Comparative Analyses of Select Microbial Growth Inhibited Rate Models

Year : 2024 | Volume :15 | Issue : 01 | Page : 16-24

Chemical Journal

  1. Research Scholar Rivers State University Port Harcourt Nigeria


Food waste is a complex substrate comprising of different mixtures of chemical compounds. The growth rate of micro-organism in such environment will experience inhibition. Consequently, the Monod’s model will not be able to describe the growth rate of its bacteria. The Aiba’s, Andrews and the Haldane’s growth rate models that are accounts for growth rate of bacteria with inhibition were compared. To do this, seven different batch experimentations; each with different initial substrate concentration were carried out at constant temperature. The data obtained during the time course of rection were used to curve fit these model equations using Python software. The results showed that the Aiba’s model had the best fit followed very closely by the Andrew and Haldane’s models which were essentially the same as indicated by the value of their coefficient of correlation. This is an indication that any of these models are suitable for modelling the growth rate of bacteria in a batch reactor using food waste as the substrate. Notwithstanding, due to the formation multiple steady state formation by the Andrew and Haldane’s models, they cannot be used to model a continuous stirred tank reactor. On the other hand, the steady state concentration of the Aiba’s model requires a numerical software for ease of solution.

Keywords: Aiba’s Model, Andrew’s Model, Haldane, Complex Substrate, Growth Rate Models.

[This article belongs to Journal of Modern Chemistry & Chemical Technology(jomcct)]

How to cite this article: Chemical Journal. Comparative Analyses of Select Microbial Growth Inhibited Rate Models. Journal of Modern Chemistry & Chemical Technology. 2024; 15(01):16-24.
How to cite this URL: Chemical Journal. Comparative Analyses of Select Microbial Growth Inhibited Rate Models. Journal of Modern Chemistry & Chemical Technology. 2024; 15(01):16-24. Available from:


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Regular Issue Subscription Original Research
Volume 15
Issue 01
Received March 26, 2024
Accepted April 15, 2024
Published April 16, 2024