Open AccessMathematical Modeling of the growth of Acinetobacter baumannii YNWH 226 on Azo dye Congo red
Author(s) -
I Sabó,
Salihu Yahuza,
Mohd Yunus Shukor
Publication year - 2021
Publication title -
journal of environmental bioremediation and toxicology
Language(s) - English
Resource type - Journals
ISSN - 2289-5884
DOI - 10.54987/jebat.v4i2.626
Subject(s) - gompertz function , confidence interval , akaike information criterion , mathematics , effluent , toxicology , statistics , congo red , chemistry , environmental science , biology , environmental engineering , organic chemistry , adsorption
Industrial effluents (Azo dyes) are brightly coloured, making their disposal into receiving waters undesirable not only because many Azo dyes and their breakdown products are toxic to aquatic life and mutagenic to humans, but also because many Azo dyes and their breakdown products are harmful to aquatic life due to the presence of aromatics and metals, chlorides, and other chemicals. Various kinetic models, including modified Gompertz, Baranyi-Roberts, modified Richards, Von Bertalanffy, modified Logistics, modified Schnute, Buchanan three-phase, and the most recently presented Huang, were used in this study. Based on statistical tests, the modified Schnute model provided the best fit, with the lowest values for RMSE and corrected Akaike Information Criteria (AICc), the greatest value for adjusted R2, and the closest to unity for both Accuracy and Bias Factor. The Modified Schnute parameters such as λ (lag time), µmax (maximum specific bacterial growth rate) and curve fitting parameters α and β (Constant), were found to be -4.39 (95% confidence interval of -77.58 to 68.79), 57.00 (95% confidence interval of -2854.30 to 2968.30), 0.78 (95% confidence interval of -0.34 to 1.89) and 0.96 (95% confidence interval of -0.85 to 2.78, respectively.