Statistical optimization of culture conditions for enhanced mycelial biomass production using Ganoderma lucidum

Abstract

The study aimed at optimizing the mycelial biomass production of Ganoderma lucidum by submerged fermentation. Plackett-Burman design was used to screen the important growth conditions coupled with central composite design to study the interaction of various variables with one another. Using Plackett-Burman design, temperature, yeast extract concentration, and glucose concentration were found to be significant variables contributing the most to biomass production. The R 2 value of the model was 0.9623 which indicated that the model is good. These three variables were used for further optimization studies by central composite design. Through central composite design, temperature and glucose concentration were found to be the most significant factors affecting the mycelial biomass of G. lucidum. The overall model was found to be statistically significant with a P < 0.0001. Statistical optimization was found to be an effective tool as it helped to increase the biomass production significantly.