Predictive Study on the Effect of Using Microbial-Derived Enzymes for the Aqueous Extraction of Coconut Oil
Author : Marges, Ma. Cecilia Escueta
Major Adviser : Chay, Pham Binh
Major Co-Adviser : Movillon, Jovita L.
Committee Members : Acda, Reynaldo I.
Year : 1992
Month : October
Type : Thesis
Degree: BS
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Abstract
The effects of various process parameters (PH, temperature and enzyme concentration) on the aqueous extraction of coconut oil using a crude enzyme solution extracted from a selected Aspergillus niger strain was evaluated.
The extraction ability of the enzyme, measured in terms of the yield of cream, was significantly affected by pH. Generally, peak enzyme activity was observed between pH 5 to 6.
Different process temperatures (40, 50 and 60 °C) were tested for its effect on the enzymatic activity. However, no consistent general trend was observed at the different pH and enzyme concentration levels. However, the central trend (taken at center values of the two other parameters) shows the yield decreasing as temperature increases.
Enzyme concentrations of 15, 20 and 25% (w/v) were also tested. Again, no definite and consistent trend was observed. Graphical response surface analysis failed to identify the true optimum point for the process within the range of values tested. The highest value for the cream yield (32.70 ml) occured at a point where the curve was discontinuous, and thus could not be considered as the absolute maximum point.
Further studies are recommended, using parameter values beyond the range considered in this study, to ascertain where the true optimum conditions for the process to occur. Other process variables must also be studied and optimized to enhance the process. Also, the crude enzyme solution must be further studied to identify and characterize the enzyme complexes present. The method of extraction must also include a process for separating the oil from the cream, to ascertain it’s true quality and quantity, as well as a method for measuring the total oil content of the coconut sample, to be able to express yield in terms of percent extraction.
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