Modelling of Soxhlet Extraction of Lemongrass Oil

International Journal of Chemical Engineering Research

© 2020 by SSRG - IJCER Journal

Volume 7 Issue 2

Year of Publication : 2020

Authors : Samson Onoriode Okpo, Ipeghan Jonathan Otaraku

10.14445/23945370/IJCER-V7I2P103

How to Cite?

Samson Onoriode Okpo, Ipeghan Jonathan Otaraku, "Modelling of Soxhlet Extraction of Lemongrass Oil," SSRG International Journal of Chemical Engineering Research, vol. 7,  no. 2, pp. 24-29, 2020. Crossref, https://doi.org/10.14445/23945370/IJCER-V7I2P103

Abstract:

Soxhlet extraction of lemongrass oil using ethanol as a solvent was carried out, and regression modeling was done with Microsoft Excel 2010 and SPSS version 23. The results obtained from the extraction process were fitted into different regression models to select an appropriate model for the extraction process using their coefficients of regression (R2) and significance values (p-value) as the basis for selection. The effects of particle size, contact time, and solvent volume on oil yield were considered in the modeling. The proposed regression model for effect of particle size, contact time and solvent volume on yield are y = -0.246In(x) +1.4147, y = - 0.00002510x2+ 0.01548x- 0.6898 and y = -0.0000001714x2+ 0.000113x +1.600 respectively. The optimum yield on applying the proposed models was 1.586 for 0.5cm particle size, 1.696 for 300 minutes contact time, and 1.6179 for 300ml solvent volume. To maximize the lemongrass's oil yield using Soxhlet extraction, a particle size of 0.5cm, contact time of 300 minutes, and solvent volume of 300ml is recommended. Finally, the proposed model equations can be used satisfactorily to predict any value of yield for Soxhlet extraction of lemongrass essential oil within the defined experimental range of values.

Keywords:

Essential oil, Lemongrass, Modelling, Operating parameters, Soxhlet extraction

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