Optimization of microbiological parameters for enhanced griseofulvin production using response surface methodology

Abstract

Central composite design was used to determine the optimal levels of microbiological parameters, viz., slant age, seed age and inoculum level, for enhanced griseofulvin production by Penicillium griseofulvum MTCC 1898 and Penicillium griseofulvum MTCC 2004 in shake¯ask fermentation. The optimal levels of slant age, seed age and inoculum level for Penicillium griseofulvum MTCC 1898 were found to be 8.8772 days, 4.2093 days, 12% (v/v) (º17.56 kg dry cell mass/m 3 ) and for Penicillium griseofulvum MTCC 2004, 8.221 days, 3.4875 days and 9% (v/v) (º8.09 kg dry cell mass/m 3 ) respectively. The yield of griseofulvin under optimal conditions was found to be 1.65 times for Penicillium griseofulvum MTCC 1898 and 1.07 times for Penicillium griseofulvum MTCC 2004 higher than that obtained using unoptimized conditions. The fermentation time for maximum production of griseofulvin by Penicillium griseofulvum MTCC 1898 and Penicillium griseofulvum MTCC 2004 decreased by 4 days and 2 days respectively.

Purification and characterization of l-asparaginase from Pseudomonas aeruginosa strain SN004: Production optimization by statistical methods

“…In addition, traditional technique of bioprocess progress by studying the effect of one variable at a time is tedious, time consuming and expensive. In contrast, statistical approaches are mostly favored due to their advantages (Dasu et al, 2000;Reddy et al, 2008) and statistically planned experiments diminish the error in defining the effect of the factors in an economical manner (Sharma et al, 2006;Kumar et al, 2009). There is little information accessible concerning statistical optimization of the media elements of L-asparaginase production.…”

OPTIMIZATION OF PROCESS CONDITIONS USING RESPONSE SURFACE METHODOLOGY (RSM) FOR ETHANOL PRODUCTION FROM WASTE CASHEW APPLE JUICE BYZYMOMONAS MOBILIS

“…In spite of various advantages, statistical designs have been applied to only a limited number of aerobic submerged and solid-state fermentation and anaerobic submerged fermentation processes (Cheynier et al, 1983). Thus, RSM experimental design is an efficient approach to deal with a large number of variables, and there are several reports on the application of RSM for the production of primary and secondary metabolites through microbial fermentation (Dasu and Panda, 2002).…”

Microbial Production of 7-Aminocepahlosporanic Acid and New Generation Cephalosporins (Cephalothin) by Different Processing Strategies

“…Response surface methodology (RSM) is a collection of mathematical and statistical techniques widely used to determine effects of several variables and to optimize different biotechnological processes [15][16][17][18]. Optimization of cephalosporin-C acylase was done by central composite experimental design (CCD), where a 2 3 factorial design was employed with 20 experiments.…”