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dc.contributor.authorClayton, Barry Timothy Marr
dc.date.accessioned2009-03-16T14:32:00Z
dc.date.available2009-03-16T14:32:00Z
dc.date.issued2007
dc.identifier.urihttp://hdl.handle.net/10394/1620
dc.descriptionThesis (M.Sc. (Chemistry))--North-West University, Potchefstroom Campus, 2007.
dc.description.abstractThe sc-CO2 extraction of annato pigment from seed, piperine from black pepper corns and caffeine from coffee beans was shown to be feasible, yielding extracts comparable to those obtainable by solvent extraction. A principal feature of the investigation was that it revealed the contribution of quite a few variables not normally considered to have a major influence on sc-CO2 botanical extraction. One of these is the natural moisture and light oil content of the plant material that act like internal cosolvents influencing the solvent characteristics of sc- CO2 in a similar way as an added external cosolvent adjusts the polarity of the fluid. The extraction data were processed by linear regression analysis and goal seek statistics available in a commercial software package. It offered the possibility to predict the outcome of an extraction for a moderate change in one parameter while all others are kept constant. The regression fit, however, was not based on real process modelling but rather on an algebraic summation of the contribution of different variables, thus preventing statistical weighting to be applied to the different parameters. The extractions were performed on both micro and pilot plant scale and thereby demonstrated the ability to upscale supercritical work. The mechanism of botanical extraction by sc-CO2 was shown to be principally governed by dissolution of a desired substance by virtue' of the density and thus the solvent strength of the fluid and by the magnitude of the corresponding activation energy. This suggests that the extraction process is chemical in nature.
dc.publisherNorth-West University
dc.titleThe supercritical carbon dioxide extraction of some food related productsen
dc.typeThesisen
dc.description.thesistypeMasters


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