Optimization of fungi co-fermentation for improving anthraquinone contents and antioxidant activity using artificial neural networks.

Journal: Food chemistry
PMID: 31931424

Abstract

The fermentation products of edible fungi are rich in anthraquinones and have a variety of activities, including the antioxidant activity. Because of the large number of combinations, it is very difficult to obtain the optimal multi-strains co-fermentation to improve the yield of anthraquinone. In the present study, an intelligent model based on artificial neural networks (ANNs) using backpropagation (BP) and radial basis function (RBF) algorithms was developed and validated to predict the anthraquinone contents in 136 two fungi and 680 three fungi co-fermented products. After experimental validation of the anthraquinone contents, the mean absolute error and the mean bias error of the results from RBF ANN were lower than those from BP ANN. The results indicated that the anthraquinone contents in A. bisporus, C. comatus and H. erinaceus co-fermentation product was the highest (2.11%). Furthermore, this co-fermentation product showed strong antioxidant activity.

Authors

  • Jiao Yang
    School of Light Industry and Chemical Engineering, Dalian Polytechnic University, Dalian 116034, China; Key Laboratory of Particle & Radiation Imaging of Ministry of Education, Department of Engineering Physics, Tsinghua University, Beijing, China.
  • Yun Huang
    Peking University Sixth Hospital, Beijing, China.
  • Haiyu Xu
    School of Light Industry and Chemical Engineering, Dalian Polytechnic University, Dalian 116034, China.
  • Dongyu Gu
    College of Marine Science and Environment, Dalian Ocean University, Dalian, China. Electronic address: gudongyu@dlou.edu.cn.
  • Fa Xu
    School of Light Industry and Chemical Engineering, Dalian Polytechnic University, Dalian 116034, China.
  • Jintian Tang
    Key Laboratory of Particle & Radiation Imaging of Ministry of Education, Department of Engineering Physics, Tsinghua University, Beijing, China. Electronic address: tangjt@mail.tsinghua.edu.cn.
  • Chen Fang
    State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
  • Yi Yang
    Department of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, Sichuan, China.

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