Skip to main content
SpringerLink
Log in

Predictive modeling of competitive biosorption equilibrium data

  • Published:
Biotechnology and Bioprocess Engineering Aims and scope Submit manuscript

Abstract

This paper compares regression and neural network modeling approaches to predict competitive biosorption equilibrium data. The regression approach is based on the fitting of modified Langmuir-type isotherm models to experimental data. Neural networks, on the other hand, are non-parametric statistical estimators capable of identifying patterns in data and correlations between input and output. Our results show that the neural network approach outperforms traditional regression-based modeling in correlating and predicting the simultaneous uptake of copper and cadmium by a microbial biosorbent. The neural network is capable of accurately predicting unseen data when provided with limited amounts of data for training. Because neural networks are purely data-driven models, they are more suitable for obtaining accurate predictions than for probing the physical nature of the biosorption process.

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

Similar content being viewed by others

References

  1. Sag, Y. and T. Kutsal (2001) Recent trends in the biosorption of heavy metals: a review.Biotechnol. Bioprocess Eng. 6: 376–385.

    Article  CAS  Google Scholar 

  2. Pagnanelli, F., M. Trifoni, F. Beolchini, A. Exposito, L. Toro, and F. Veglio (2001) Equilibrium biosorption studies in single and multi-metal systems.Process Biochem. 37: 115–124.

    Article  CAS  Google Scholar 

  3. Klimmer, S., H.-J. Stan, A. Wilke, G. Bunke, and R. Buchholz (2001) Comparative analysis of the biosorption of cadmium, lead, nickel, and zinc by algae.Environ. Sci. Technol. 35: 4283–4288.

    Article  CAS  Google Scholar 

  4. Lee, M.-G., J.-H. Lim, and S.-K. Kam (2002) Biosorption characteristics in the mixed heavy metal solution by biosorbents of marine brown algae.Kor. J. Chem. Eng. 19: 277–284.

    Article  CAS  Google Scholar 

  5. Li, Q., S. Wu, G. Liu, X. Liao, X. Deng, D. Sun, Y. Hu, and Y. Huang (2004) Simultaneous biosorption of cad mium (II) and lead (II) ions by pretreated biomass ofPhanerochaete chrysosporium.Sep. Purif. Technol. 34: 135–142.

    Article  CAS  Google Scholar 

  6. Kang, S. Y., J. U. Lee, and K. W. Kim (2005) Metal removal from wastewater by bacterial sorption: kinetics and competition studies.Environ. Technol. 26: 615–624.

    Article  CAS  Google Scholar 

  7. Pagnanelli, F., S. Mainelli, S. De Angelis, and L. Toro (2005) Biosorption of protons and heavy metals onto olive pomace: modeling of competition effects.Water Res. 39: 1639–1651.

    Article  CAS  Google Scholar 

  8. Sag, Y. (2001) Biosorption of heavy metals by fungal biomass and modeling of fungal biosorption: a review.Sep. Purif. Methods 30: 1–48.

    CAS  Google Scholar 

  9. Pagnanelli, F., A. Esposito, and F. Veglio (2002) Multimetallic modeling for biosorption of binary systems.Water Res. 36: 4095–4105.

    Article  CAS  Google Scholar 

  10. Aksu, Z., U. Acikel, E. Kabasakal, and S. Tezer (2002) Equilibrium modeling of individual and simultaneous biosorption of chromium (VI) and nickel (II) onto dried activated sludge.Water Res. 36: 3063–3073.

    Article  CAS  Google Scholar 

  11. Ma, W. and J. M. Tobin (2003) Development of multimetal binding model and application to binary metal biosorption onto peat biomass.Water Res. 37: 3967–3977.

    Article  CAS  Google Scholar 

  12. Chang, J.-S. and J.-C. Huang (1998) Selective adsorption/recovery of Pb, Cu, and Cd with multiple fixed beds containing immobilized bacterial biomass.Biotechnol. Prog. 14: 735–741.

    Article  CAS  Google Scholar 

  13. Texier, A. C., Y. Andres, C. Faur-Brasquet, and P. Le Cloirec (2002) Fixed-bed study for lanthanide (La, Eu, Yb) ions removal from aqueous solutions by immobilizedPseudomonas aeruginosa: experimental data and modelization.Chemosphere 47: 333–342.

    Article  CAS  Google Scholar 

  14. Chu, K. H. (2004) Prediction of two-metal biosorption equilibria using a neural network.Eur. J. Mineral Proc. Environ. Protect. 3: 119–127.

    Google Scholar 

  15. Hornik, K., M. Stinchcombe, and H. White (1989) Multilayer feedforward networks are universal approximators.Neural Netw. 2: 359–366.

    Article  Google Scholar 

  16. Hornik, K. (1991) Approximation capabilities of multilayer feedforward networks.Neural Netw. 4: 251–257.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Chemical and Process Engineering, University of Canterbury, Private Bag 4800, Christchurch, New Zealand

    K. H. Chu

  2. Department of Chemical Engineering, University of Seoul, 130-743, Seoul, Korea

    E. Y. Kim

Authors
  1. K. H. Chu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. E. Y. Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to K. H. Chu.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chu, K.H., Kim, E.Y. Predictive modeling of competitive biosorption equilibrium data. Biotechnol. Bioprocess Eng. 11, 67–71 (2006). https://doi.org/10.1007/BF02931871

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02931871

Keywords

Search

Navigation