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

Abstract

Ethanol has been known for a long time, being perhaps the oldest product obtained through traditional biotechnology. It is an attractive, sustainable energy source for fuel additives. Based on a four-level central composite design (CCD) involving the variables substrate composition (20-100%) X 1 , pH (4.5-6.5) X 2 , incubation temperature (28 -36 C) X 3 , and fermentation time (12-60 h) X 4 , a response surface methodology (RSM) for the production of ethanol using waste cashew apple juice as substrate by Zymomonas mobilis MTCC 090 was standardized. The design contains a total of 31 experimental trials with the first 16 organized in a fractional factorial design and 25 to 31 involving the replications of the central points. Data obtained from RSM on ethanol production were subjected to the analysis of variance (ANOVA) and analyzed using a second-order polynomial equation, which resulted in the optimized process conditions of 62% (v=v) as substrate concentration, pH of 5.5, temperature of 32 C, and fermentation time of 37 h. Maximum ethanol concentration (12.64 g=L) was obtained at the optimized conditions in an anaerobic batch fermentation.

Optimization of a synthetic medium for ethanol production by xylose-fermenting Zymomonas mobilis using response surface methodology

“…A report described the application of RSM to the optimization of ethanol production in RM medium with glucose as the sole carbon source for Z. mobilis, obtaining an ethanol yield of 0.5 g/g, which was very close to the predicted value (0.51 g/g) [16]. RSM was also applied to the optimization of ethanol production from waste cashew apple juice [17], sugar cane molasses [15] and carob pod extract [2]. Although optimal ethanol production by wild Z. mobilis was achieved, these complicated media are not suitable for studies on microbial growth, product formation and metabolism.…”

Optimization of polysaccharides extraction from Tetrastigma hemsleyanum Diels et Gilg using response surface methodology

“…The shapes of the contour plots, circular or elliptical, indicated whether the mutual interactions between the variables were significant or not. Circular contour plot indicated that the interactions between the corresponding variables are negligible, while elliptical contour plot indicates that the interactions between the corresponding variables are significant [24]. The relationship between independent and dependent variables was illustrated in tri-dimensional representation of the response surfaces and two-dimensional contour plots generated by the model for yield of polysaccharides, two variables were depicted in one tri-dimensional surface plots while the other variable kept at level zero.…”

Optimization of fermentation conditions for producing Indian rock bee (Apis dorsata) mead using response surface methodology

“…Major problems of fermentation process are that they need a large number ISSN : 0974-9411 (Print), 2231-5209 (Online) All Rights Reserved © Applied and Natural Science Foundation www.ansfoundation.org of experiments and often the models are very complicated to describe the experimental observation (Hajar et al, 2012). Optimization of process condition is one of the most critical stages in the development of an efficient and economic bioprocess (Karuppaiya et al, 2009). The conventional one-factor-at-a-time approach of optimization is not only tiresome but also ignores to merge interaction of each factor.…”

“…There are various advantages in using statistical methodologies in terms of rapid and reliable short listing of process conditions, understanding interaction among them, and a tremendous reduction in total number of experiments, resulting in saving time, glassware, chemicals and manpower (Cheynier et al, 1983). In spite of various advantages, statistical designs have been applied to only limited number of aerobic submerged and solid state fermentation and anaerobic submerged fermentation processes 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 (Karuppaiya et al, 2009). Although many advances in the developments of mead have been made over the last few years, particularly in terms of optimizing ethanol concentration, there is still scope for future development.…”