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Statistical Optimization of Polysaccharides Production by the Lingzhi or Reishi Medicinal Mushroom Ganoderma lucidum
Yan Liu1, Meng-Yuan Jin1, Pei-Wen Mao1
1School of Agriculture and Biology, and Engineering Research Center of Cell & Therapeutic Antibody, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200240, P.R. China.
Abstract:
Ganoderma lucidum is a widely used medicinal mushroom in traditional Chinese medicine that creates a diverse set of bioactive compounds. Highland barley, a typical nutrition-balanced crop, is not convenient for direct consumption but its nutritional characteristics meet the modern requirements of health food. In the present study, barley grains were used as substrates on solid-state fermentation (SSF) of G. lucidum. Statistical optimization of media composition was employed for enhancing the production of polysaccharides. Peptone, medlar, and KH2PO4 were identified as the most important components for producing polysaccharide. Based on the one-factor-at-a-time experimentation, a quadratic regression model with the polysaccharide contents as the response value was established by central composite design (CCD). The results showed that the predicted variables were 2.38% peptone, 1.14% medlar, and 0.25% KH2PO4 for the maximum yield of predicted polysaccharides of 11.64% in the fermented substrate. The experimental polysaccharides obtained using the predicted optimum media composition constituted 11.61% of the fermented substrate, which validates the high degree of accuracy of optimization for enhanced production of polysaccharides by SSF. This study suggested that in the process of barley grains fermentation by G. lucidum for polysaccharides production, the optimized SSF substrate consists of 71.4% barley grains, 2.38% peptone, 1.14% medlar, 0.25% KH2PO4, 2.5% glucose, 0.25% MgSO4 · 7H2O, and 1% CaCO3. According to this study, the strain G. lucidum 00679 showed a good fermentation property by optimizing the media. It might be a candidate industrial strain for further process optimization and scale-up study.
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