Solubility of garcinia mangostana oil in supercritical carbon dioxide / Izni Atikah Abd Hamid

Natural antioxidant as medical treatment nowadays has gained great attention in substituting the use of synthetic drugs. Mangosteen peel was proven containing abundant of potential compounds which were believed to exhibit antimicrobial, antibacterial and anticancer activity for cancer disease treatm...

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Main Author:	Abd Hamid, Izni Atikah
Format:	Thesis
Language:	English
Published:	2013
Subjects:	Biotechnology Oils, fats, and waxes
Online Access:	http://ir.uitm.edu.my/id/eprint/20426/ http://ir.uitm.edu.my/id/eprint/20426/1/TM_IZNI%20ATIKAH%20ABD%20HAMID%20EH%2013_5.pdf

id	uitm-20426
recordtype	eprints
spelling	uitm-204262018-07-05T05:30:58Z http://ir.uitm.edu.my/id/eprint/20426/ Solubility of garcinia mangostana oil in supercritical carbon dioxide / Izni Atikah Abd Hamid Abd Hamid, Izni Atikah Biotechnology Oils, fats, and waxes Natural antioxidant as medical treatment nowadays has gained great attention in substituting the use of synthetic drugs. Mangosteen peel was proven containing abundant of potential compounds which were believed to exhibit antimicrobial, antibacterial and anticancer activity for cancer disease treatment. Conventional extraction method i.e. solvent extraction was used for years in extracting natural compounds. The method however contributed to the enormous increment of hazardous organic solvents emissions and caused generation of aqueous waste streams to the environment. Therefore, an alternative cleaner, safer and sustainable process that does not require the use of dangerous solvents is necessary. In this study, an environmental friendly solvent Carbon Dioxide (CO2) under supercritical conditions has been chosen to extract the interest compounds from mangosteen peel. The extraction was conducted at constant flowrate of 24 mL/min within 40 minutes by varying temperature and pressure from 50 to 80 °C and from 34.5 to 55.1 MPa, respectively. The extracts obtained were identified using Gas Chromatography Mass Spectrometer (GCMS) to determine the oil compositions. The highest extraction yield of 1.85% (g oil/g sample) with 0.12 of Average Absolute Deviation (AAD) and highest solubility of mangosteen peel oil (0.575 mg oil/g CO2) in Supercritical Carbon Dioxide (SC-CO2) was obtained at temperature of 80 °C and pressure of 41.4 MPa. Experimental work for the whole range of temperature and pressure consumed more cost, time and energy. Therefore modeling of solubility data was required to obtain the relationship between the manipulated variable i.e. extraction temperature and pressure with the solubility of mangosteen peel oil in SC-CO2. In this study, a multi-layer feedforward back-propagation Artificial Neural Network (ANN) model was developed for the solubility prediction of mangosteen peel oil in SC-CO2, where the input variables were temperature and pressure. An optimal ANN model consisted of one hidden layer and five neurons was obtained with minimum value of Mean Square Error (MSE) of 0.011 for 48 experimental data points used. The analysis showed that the ANN prediction model have a good agreement with the experimental data in which the value of correlation coefficient (R-value) for training, validating and testing obtained is 0.933, 0.982 and 0.927, respectively. 2013 Thesis NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/20426/1/TM_IZNI%20ATIKAH%20ABD%20HAMID%20EH%2013_5.pdf Abd Hamid, Izni Atikah (2013) Solubility of garcinia mangostana oil in supercritical carbon dioxide / Izni Atikah Abd Hamid. Masters thesis, Universiti Teknologi MARA.
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Teknologi MARA
building	UiTM Institutional Repository
collection	Online Access
language	English
topic	Biotechnology Oils, fats, and waxes
spellingShingle	Biotechnology Oils, fats, and waxes Abd Hamid, Izni Atikah Solubility of garcinia mangostana oil in supercritical carbon dioxide / Izni Atikah Abd Hamid
description	Natural antioxidant as medical treatment nowadays has gained great attention in substituting the use of synthetic drugs. Mangosteen peel was proven containing abundant of potential compounds which were believed to exhibit antimicrobial, antibacterial and anticancer activity for cancer disease treatment. Conventional extraction method i.e. solvent extraction was used for years in extracting natural compounds. The method however contributed to the enormous increment of hazardous organic solvents emissions and caused generation of aqueous waste streams to the environment. Therefore, an alternative cleaner, safer and sustainable process that does not require the use of dangerous solvents is necessary. In this study, an environmental friendly solvent Carbon Dioxide (CO2) under supercritical conditions has been chosen to extract the interest compounds from mangosteen peel. The extraction was conducted at constant flowrate of 24 mL/min within 40 minutes by varying temperature and pressure from 50 to 80 °C and from 34.5 to 55.1 MPa, respectively. The extracts obtained were identified using Gas Chromatography Mass Spectrometer (GCMS) to determine the oil compositions. The highest extraction yield of 1.85% (g oil/g sample) with 0.12 of Average Absolute Deviation (AAD) and highest solubility of mangosteen peel oil (0.575 mg oil/g CO2) in Supercritical Carbon Dioxide (SC-CO2) was obtained at temperature of 80 °C and pressure of 41.4 MPa. Experimental work for the whole range of temperature and pressure consumed more cost, time and energy. Therefore modeling of solubility data was required to obtain the relationship between the manipulated variable i.e. extraction temperature and pressure with the solubility of mangosteen peel oil in SC-CO2. In this study, a multi-layer feedforward back-propagation Artificial Neural Network (ANN) model was developed for the solubility prediction of mangosteen peel oil in SC-CO2, where the input variables were temperature and pressure. An optimal ANN model consisted of one hidden layer and five neurons was obtained with minimum value of Mean Square Error (MSE) of 0.011 for 48 experimental data points used. The analysis showed that the ANN prediction model have a good agreement with the experimental data in which the value of correlation coefficient (R-value) for training, validating and testing obtained is 0.933, 0.982 and 0.927, respectively.
format	Thesis
author	Abd Hamid, Izni Atikah
author_facet	Abd Hamid, Izni Atikah
author_sort	Abd Hamid, Izni Atikah
title	Solubility of garcinia mangostana oil in supercritical carbon dioxide / Izni Atikah Abd Hamid
title_short	Solubility of garcinia mangostana oil in supercritical carbon dioxide / Izni Atikah Abd Hamid
title_full	Solubility of garcinia mangostana oil in supercritical carbon dioxide / Izni Atikah Abd Hamid
title_fullStr	Solubility of garcinia mangostana oil in supercritical carbon dioxide / Izni Atikah Abd Hamid
title_full_unstemmed	Solubility of garcinia mangostana oil in supercritical carbon dioxide / Izni Atikah Abd Hamid
title_sort	solubility of garcinia mangostana oil in supercritical carbon dioxide / izni atikah abd hamid
publishDate	2013
url	http://ir.uitm.edu.my/id/eprint/20426/ http://ir.uitm.edu.my/id/eprint/20426/1/TM_IZNI%20ATIKAH%20ABD%20HAMID%20EH%2013_5.pdf
first_indexed	2023-09-18T23:04:36Z
last_indexed	2023-09-18T23:04:36Z
_version_	1777418398777475072

Solubility of garcinia mangostana oil in supercritical carbon dioxide / Izni Atikah Abd Hamid

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