Skip to main content

Advertisement

SpringerLink
Log in

Use of Non-linear Empirical Models to Predict the Substrate Degradation, Enzymatic Activity and Cell Growth in a Bioreactor with Aspergillus niger and Sugarcane Bagasse

  • Original Paper
  • Published:
Waste and Biomass Valorization Aims and scope Submit manuscript

Abstract

The present study concerns to the evaluation of non-linear empirical logistic models applied to bioprocess modeling. The substrate degradation, as a function of fermentation time, enzymatic activity, as a function of substrate degradation, and cell growth, as a function of dissolved oxygen concentration were modeled using this proposed approach. Different concentrations of sugarcane bagasse (5, 10, 13, 15, and 20 g L−1) were used in a stirred tank bioreactor with Aspergillus niger. The parameter estimation, based on assays with 5, 10, 13 and 20 g L−1 of sugarcane bagasse, was performed by non-linear least square method and one assay with 15 g L−1 of sugarcane bagasse was used for models’ validation. The results obtained allow to conclude that sugarcane bagasse was efficient as carbon source for cellulases production, requiring no other carbon sources. The use of agricultural waste reduces the production costs of cellulases, making de process feasible. The non-linear empirical models proposed this work allowed to predict the variables. The use of these models could be encouraged to evaluate submerged fermentation's characteristics in new experimental works due to its mathematical simplicity and utility. Besides that, they can provide relevant information from the point of view of process control and optimization because they allow to infer about the inflection point which characterizes the maximum rate of variation of the function.

Graphic Abstract

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Lin, Y., Tanaka, S.: Ethanol fermentation from biomass resources: current state and prospects. Appl. Microbiol. Biotechnol. 69(6), 627–642 (2006)

    Article  Google Scholar 

  2. Sukumaran, R.K., Singhania, R.R., Mathew, G.M., Pandey, A.: Cellulase production using biomass feed stock and its application in lignocellulose saccharification for bio-ethanol production. Renew. Energ. 34(2), 421–424 (2009)

    Article  Google Scholar 

  3. Dhillon, G.S., Oberoi, H.S., Kaur, S., Bansal, S., Brar, S.K.: Value-addition of agricultural wastes for augmented cellulase and xylanase production through solid-state tray fermentation employing mixed-culture of fungi. Ind. Crops Prod. 34(1), 1160–1167 (2011)

    Article  Google Scholar 

  4. Maki, M., Leung, K.T., Qin, W.: The prospects of cellulase-producing bacteria for the bioconversion of lignocellulosic biomass. Int. J. Biol. Sci. 5(5), 500–516 (2009)

    Article  Google Scholar 

  5. Adav, S.S., Cheow, E.S.H., Ravindran, A., Dutta, B., Sze, S.K.: Label free quantitative proteomic analysis of secretome by Thermobifida fusca on different lignocellulosic biomass. J. Proteomics. 75(12), 3694–3706 (2012)

    Article  Google Scholar 

  6. Singh, A., Bajar, S., Bishnoi, N.R., Singh, N.: Laccase production by Aspergillus heteromorphus using distillery spent wash and lignocellulosic biomass. J. Hazard. Mater. 176(1–3), 1079–1082 (2010)

    Article  Google Scholar 

  7. Kogo, T., Yoshida, Y., Koganei, K., Matsumoto, H., Watanabe, T., Ogihara, J., Kasumi, T.: Production of rice straw hydrolysis enzymes by the fungi Trichoderma reesei and Humicola insolens using rice straw as a carbon source. Bioresour. Technol. 233, 67–73 (2017)

    Article  Google Scholar 

  8. Raimbault, M.: General and microbiological aspects of solid substrate fermentation. Electron. J. Biotechnol. 1(3), 114–140 (1998)

    Google Scholar 

  9. Acuña-Argüelles, M.E., Gutiérrez-Rojas, M., Viniegra-González, G., Favela-Torres, E.: Production and properties of three pectinolytic activities produced by Aspergillus niger in submerged and solid-state fermentation. Appl. Microbiol. Biotechnol. 43(5), 808–814 (1995)

    Article  Google Scholar 

  10. Saqib, A.A.N., Hassan, M., Khan, N.F., Baig, S.: Thermostability of crude endoglucanase from Aspergillus fumigatus grown under solid state fermentation (SSF) and submerged fermentation (SmF). Process Biochem. 45(5), 641–646 (2010)

    Article  Google Scholar 

  11. Cunha, F.M., Bacchin, A.L.G., Horta, A.C.L., Zangirolami, T.C., Badino, A.C., Farinas, C.S.: Indirect method for quantification of cellular biomass in a solids containing medium used as pre-culture for cellulase production. Biotechnol. Bioprocess Eng. 17(1), 100–108 (2012)

    Article  Google Scholar 

  12. Florencio, C., Badino, A.C., Farinas, C.S.: Soybean protein as a cost-effective lignin-blocking additive for the saccharification of sugarcane bagasse. Bioresour. Technol. 221, 172–180 (2016)

    Article  Google Scholar 

  13. De Oliveira, G.S.C., Filho, E.X.F.: A review of holocellulase production using pretreated lignocellulosic substrates. Bioenergy Res. 10(2), 592–602 (2017)

    Article  MathSciNet  Google Scholar 

  14. Cunha, F.M., Bacchin, A.L.G., Horta, A.C.L., Zangirolami, T.C., Badino, A.C., Farinas, C.S.: Indirect method for quantification of cellular biomass in a solids containing medium used as pre-culture for cellulase production. Biotechnol. Bioprocess. Eng. 17(1), 100–108 (2012)

    Article  Google Scholar 

  15. Kennedy, M.J., Thakur, M.S., Wang, D.I.C., Stephanopoulos, G.N.: Techniques for the estimation of cell concentration in the presence of suspended solids. Biotechnol. Progress. 8(5), 375–381 (1992)

    Article  Google Scholar 

  16. Ooijkaas, L.P., Tramper, J., Buitelaar, R.M.: Biomass estimation of Coniothyrium minitans in solid-state fermentation. Enzyme Microb. Technol. 22(6), 480–486 (1998)

    Article  Google Scholar 

  17. Koutinas, A.A., Wang, R., Webb, C.: Estimation of fungal growth in complex, heterogeneous culture. Biochem. Eng. J. 14(2), 93–100 (2003)

    Article  Google Scholar 

  18. Prado, F. C., L. R. S., Vandenberghe, C., Lisboa, J., Paca, A.: Pandey, and C. R. Soccol. Relation between citric acid production and respiration rate of Aspergillus niger in solid-state fermentation. Eng. Life Sci. 4(2), 179–186 (2004)

  19. De Carvalho, J.C., Pandey, A., Oishi, B.O., Brand, D., Rodriguez-Léon, J.A., Soccol, C.R.: Relation between growth, respirometric analysis and biopigments production from Monascus by solid-state fermentation. Biochem. Eng. J. 29(3), 262–269 (2006)

    Article  Google Scholar 

  20. Silva, R.G., Cruz, A.J.G., Hokka, C.O., Giordano, R.L.C., Giordano, R.C.: A hybrid neural network algorithm for on-line state inference that accounts for differences in inoculum of Cephalosporium acremonium in fed-batch fermentors. Appl. Biochem. Biotechnol. Enzym. Eng. Biotechnol. 91–93, 341–352 (2001)

    Article  Google Scholar 

  21. Moles, C.G., Mendes, P., Banga, J.R.: Parameter estimation in biochemical pathways: a comparison of global optimization methods. Genome Res. 13(11), 2467–2474 (2003)

    Article  Google Scholar 

  22. Rodriguez-Fernandez, M., Mendes, P., Banga, J.R.: A hybrid approach for efficient and robust parameter estimation in biochemical pathways. BioSystems. 83(2–3 SPEC. ISS.), 248–265 (2006)

  23. Gernaey, K.V., Lantz, A.E., Tufvesson, P., Woodley, J.M., Sin, G.: Application of mechanistic models to fermentation and biocatalysis for next-generation processes. Trends Biotechnol. 28(7), 346–354 (2010)

    Article  Google Scholar 

  24. Gelain, L., Pradella, J.G.C., Costa, A.C.: Mathematical modeling of enzyme production using Trichoderma harzianum P49P11 and sugarcane bagasse as carbon source. Bioresour. Technol. 198, 101–107 (2015)

    Article  Google Scholar 

  25. Liu, J.Z., Weng, L.P., Zhang, Q.L., Xu, H., Ji, L.N.: A mathematical model for gluconic acid fermentation by Aspergillus niger. Biochem. Eng. J. 14(2), 137–141 (2003)

    Article  Google Scholar 

  26. Mandels, M., Weber, J.: The production of cellulases. Adv Chem. 95, 391–414 (1969)

    Article  Google Scholar 

  27. Ghose, T.K.: Measurement of cellulase activities. Pure Appl Chem. 59(2), 257–268 (1987)

    Article  Google Scholar 

  28. Pinto, J.C., Laje, P.L.C.: Numerical Methods in Chemical Engineering Problems. E-papers, Rio de Janeiro (2001)

    Google Scholar 

  29. Bader, J., Klingspohn, U., Bellgardt, K.H., Schügerl, K.: Modelling and simulations of the growth and enzyme production of Trichoderma reesei Rut C30. J. Biotechnol. 29(1–2), 121–135 (1993)

    Article  Google Scholar 

  30. Mohana, S., Acharya, B.K., Madamwar, D.: Distillery spent wash: Treatment technologies and potential applications. J. Hazard. Mater. 163(1), 12–25 (2009)

    Article  Google Scholar 

  31. Florentino, H.O., Biscaro, A.F.V., Passos, J.R.S.: Sigmoidal functions applied in the determination of specific methanogenic activity—SMA. Rev. Bras. Biom. 28(1), 141–150 (2010)

    Google Scholar 

  32. Carrillo, M., González, J.M.: A new approach to modelling sigmoidal curves. Technol. Forecast. Soc. Chang. 69(3), 233–241 (2002)

    Article  Google Scholar 

  33. Suresh, S., Khan, N.S., Srivastava, V.C., Mishra, I.M.: Kinetic Modeling and sensitivity analysis of kinetic parameters for L-glutamic acid production using Corynebacterium glutamicum. Int. J. Chem. React. Eng. 7, A89 (2009)

    Google Scholar 

  34. Tian, X., Shen, Y., Zhuang, Y., Zhao, W., Hang, H., Chu, J.: Kinetic analysis of sodium gluconate production by Aspergillus niger with different inlet oxygen concentrations. Bioprocess Biosyst. Eng. 41(11), 1697–1706 (2018)

    Article  Google Scholar 

  35. Zhang, Q., Sun, J., Wang, Z., Hang, H., Zhao, W., Zhuang, Y., Chu, J.: Kinetic analysis of curdlan production by Alcaligenes faecalis with maltose, sucrose, glucose and fructose as carbon sources. Bioresour. Technol. 259, 319–324 (2018)

    Article  Google Scholar 

  36. Díaz-Godínez, G., Soriano-Santos, J., Augur, C., Viniegra-González, G.: Exopectinases produced by Aspergillus niger in solid-state and submerged fermentation: a comparative study. J. Ind. Microbiol Biotechnol. 26(5), 271–275 (2001)

    Article  Google Scholar 

  37. Schwaab, M., Biscaia, E.C., Jr., Monteiro, J.L., Pinto, J.C.: Nonlinear parameter estimation through particle swarm optimization. Chem. Eng. Sci. 63(6), 1542–1552 (2008)

    Article  Google Scholar 

  38. Edgar, T.F., Himmelblau, D.M.: Optimization of Chemical Processes. McGraw-Hill, New York (1988)

    Google Scholar 

  39. Montgomery, D.C., Runger, G.C.: Applied Statistics and Probability for Engineers. Wiley, New Jersey (2018)

    MATH  Google Scholar 

  40. Atala, D.I.P., Costa, A.C., Maciel, R., Maugeri, F.: Kinetics of ethanol fermentation with high biomass concentration considering the effect of temperature. Appl. Biochem. Biotechnol. Enzym. Eng. Biotechnol. 91–93, 353–365 (2001)

    Article  Google Scholar 

Download references

Acknowledgements

The authors thank the financial support from Foundation for Research Support of Espírito Santo (FAPES), Federal University of Espírito Santo (UFES) and by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES)—Finance Code 001.

Author information

Authors and Affiliations

  1. Postgraduate Program in Energy, Federal University of Espírito Santo, São Mateus, Espírito Santo, Brazil

    Thais C. Catelan & Laura M. Pinotti

  2. Department of Engineering and Technology, Federal University of Espirito Santo, São Mateus, Espírito Santo, Brazil

    Vinícius B. Soares

Authors
  1. Thais C. Catelan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Laura M. Pinotti
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Vinícius B. Soares
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Vinícius B. Soares.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Catelan, T.C., Pinotti, L.M. & Soares, V.B. Use of Non-linear Empirical Models to Predict the Substrate Degradation, Enzymatic Activity and Cell Growth in a Bioreactor with Aspergillus niger and Sugarcane Bagasse. Waste Biomass Valor 12, 4433–4440 (2021). https://doi.org/10.1007/s12649-020-01337-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12649-020-01337-2

Keywords

Search

Navigation