Optimization the Fermentation Conditions of Marasmius androsaceus by Desirability Function Method

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