Supercritical extraction of essential oil from Echium amoenum seed : Experimental, modeling and genetic algorithm parameter estimation

Seyyed Mohammad Ghoreishi; Ehsan Bataghva

Korean Journal of Chemical Engineering, Vol.31, No.9, 1632-1640, September, 2014

DOI10.1007/s11814-014-0118-z Export Citation

Supercritical extraction of essential oil from Echium amoenum seed : Experimental, modeling and genetic algorithm parameter estimation

Seyyed Mohammad Ghoreishi^†, and Ehsan Bataghva

Department of Chemical Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran

E-mail:

Mathematical modeling of supercritical CO2 extraction of essential oil from Echium amoenum seed was carried out. The effect of process variables such as pressure (15, 20, 25 and 30 MPa), temperature (313, 318, 323 and 328 K) and CO2 flow rate (0.6, 0.9, 1.2 and 1.5 ml/min) on the recovery of essential oil extraction was investigated in a series of experiments conducted in a laboratory scale apparatus. The chemical composition of recovered essential oil (fatty acids) was analyzed by GC-FID. The mathematical model was developed utilizing diffusion-controlled regime in the pore and film mass transfer resistances with axial dispersion of the mobile phase at dynamic conditions. Henry’s law was used to describe the equilibrium state of solid and pore fluid phases. The obtained mass transfer equations for the mobile and stationary phases were solved using the numerical explicit method of line, and the modeling predictions of oil extraction recovery were validated via comparison with experimental data. Genetic algorithm (GA) was applied to estimate the optimum value of the Henry constant. Finally, applying the validated model the extraction recovery was investigated as a function of effective variables such as dynamic extraction time and supercritical fluid temperature, pressure and flow rate. A set of optimal operating conditions were determined via modeling parametric analysis to achieve the objective function of maximum recovery.

Keywords:Supercritical Fluid Extraction;Modeling;Echium amoenum Seed;Genetic Algorithm

[References]

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Rebouillat S, Steffenino B, Letellier B, Chem. Eng. Sci., 55(1), 15 (2000)
Ghoreishi SM, Shahrestani RG, Ghaziaskar HS, Chem. Eng. Technol., 32, 1 (2009)
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Tan CS, Liang SK, Liou DC, Chem. Eng. J., 38, 1 (1988)
Kiran E, Arai K, J. Supercrit. Fluids, 13(1), 1 (1998)
Goldberg DE, Genetic algorithms in search, optimization and machine learning, Addision Wesley, MA (1989)
Holland JH, Adaptation in natural and artificial systems, MIT Press Cambridge, MA (1992)
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[Referenced By]

[1] Shafaghi B, Naderi N, Tahmasb L, Kamalinejad M, Iran J. Pharm. Res., 1, 1 (2002)

[2] Menendez JA, Colomer R, Lupu R, Med. Hypo. Theses, 64, 2 (2005)

[3] Ge H, Kong X, Shi L, Hou L, Liu Z, Li P, Cell Biol. Int., 33, 3 (2009)

[4] Wang L, Weller CL, Schlegel VL, Carr TP, Cuppett SL, Bioresour. Technol., 99, 5 (2008)

[5] Lucas S, Calvo MP, Garcia-Serna J, Palencia C, Cocero MJ, J. Supercrit. Fluids, 41, 2 (2007)

[6] Oliveira ELG, Silvestre AJD, Silva CM, Chem. Eng. Res. Des., 89(7A), 1104 (2011)

[7] Huang Z, Shi XH, Jiang WJ, J. Chromatogr. A, 1250, 2 (2012)

[8] Bernardo-Gil MG, Casquilho M, AIChE J., 53, 11 (2007)

[9] Mongkholkhajornsilp D, Douglas S, Douglas PL, Elkamel A, Teppaitoon W, Pongamphai S, J. Food Eng., 71, 4 (2005)

[10] Gaspar F, Lu T, Santos R, Al-Duri B, J. Supercrit. Fluids, 25, 3 (2003)

[11] Reverchon E, Sesti Osseo L, Chem. Biochem. Eng. Q., 8, 1 (1994)

[12] Salgin U, Doker, CalImlI A, J. Supercrit. Fluids, 38, 3 (2006)

[13] Lee AKK, Bulley NR, Fattori M, Meisen A, J. Am. Oil Chem. Soc., 63, 7 (1986)

[14] Reverchon E, Marrone C, Chem. Eng. Sci., 52, 20 (1997)

[15] Reverchon E, Poletto M, Chem. Eng. Sci., 51, 15 (1996)

[16] Rebouillat S, Steffenino B, Letellier B, Chem. Eng. Sci., 55(1), 15 (2000)

[17] Ghoreishi SM, Shahrestani RG, Ghaziaskar HS, Chem. Eng. Technol., 32, 1 (2009)

[18] Sovova H, Kuera J, Je J, Chem. Eng. Sci., 49, 3 (1994)

[19] Stastova J, Jez J, Bartlova M, Sovova H, Chem. Eng. Sci., 51, 18 (1996)

[20] Marrone C, Poletto M, Reverchon E, Stassi A, Chem. Eng. Sci., 53, 21 (1998)

[21] Dalton L, Harper A, Ren A, Wang F, Todorova G, Chen J, Zhang C, Lee M, Ind. Eng. Chem. Res., 38(1), 8 (1999)

[22] Kim HJ, Lee SB, Park KA, Hong IK, Sep. Purif. Technol., 15(1), 1 (1999)

[23] Angus S, Armstrong B, De-Reuck KM, IUPAC: International thermodynamics tables of the fluid state carbon dioxide, Pergamon Press, New York (1976)

[24] Poling BE, Prausnitz JM, John Paul OC, Reid RC, The properties of gases and liquids, McGraw-Hill, New York (2001)

[25] Delitala C, Marongiu B, Porcedda S, Fluid Phase Equilib., 142(1-2), 1 (1998)

[26] Wakao N, Smith JM, Chem. Eng. Sci., 17, 11 (1962)

[27] Tan CS, Liang SK, Liou DC, Chem. Eng. J., 38, 1 (1988)

[28] Kiran E, Arai K, J. Supercrit. Fluids, 13(1), 1 (1998)

[29] Goldberg DE, Genetic algorithms in search, optimization and machine learning, Addision Wesley, MA (1989)

[30] Holland JH, Adaptation in natural and artificial systems, MIT Press Cambridge, MA (1992)

[31] Guil-Guerrero JL, Lopez-Martinez JC, Gomez-Mercado F, Campra-Madrid P, Eur. J. Lipid Sci. Technol., 108, 1 (2006)

[32] Daukas E, Venskutonis PR, Sivik B, J. Supercrit. Fluids, 22, 3 (2002)

[33] Salimi A, Fatemi S, Nei HZN, Safaralie A, Chem. Eng. Technol., 31, 10 (2008)