Optimizing the Conditions for Polysaccharides Ultrasonic-assisted Extraction in Mycelium of Paecilomyces tenuipes Pt196 Using Statistical Approach

摘要

In order to enhance the extraction rate of polysaccharides, a series of statistical approach was used to optimize the ultrasonic-assisted extraction conditions from the mycelium of Paecilomyces tenuipes Pt196. [Method] The optimization of conditions was carried out in two stages. Firstly, the effects of various experimental parameters considered for the investigation (ultrasonic power, ultrasonic time and liquid-solid ratio) were studied using the method of single factor test design experiments. Secondly, a 15-run Box-Behnken design was performed to optimize the extraction conditions of polysaccharides. The experimental results of Box-Behnken design were analyzed by response surface methodology and artificial neural network together with genetic algorithm. [Results] The optimum conditions for polysaccharides extraction obtained by the application of artificial neural network-genetic algorithm were ultrasonic time 345 s, ultrasonic power 320 W and liquid-solid ratio 95 mL·g~(-1). [Conclusions] Artificial neural network-genetic algorithm can effectively select the best extraction conditions of polysaccharides in this study.