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Abstract: Response surface methodology (RSM) is the most preferred method for fermentation media optimization so far. In last two decades, artificial neural network-genetic algorithm (ANN-GA) has come up as one of the most efficient method for empirical modeling and optimization, especially for non-linear systems. This paper presents the comparative studies between ANN-GA and RSM in fermentation media optimization. Fermentative production of biopolymer scleroglucan has been chosen as case study. The yield of scleroglucan was modeled and optimized as a function of four independent variables (media components) using ANN-GA and RSM. The optimized media produced 16.22±0.44g/l scleroglucan as compared to 7.8±0.54g/l with unoptimized medium. Two methodologies were compared for their modeling, sensitivity analysis and optimization abilities. The predictive and generalization ability of both ANN and RSM were compared using separate dataset of 17 experiments from earlier published work. The average % error for ANN and RSM models were 6.5 and 20 and the CC was 0.89 and 0.99, respectively, indicating the superiority of ANN in capturing the non-linear behavior of the system. The sensitivity analysis performed by both methods has given comparative results. The prediction error in optimum yield by hybrid ANN-GA and RSM were 2% and 8%, respectively. [Copyright &y& Elsevier]

Abstract: Submerged fermentation was carried out for the production of scleroglucan by Sclerotium rolfsii MTCC 2156 using complex media, such as coconut water, sugarcane molasses and sugarcane juice at 28±2°C and 180rpm for 72h. Sugarcane juice gave maximum scleroglucan production of 23.87g/l as compared to 12.58 and 18.45g/l with coconut water and sugarcane molasses, respectively. Utilization of these substrates would be ecologically sound and economically advantageous. [Copyright &y& Elsevier]

Abstract: The aim of this work was to study the effect of addition of different amino acids and sugar nucleotides as metabolic precursors on the production of scleroglucan. A maximum yield of 20.00g/l and 22.32g/l was obtained with optimized media supplemented with l-lysine (1.1mM) and uridine mono-phosphate (UMP), respectively as compared to 16.52g/l scleroglucan achieved with the control in the absence of metabolic precursors. [Copyright &y& Elsevier]

Abstract: Scleroglucan, a neutral homopolysaccaride consisting of a linear chain of β-d-(1-3)-glucopyranosyl and β-d-(1-6)-glucopyranosyl groups, was produced by pure culture fermentation from Sclerotium rolfsii MTCC 2156 by submerged culture. Fermentation process was optimized in two steps. In the first step, one-factor-at-a-time method was used to investigate the effects of medium constituents such as carbon and nitrogen sources. In the second step, concentration of medium components was optimized using an L16-orthogonal array method. In all, 10 different carbon sources and eight different nitrogen sources were evaluated. Maximum yield of 16.58g/l was obtained in a medium containing sucrose as a carbon source and sodium nitrate and yeast extract as nitrogen source. [Copyright &y& Elsevier]