Journal of Microbiology and Biotechnology

The Korean Society for Microbiology and Biotechnology (한국미생물·생명공학회)
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Fuzzy Logic Control of Rotating Drum Bioreactor for Improved Production of Amylase and Protease Enzymes by Aspergillus oryzae in Solid-State Fermentation

  • Sukumprasertsri, Monton (Department of Chemical Engineering, King Mongkut's University of Technology Thonburi) ;
  • Unrean, Pornkamol (Biochemical Engineering and Pilot Plant Research and Development Unit, National Center for Genetic Engineering and Biotechnology (BIOTEC) at King Mongkut's University of Technology Thonburi) ;
  • Pimsamarn, Jindarat (Department of Chemical Engineering, King Mongkut's University of Technology Thonburi) ;
  • Kitsubun, Panit (Biochemical Engineering and Pilot Plant Research and Development Unit, National Center for Genetic Engineering and Biotechnology (BIOTEC) at King Mongkut's University of Technology Thonburi) ;
  • Tongta, Anan (School of Bioresources and Technology, King Mongkut's University of Technology Thonburi)
  • Received : 2012.04.18
  • Accepted : 2012.10.17
  • Published : 2013.03.28
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Abstract

In this study, we compared the performance of two control systems, fuzzy logic control (FLC) and conventional control (CC). The control systems were applied for controlling temperature and substrate moisture content in a solidstate fermentation for the biosynthesis of amylase and protease enzymes by Aspergillus oryzae. The fermentation process was achieved in a 200 L rotating drum bioreactor. Three factors affecting temperature and moisture content in the solid-state fermentation were considered. They were inlet air velocity, speed of the rotating drum bioreactor, and spray water addition. The fuzzy logic control system was designed using four input variables: air velocity, substrate temperature, fermentation time, and rotation speed. The temperature was controlled by two variables, inlet air velocity and rotational speed of bioreactor, while the moisture content was controlled by spray water. Experimental results confirmed that the FLC system could effectively control the temperature and moisture content of substrate better than the CC system, resulting in an increased enzyme production by A. oryzae. Thus, the fuzzy logic control is a promising control system that can be applied for enhanced production of enzymes in solidstate fermentation.

Keywords

References

  1. Aidoo, K. E., R. Handry, and B. J. B. Wood. 1981. Estimation of fungal growth in a solid state fermentation system. Eur. J. Appl. Microbiol. Biotechnol. 12: 6-9. https://doi.org/10.1007/BF00508111
  2. Anson, M. L. 1938. Estimation of pepsin, trypsin, papain, and acthepsin with hemoglobin. J. Gen. Physiol. 22: 79-89. https://doi.org/10.1085/jgp.22.1.79
  3. Babuska, R. and H. B. Verbruggen. 1996. An overview of fuzzy modeling for control. Control Eng. Pract. 4: 1593-1606. https://doi.org/10.1016/0967-0661(96)00175-X
  4. Battaglino, R. A., M. Huergo, A. M. R. Pilosof, and G. B. Bartholamai. 1991. Culture requirement for the production of protease by Aspergillus oryzae in solid-state fermentation. Appl. Microbiol. Biotechnol. 35: 292-296.
  5. Couilard, D. and S. Zhu. 1992. Control strategy for the activated sludge process under shock loading. Water Res. 26: 649-655. https://doi.org/10.1016/0043-1354(92)90241-U
  6. Czogala, E. and W. Pedrycz. 1981. On identification in fuzzy systems and its applications in control problems. Fuzzy Sets Syst. 6: 73-83. https://doi.org/10.1016/0165-0114(81)90081-6
  7. George, J. K. and B. Yuan. 1995. Fuzzy Set Theory Foundations and Applications. Prentice-Hall, New Jersey.
  8. Hardin, M. T., D. A. Mitchell, and T. Howes. 2000. Approach to designing rotating drum bioreactors for solid-state fermentation on the basis of dimensionless design factors. Biotechnol. Bioeng. 67: 274-282. https://doi.org/10.1002/(SICI)1097-0290(20000205)67:3<274::AID-BIT3>3.0.CO;2-I
  9. Honda, H. and T. Kobayashi. 2000. Fuzzy control of bioprocesses. J. Biosci. Bioeng. 89: 401-408.
  10. Koffman, S. J., R. R. Fullmer, and R. C. Brown. 1989. Fuzzy logic control of a fluidized bed combustor. Proceedings of the American Control Conference 3: 3756-3758.
  11. Miller, G. L. 1959. Use of dinitrosalicylic acid reagent for determination of reducing sugar. Anal. Chem. 31: 426-428. https://doi.org/10.1021/ac60147a030
  12. Mitchell, D. A., A. Tongta, D. M. Stuart, and N. Krieger. 2002. The potential for establishment of axial temperature profiles during solid-state fermentation in rotating drum bioreactors. Biotechnol. Bioeng. 80: 114-122. https://doi.org/10.1002/bit.10356
  13. Nagel, J. I., J. Tramper, M. S. N. Bakker, and A. Rinzema. 2000. Temperature control in a continuously mixed bioreactor for solid-state fermentation. Biotechnol. Bioeng. 72: 219-230.
  14. Nakano, K., R. Katsu, K. Tada, and M. Matsumura. 2000. Production of highly concentrated xylitol by Candida magnoliae under a microaerobic condition maintained by simple fuzzy control. J. Biosci. Bioeng. 89: 372-376.
  15. Narahaha, H., Y. Koyama, T. Yoshida, S. Pichangkura, R. Ueda, and H. Taguchi. 1982. Growth and enzyme production in a solid-state culture of Aspergillus oryzae. J. Ferm. Technol. 60: 311-319.
  16. Padmanabham, S., M. V. Ramana, and B. K. Lonsane. 1993. Potential of Aspergillus oryzae CFTRI 1480 for producing proteinase in high titers by solid state fermentation system. Appl. Microbiol. Biotechnol. 40: 499-503.
  17. Postlethwaite, B. E. 1994. A model-based fuzzy controller. Trans. Inst. Chem. Eng. 72: 38-46.
  18. Prior, B. A., J. C. Du Preez, and P. W. Rein. 1992. Environment parameters, 65-85. In H. W. Doelle, D. A. Mitchell, and C. Rolz (eds.). Solid State Cultivation. Elsevier Applied Science, NY.
  19. Sakurai, Y., T. H. Lee, and H. Shiota. 1977. On the convenient method for glucosamine estimation in koji. Agric. Biol. Chem. 41: 619-624. https://doi.org/10.1271/bbb1961.41.619
  20. Shioya, S., K. Shimizu, and T. Yoshida. 1999. Knowledge based design and operation of bioprocess systems. J. Biosci. Bioeng. 87: 261-266.
  21. Stuart, D. M., D. A. Mitchell, M. R. Johns, and J. D. Litster. 1998. Solid-state fermentation in rotation drum bioreactors: Operating variables affect performance through their effects on transport phenomena. Biotechnol. Bioeng. 63: 383-391.
  22. Tong, R. M., M. B. Beck, and A. Laten. 1980. Fuzzy control of activated sludge waste water treatment process. Automatica 16: 659-701.

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