fluids, 38(2), 146 (2006)
Espinosa S, Diaz S, Brignole EA, Comput. Chem. Eng., 24(2-7), 1301 (2000)
Stahl E, Gerard D, Perfumer Flavorist, 10, 29 (1985)
Di Giacomo G, Brandani V, Del Re G, Mucciante V, Fluid Phase Equilib., 52, 405 (1989)
Platin S, Ozer EO, Akman U, Hortacsu O, JAOCS, 71, 833 (1994)
Platin S, Akman U, Hortacsu O, Turkish J. Eng. and Environmental Sci., 18, 369 (1994)
Akgun M, Akgun NA, Dincer S, J. Supercrit. Fluids, 15(2), 117 (1999)
Raeissi S, Peters CJ, J. Supercrit. Fluids, 35(1), 10 (2005)
Ertugrul S, Relative distributions of origanum oil components in oil and sub/supercritical carbon dioxide phases, M.Sc. Thesis, Bogazici University, stanbul, Turkey (1997)
Ertugrul S, Aeskenazi O, Akman U, Hortacsu O, Distributions of origanum-oil components in oil and sub/supercritical carbon dioxide phases, Proceedings of the 4th International Symposium on Supercritical Fluids, Sendai, JAPAN, Vol.B, 417 (1997)
Jain AK, Murty MN, Flynn PJ, ACM Computing Surveys, 31, 264 (1999)
Han SI, Lee SG, Hou BK, Park S, Kim YH, Hwang KS, Korean J. Chem. Eng., 22(3), 345 (2005)
Ward JH, J. Amer. Statist. Assoc., 58, 236 (1963)
Johnson SC, Psychometrika, 2, 241 (1967)
Farris JS, Systematic Zoology, 18, 279 (1969)
Everitt BS, Landau S, Leese M, Cluster analysis, 4th Ed., London, Arnold (2001)
Milligan GW, Cooper MC, Psychometrika, 50, 159 (1985)
Calinski T, Harabasz J, Communications in Statistics, 3, 1 (1974)