Kinetic Models of Microbial Growth Inhibition of Pseudomonas sp. on Acrylamide
DOI:
https://doi.org/10.54987/jebat.v7i1.995Keywords:
Substrate Inhibition, Kinetics models, Acrylamide, Haldane, Han-LevenspielAbstract
In this study, various secondary growth models, including Luong, Yano, Teissier-Edward, Aiba, Haldane, Monod, Han, and Levenspiel, were employed to model the inhibitory effect of high acrylamide concentrations on the growth rate of Pseudomonas sp. strain DrY135. Following thorough statistical analyzes, the ten bacterial growth models ranged from very poor fits, as observed with the Luong, Monod, and Webb models, to exceptionally good fits for the other models. The Han-Levenspiel model was superior, demonstrating minimal RMSE, BIC, HQC, and modified adj.R2 values, except for the MPSD and AICc statistics. Moreover, the model's Accuracy Factor (AF) and Bias Factor (BF) values were close to unity, indicating a good fit between predicted and observed data. Experimental research indicates that acrylamide is detrimental and impedes growth at elevated concentrations. The Han-Levenspiel constants, including the maximal degradation rate (max), half-saturation constant (Ks), maximal substrate concentration tolerated (Sm), and curve-fitting parameters (m and n), were determined to be 16.704 h−1, 3943.26 mg/L, 125.58 mg/L, 3.1469, and 0.9835, respectively. However, these values were accompanied by very large confidence intervals, likely due to the limited dataset. Similarly, the fitted parameters of other models also exhibited large 95% confidence intervals, likely for the same reason. Future remedies include incorporating additional data points to improve fitting accuracy. These enhanced constants can serve as significant inputs for future modeling projects. Furthermore, integrating substrate inhibition kinetics into risk assessment models can enhance the precision of hazard evaluation for toxic substrates at contaminated sites. This knowledge is vital for informed decision-making in environmental management.
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