Issue:Application of the intercriteria analysis for selection of growth rate models for cultivation of strain Kluyveromyces marxianus var. lactis MC 5

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Title of paper: Application of the intercriteria analysis for selection of growth rate models for cultivation of strain Kluyveromyces marxianus var. lactis MC 5
Author(s):
Mitko Petrov
Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, 105 Acad. George Bonchev St., Sofia 1113, Bulgaria
mpetrovAt sign.pngbiomed.bas.bg
Tatiana Ilkova
Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, 105 Acad. George Bonchev St., Sofia 1113, Bulgaria
tanjaAt sign.pngbiomed.bas.bg
Presented at: 11th International Workshop on Intuitionistic Fuzzy Sets, Banská Bystrica, Slovakia, 30 Oct. 2015
Published in: "Notes on IFS", Volume 21, 2015, Number 5, pages 49—60
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Abstract: In this study we have applied a new method named Intercriteria Analysis (ICrA) to evaluation and selection of growth rate models for a batch cultivation of the strain Kluyweromyces marxianus var. lactis MC 5. Different unstructured models (Monod, Mink, Tessier, Aiba, Andrews, Haldane, Luong, Edward and Han-Levenspiel) have been considered in order to explain the cell growth kinetics from the lactose and oxygen. The application of the ICrA for the growth rate from lactose and oxygen has shown that there are many strong correlation connections between the investigation models. the models have been reduced At growth rate from lactose only into two – Monod and Mink, аnd at growth rate from oxygen – into three – Mink, Tessier, and Haldane. In this way the application of the ICrA has permitted us to investigate only the combination of groups of models – Monod for lactose and Mink, Tessier, and Haldane for oxygen, as well as Mink with the same models for oxygen.
Keywords: Intercriteria analysis, Consonance, Growth rate models, Intuitionistic fuzzy sets, Index matrix, Intuitionistic fuzzy pairs.
AMS Classification: 03E72, 93A30, 92C45.
References:
  1. Angelov, P., E. Simova, D. Beshkova & G. Frengova (1996) Control of cell protein synthesis from Kluyveromyces marxianus var. lactis MC5. Biotechnology and Biotechnological EQ., 10, 44–50.
  2. Angelov, P. (2002) Evolving Rule-Based Models: A Tool for Design of Flexible Adaptive Systems, Springer Verlag, Heidelberg.
  3. Atanassov, K., D. Mavrov, V. Atanassova (2014) Intercriteria decision making: A new approach for multicriteria decision making, based on index matrices and intuitionistic fuzzy sets, Issues in IFSs and GNs, 11, 1–8.
  4. Atanassov, K. (2014) Index Matrices: Towards an Augmented Matrix Calculus, Springer, Cham.
  5. Atanassov, K. (2012) On Intuitionistic Fuzzy Sets Theory, Springer, Berlin.
  6. Atanassov, K., E. Szmidt & J. Kacprzyk (2013) On intuitionistic fuzzy pairs, Notes on Intuitionistic Fuzzy Sets, Vol. 19(3), 1–13.
  7. Atanassov, K., E. Szmidt, J. Kacprzyk & V. Atanassova (2015), Intuitionistic fuzzy approach to the preference degree estimations, Comptes rendus de l’Academie bulgare des Sciences, Vol. 68(1), 25–32.
  8. Atanassova, V., L. Doukovska, K. Atanassov & D. Mavrov (2014) InterCriteria decision making approach to EU member states competitive analysis. Proc. of 4th Int. Symposium on Business Modeling and Software Design, Luxembourg, Grand Duchy of Luxembourg, 24–26 June 2014, 289–294.
  9. Atanassova, V., L. Doukovska, D. Mavrov & K. Atanassov (2014) InterCriteria decision making approach to EU member states competitiveness analysis: Temporal and threshold analysis. Proceedings of 7th IEEE International Conference Intelligent Systems IS’2014, 24-26 September 2014, Warsaw, Poland, Vol. 1, 97–106.
  10. Ilkova, T. & M. Petrov (2015) Application of InterCriteria analysis to the Mesta River pollution modelling, Notes on Intuitionistic Fuzzy Sets, 21(2), 118–125.
  11. Ilkova, T. & M. Petrov (2015) Intercriteria analysis for identification of Escherichia coli fed-batch mathematical model, Journal of International Scientific Publications: Materials, Methods & Technology, 9, 598–608.
  12. Petrov, M., T. Ilkova & J. Vanags (2015) Modelling of batch whey cultivation by strain Kluyveromyces marxianus var. lactis MC 5 with investigation of mass transfer processes in the bioreactor, International J. Bioautomation, 19(1), S81–S92.
  13. Wang, F.-S., S. Tzu-Liang & J. Horng-Jhy (2001) Hybrid differential evolution for problems of kinetic parameter estimation and dynamic optimization of an ethanol fermentation process, Ind. Eng. Chem. Res., 40, 2876–2885.
  14. Vuchkov, I. & S. Stoyanov (1986) Mathematical modelling and optimisation of technological objects, Technique, Sofia.
  15. Giridhar, R. & A. Srivastava (2002) Model based constant feed fed-batch L-sorbose production process for improvement in L-sorbose productivity, Chem. Biochem. Eng. Q., 14(4), 133–140.
  16. Atanassov, K., V. Atanassova & G. Gluhchev (2015) Intercriteria Analysis: Ideas and problems, Notes on Intuitionistic Fuzzy Sets, 21(1), 81–88.
  17. Petrov, M., T. Ilkova, & S. Tzonkov (2005) Modeling and fuzzy optimization of whey fermentation by Kluyveromyces marxianus var. lactis MC 5, Chem. Biochem. Eng. Q., 19(1), 49–55.
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