Screening of significant factors affecting pravastatin production by Penicillium sp. ESF21P
Zainol, Norazwina; Seydametova, Emine; Salihon, Jailani; Convey, Peter ORCID: https://orcid.org/0000-0001-8497-9903. 2020 Screening of significant factors affecting pravastatin production by Penicillium sp. ESF21P. IOP Conference Series: Materials Science and Engineering, 736, 022087. 10.1088/1757-899x/736/2/022087
Before downloading, please read NORA policies.Preview |
Text (Open Access)
Published under licence by IOP Publishing Ltd. Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Zainol_2020_IOP_Conf._Ser.__Mater._Sci._Eng._736_022087.pdf - Published Version Available under License Creative Commons Attribution. Download (368kB) | Preview |
Abstract/Summary
Pravastatin is a clinically useful cholesterol-lowering agent. The development of a one-step fermentation process using pravastatin-producing microfungi may be an attractive approach from an economic point of view. To facilitate this, previously 54 fungal cultures were isolated from soil samples. Among them, Penicillium sp. ESF21P was the most active pravastatin producer (196.83 mg/L). The objective of the present study is to determine significant factors affecting pravastatin production by Penicillium sp. ESF21P. The method of the 27-3 fractional factorial design with seven variables was performed using Design-Expert 6.0.8 software package. The seven factors studied were slant age, spore concentration, inoculum volume, fermentation time, temperature, initial pH of the medium, and agitation rate. The results obtained confirmed that the factorial model was significant. Amongst the tested factors, only four were important: agitation rate, slant age, initial pH of the medium, and fermentation time with a percentage contribution of 25.66%, 11.56%, 9.72%, and 7.69%, respectively. These significant factors will be optimized further using response surface methodology.
Item Type: | Publication - Article |
---|---|
Digital Object Identifier (DOI): | 10.1088/1757-899x/736/2/022087 |
Date made live: | 19 Mar 2020 06:58 +0 (UTC) |
URI: | https://nora.nerc.ac.uk/id/eprint/527274 |
Actions (login required)
View Item |
Document Downloads
Downloads for past 30 days
Downloads per month over past year