Optimization the fermentation conditions of marasmius androsaceus by desirability function method

Abstract

The objective of this study is to optimize fermentation conditions for large production of Marasmius androsaceus biomass and metablites production. The desirability function and chemometric methods were applied to optimize the fermentation conditions of M. androsaceus fermentation conditions in a 500 mL shake flask. Based on the desirability function methods, Plackett-Burman (PB) design was employed to optimize fermentation process parameters (culturing temperature, rotating speed, culture time, initial pH, inoculum size, inoculum age and inoculum volume). Culturing temperature, rotating speed were found to significantly impact Da value which were chosen as assessment criteria and were further optimized by Box-Behnken (BB) design. The response surface regression (RSM) and artificial neural network-genetic algorithm (ANN-GA) were employed to analyze the results. Finally, the optimum M. androsaceus submerged fermentation condition in a 500 mL shake flask were obtained as follows: initial pH of 6.0, rotating speed of 169 rpm, culture time 6.57 days, culture temperature 26.7 °C, inoculum size of 5%, inoculum age of 4 days and a loading volume of 200/500 mL, then the predictive Da value was 0.5059 and the average experimental Da value was 0.4941. The model possesses successfully fitness and more this study also provides experimental evidence that PB design and RSM are effective tools for mathematical modeling and factor analysis of optimization the fermentation process.