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9 Studies on the optimization of submerged fermentation medium and conditions for Tricholoma matsutake
  1. Yanzhen Wang,
  2. Yao Zhang,
  3. Liang Wang,
  4. Dongsheng Yang,
  5. Wenjun Wang,
  6. Lirong Teng
  1. Department of Chemistry and Pharmacy, Zhuhai College of Jilin University, Zhuhai, China


Background Tricholoma matsutake, a popular food and biopharmaceutical in Asia, displays various pharmacological activities. Submerged fermentation is an efficient way to produce mycelia and bioactive metabolites. Consequently, research groups are working to optimize submerged fermentation conditions. This study was conducted in an attempt to optimize the fermentation parameters for T. matsutake and its active ingredients by using statistical and mathematical techniques.

Methods Chemometrics methods were employed to optimize the fermentation medium and conditions. Based on a single-factor optimization strategy, suitable carbon and nitrogen sources were obtained. The key medium components were then identified using a Plackett-Burman design (PBD) and further optimized using a Box-Behnken design (BBD). Response surface methodology (RSM) was further used to optimize the experimental results obtained from BBD. Based on the optimum medium, the culture conditions were further optimized using a single-factor optimization strategy.

Results The optimum components of nutrient medium comprised (g/L): glucose 43.2, peptone 26.9, NaNO3 0.18, (NH4)2SO4 0.36, KH2PO4 2.0, MgSO4 7 H2O 0.5, and vitamin B1 0.15. The best production of mycelium was 22.66 g/L, which was 59% higher than that of the original culture. The suitable culture conditions were: initial pH 4.25, temperature 26° C, culture time 6 days, seed age 3 days, rotating speed 225 rpm, inoculation amount 5%, and 75 mL liquid volume in a 250 mL flask. The best production of mycelium was 24.2 g/L, which was 7.0% higher than that of the original culture.

Conclusions In this study, we used chemometrics methods to optimize the fermentation medium and conditions for T. matsutake. Our finding provides experimental evidence that PBD, BBD and RSM are effective tools for mathematical modeling and factor analysis of a medium optimization process.

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