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Modeling the Kinetics of Complex Systems: Enzymatic Hydrolysis of Lignocellulosic Substrates

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Abstract

Lignocellulosic biomass is mainly composed of cellulose, hemicellulose, and lignin. Fuzzy logic, in turn, is a branch of many-valued logic based on the paradigm of inference under vagueness. This paper presents a methodology, based on computational intelligence, for modeling the kinetics of a complex reactional system. The design of a fuzzy interpolator to model cellulose hydrolysis is reported, within the perspective of applying kinetic models in bioreactor engineering. Experimental data for various types of lignocellulosic materials were used to develop the interpolator. New experimental data from the enzymatic hydrolysis of a synthetic substrate, on the other hand, were used to validate the methodology. The accuracy of the results indicates that this is a promising approach to extend the application of models fitted for specific situations to different cases, thus enhancing their generality.

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References

  1. Sun, Y., & Cheng, J. (2002). Hydrolysis of lignocellulosic materials for ethanol production: a review. Bioresource Technology, 83, 1–11.

    Article  CAS  Google Scholar 

  2. Eklund, R., Galbe, M., & Zacchi, G. (1990). Optimization of temperature and enzyme concentration in the enzyme saccharification of steam-pretreated willow. Enzyme and Microbial Technology, 12, 225–228.

    Article  CAS  Google Scholar 

  3. Granda, C. B. (2007). Enzymatic hydrolysis of lime-pretreated corn stover and investigation of the HCH-1 Model: Inhibition pattern, degree of inhibition, validity of simplified HCH-1 Model. Bioresource Technology, 98, 2969–2977.

    Article  Google Scholar 

  4. Hahn-Hagerdal, B., Galbe, M., Gorwa-Grauslund, M. F., Lidén, G., & Zacchi, G. (2006). Bio-ethanol—the fuel of tomorrow from the residues of today. Trends in Biotechnology, 24, 549–556.

    Article  CAS  Google Scholar 

  5. Pandey, A., Soccol, C. R., Nigam, P., Brand, D., Mohan, R., & Roussoss, S. (2000). Biotechnology potential of agro-industrial residues. I: sugarcane bagasse. Bioresource Technology, 74, 69–80.

    Article  CAS  Google Scholar 

  6. Hamelinck, C. N., Hooijdonk, G. V., & Faaij, A. P. C. (2005). Ethanol from lignocellulosic biomass: techno-economic performance in short-, middle- and long-term. Biomass and Bioenergy, 28, 384–410.

    Article  CAS  Google Scholar 

  7. Rabelo, S. C. (2007). Avaliação do desempenho do pré-tratamento com peroxide de hidrogênio alcalino para a hidrólise enzimática de cana-de-açúcar. Dissertation. State University of Campinas.

  8. Cunha, C. M., Silva, F. T. (2001). Characterization of carbohydrates present in hydrolyzate obtained from sugar cane bagasse pretreated by explosion. In: 6th Brazilian Symposium Chemistry Lignins and other Wood Components, VII, pp. 221-226.

  9. Gámez, S., González-Cabriales, J. J., Ramírez, J. A., Garrote, G., & Vázquez, M. (2006). Study of hydrolysis of sugar cane bagasse using phosphoric acid. Journal of Food Engineering, 74, 78–88.

    Article  Google Scholar 

  10. Laser, M., Schulman, D., Allen, S. G., Lichwa, J., Antal, M. J., Jr., & Lynd, L. R. (2002). A comparison of liquid hot water and steam pretreatments of sugar cane bagasse for bioconversion to ethanol. Bioresource Technology, 81, 33–44.

    Article  CAS  Google Scholar 

  11. Vallander, L., & Eriksson, K. E. L. (1985). Enzymatic saccharification of pretreated wheat straw. Biotechnology and Bioengineering, 27, 650–659.

    Article  CAS  Google Scholar 

  12. Sousa, R., Jr., Carvalho, M. L., Giordano, R. L. C., & Giordano, R. C. (2011). Recent trends in the modeling of cellulose hydrolysis. Brazilian Journal of Chemical Engineering, 28, 545–564.

    Article  CAS  Google Scholar 

  13. Zhang, Y. H. P., & Lynd, L. R. (2004). Toward an aggregated understanding of enzymatic hydrolysis of cellulose: noncomplexed cellulose systems. Biotechnology and Bioengineering, 88, 797–824.

    Article  CAS  Google Scholar 

  14. Cavalcanti-Montaño, I. D., Suarez, C. A. G., Rodríguez-Zúñiga, U. F., Giordano, R. L. C., Giordano, R. C., & Sousa, R., Jr. (2013). Optimal bioreactor operational policies for the enzymatic hydrolysis of sugarcane bagasse. Bioenergy Research, 6, 776–785.

    Article  Google Scholar 

  15. Bezerra, R. M. F., & Dias, A. A. (2004). Discrimination among eight modified Michaelis-Menten kinetics models of cellulose hydrolysis with a large range of substrate/enzyme ratios. Applied Biochemistry and Biotechnology, 112, 173–184.

    Article  CAS  Google Scholar 

  16. Carrillo, F., LIS, M. J., Colom, X., López-Mesas, M., & Valldeperas, J. (2005). Effect of alkali pretreatment on cellulose hydrolysis of wheat straw: Kinetic study. Process Biochemistry, 40, 3360–3364.

    Article  CAS  Google Scholar 

  17. Chrastil, J. (1988). Determination of the first order consecutive reaction rate constants from final products. Computers and Chemistry, 12, 289–292.

    Article  CAS  Google Scholar 

  18. Chrastil, J. (1988). Enzymic product formation curves with the normal or diffusion limited reaction mechanism and in the presence of substrate receptors. International Journal of Biochemistry, 20, 683–693.

    Article  CAS  Google Scholar 

  19. Carvalho, M. L., Sousa, R., Jr., Rodríguez-Zúñiga, U. F., Suarez, C. A. G., Rodrigues, D. S., Giordano, R. C., et al. (2013). Kinetic study of the enzymatic hydrolysis of sugarcane bagasse. Brazilian Journal of Chemical Engineering, 30, 437–447.

    Article  CAS  Google Scholar 

  20. Carvalho, M. (2011). Estudo cinético da hidrólise enzimática de celulose de bagaço de cana-de-açúcar. Dissertation, Federal University of Sao Carlos.

  21. Adney, B., Baker, J. Chemical analysis and testing task: https://engineering.purdue.edu/LORRE/research/LAP-006.pdf. Revised 2013.

  22. Ghose, T. K. (1987). Measurement of cellulase activity. Pure and Applied Chemistry, 59, 257–268.

    CAS  Google Scholar 

  23. Miller, G. L. (1959). Use of dinitrosalicylic acid reagent for determination of reducing sugar. Analytical Chemistry, 31, 426–428.

    Article  CAS  Google Scholar 

  24. Bezdek, J. (1981). Fuzzy models and algorithms for pattern recognition and image processing. New York: Wiley.

    Google Scholar 

  25. Nelles, O. (2001). Nonlinear system identication. Berlin: Springer.

    Book  Google Scholar 

  26. Chiu, S. L. (1994). Fuzzy model identification based on cluster estimation. Journal of Intelligent and Fuzzy Systems, 2, 267–278.

    Google Scholar 

  27. Bezdek, J. C., Ehrlich, R., et al. (1984). FCM: the fuzzy c-means clustering algorithm. Computers and Geosciences, 10, 191–203.

    Article  Google Scholar 

  28. Pedrycz, W. (1990). Processing in relation structures: fuzzy relational equations. Fuzzy Sets and Systems, 40, 87–100.

    Google Scholar 

Download references

Acknowledgments

The authors would like to thank the support of Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP-BIOEN), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES).

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Correspondence to Ruy de Sousa Jr..

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Suarez, C.A.G., Cavalcanti-Montaño, I.D., da Costa Marques, R.G. et al. Modeling the Kinetics of Complex Systems: Enzymatic Hydrolysis of Lignocellulosic Substrates. Appl Biochem Biotechnol 173, 1083–1096 (2014). https://doi.org/10.1007/s12010-014-0912-4

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  • DOI: https://doi.org/10.1007/s12010-014-0912-4

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