Abstract
The complex fermentation process of medicinal filamentous fungus Cinnamomum camphora was modeled by optimization model, and the optimal fermentation medium composition was obtained. The morphological changes in the fermentation process of Anoderma camphora were observed. Artificial neural network (ANN) and response surface methodology (RSM) were used to model the fermentation process of Anoderma camphora, and genetic algorithm (GA) was used to optimize the composition of fermentation medium. The results showed that the ANN model had better fitting ability and predictive ability than RSM model, and the theoretical maximum value of biomass of Cinnamomum camphora was 6.2 g/L by GA algorithm. The optimization method based on ANN-GA can be used to optimize the complex fermentation process of other filamentous fungi to obtain biomass or active metabolites.
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Acknowledgements
This work was supported by grants from The National Natural Science Foundation of China (No. 61862056), the Guangxi Natural Science Foundation (No. 2017GXNSFAA198148) foundation of Wuzhou University(No.2017B001) and Guangxi Colleges and Universities Key Laboratory of Professional Software Technology, Wuzhou University.
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Zheng, M., Gong, H. (2020). Optimization of Fermentation Medium of Camphor Lucidum Based on Artificial Neural Network and Genetic Algorithm. In: Huang, C., Chan, YW., Yen, N. (eds) Data Processing Techniques and Applications for Cyber-Physical Systems (DPTA 2019). Advances in Intelligent Systems and Computing, vol 1088. Springer, Singapore. https://doi.org/10.1007/978-981-15-1468-5_138
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DOI: https://doi.org/10.1007/978-981-15-1468-5_138
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