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An Optimum Fermentation Model Established by Genetic Algorithm for Biotransformation from Crude Polydatin to Resveratrol

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Abstract

Natural resveratrol is widely used in medicine, food, and cosmetic because of its pharmacological properties. Due to its low content in plants, this study was conducted to increase the yield of resveratrol by microorganism transformation. Fungi Aspergillus niger AN-2436 was employed in biotransformation to produce resveratrol from polydatin, and genetic algorithm (GA) was used to optimize the fermentation conditions. A transformation ratio of higher than 95% was achieved in the following conditions: culture temperature of 30.3 °C, inoculum size of 20% (v/v), rotating speed of 147 rpm, and cultivation time of 36 h. Compared with the polydatin absorbance under the experimental conditions obtained by single-factor, orthogonal experiments and average absorbance, the GA provides the optimum experimental conditions, under which the largest transformation rate was achieved. The final transformation product obtained was identified as resveratrol, and it was proved by high-performance liquid chromatography, infrared, mass spectrometry, and nuclear magnetic resonance.

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Authors and Affiliations

  1. State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Beijing, 100029, People’s Republic of China

    Yang Chong & Aixia Yan

  2. College of Life Science and Technology, Beijing University of Chemical Technology, P.O. Box 53, 15 BeiSanHuan East Road, Beijing, 100029, People’s Republic of China

    Yang Chong, Aixia Yan, Xiaoying Yang, Yangliu Cai & Jinchun Chen

Authors
  1. Yang Chong
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  2. Aixia Yan
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  3. Xiaoying Yang
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  4. Yangliu Cai
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  5. Jinchun Chen
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Corresponding author

Correspondence to Jinchun Chen.

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Chong, Y., Yan, A., Yang, X. et al. An Optimum Fermentation Model Established by Genetic Algorithm for Biotransformation from Crude Polydatin to Resveratrol. Appl Biochem Biotechnol 166, 446–457 (2012). https://doi.org/10.1007/s12010-011-9440-7

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  • DOI: https://doi.org/10.1007/s12010-011-9440-7

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