Statistical screening and optimization of factors that influence lipase production from palm kernel cake using candida cylindracea in solid-state bioconversion

Although lipases are important class of industrial enzymes but the high cost of their production limits their applications. In this study, an abundant raw material in Malaysia, palm kernel cake (PKC), was investigated as a substrate ina fermentation process to produce lipase using solid-state biocon...

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Bibliographic Details
Main Authors: Elgharbawy, Amal Ahmed, Alam, Md Zahangir, Mohd. Salleh, Hamzah
Format: Article
Language:English
Published: Journal of Pure and Applied Microbiology 2014
Subjects:
Online Access:http://irep.iium.edu.my/38272/
http://irep.iium.edu.my/38272/
http://irep.iium.edu.my/38272/1/Paper-JPAM-amal.pdf
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Summary:Although lipases are important class of industrial enzymes but the high cost of their production limits their applications. In this study, an abundant raw material in Malaysia, palm kernel cake (PKC), was investigated as a substrate ina fermentation process to produce lipase using solid-state bioconversion (SSB) with minimum requirements of machinery and external nutrients. This requires an optimization process in order to achieve maximum production with the minimum requirements. Optimization for the parameters that influence lipase production from Candida cylindracea was conducted using statistical experimental designs including Plackett-Burman (PB) design, one-factor- at-a-time (OFAT) and response surface methodology (RSM). Optimization enhanced lipase production over 4-fold compared to the screening stage, in PKC media supplemented with 1.5% (w/w) yeast extract, 2.0% (v/w) Tween-80, 0.5% (v/w) olive oil and 7.0% (v/w) inoculum at pH 7.0 and 30oC within 72 hrs fermentation. Maximum activity of 400?2 U/g dry PKC was achieved. The analysis of variance (ANOVA) indicated that the model was significant (p<0.05) with coefficient of determination (R2) 0.9893 which was very close to the adjusted R2 (0.9816) pointing the reliability of the model.