Modelsplays a vital role in understanding microbial growth in wastewater treatment and bioremediation processes, as is, in safe food production, microbe-mediated and mining among others. However, it is also gaining popularity inoptimization designs. A study was undertaken to predict microbial growth in anaerobic digestor using Gompertz and logistic models. The objective was to determine the growth parameters and compare the performance of these primary models in anaerobic digestion(AD). Three isolates from brewery waste water closely related to Bacillus subtilis, Bacillus methylotrophicus and Lysinibacillus species were used as inoculum and their growth monitored based on optical density(OD) at the same conditions but different initial cell concentration. Microbial population growth data were fitted to the modified logistic function and Gompertz function using Marquardt algorithm and the comparison was based on both the Alkaike Information Criterion value (AIC), Residual Sum of Squares and R2values. Allthe models had a high goodness of fit (R2> 0.93) for all growth curves for three isolates, in all the cases. However, Gompertz model was accepted in 66.67% of the cases based on the AIC values and also supported by the R2> 0.95values and small RSS values. The models providedknowledge to define the growth of the methanogenic community in a bio-digester as a function of time, which could beused for maximum utilization of the exponential phase of the microbial growth for production of biogas. This indicates the practicality of applying Gompertz model to actual anaerobic digestion of brewery waste water. Growth parameters like the rate of increase in the number of cells per unit time and lag time were determined from the models.
Anaerobic digestion, Biogas, Gompertz, Logistic, Microbial growth Models
Sylvia Injete Murunga , Festus Were "Predicting Microbial Growth In Anaerobic Digester Using Gompertz And Logistic Models" Iconic Research And Engineering Journals Volume 3 Issue 4 2019 Page 198-205
Sylvia Injete Murunga , Festus Were "Predicting Microbial Growth In Anaerobic Digester Using Gompertz And Logistic Models" Iconic Research And Engineering Journals, 3(4)