(untitled) (Bulletin of Environmental Science and Sustainable Management (e-ISSN 2716-5353), 2022)
In the long run, bioremediation is the utmost cost-effective way, particularly at low concentrations while other methods like physical or chemical procedures would be ineffective, for the elimination of heavy metals and organic pollutants. The process of reducing molybdenum (sodium molybdate) with an oxidation state of (VI) to molybdenum blue (oxidation state from V to VI) serves as a form of detoxification. Important characteristics, such as specific reduction rate, theoretical reduction maximum, and the lag duration of reduction, can be shown by mathematical modeling of the reduction process. While natural logarithm transformation is a common linearization approach, it is not precise and can only provide a rough estimate of the most important single measurable parameter; the specific growth rate. In this study, for the first time, values for the aforementioned parameters or constants were calculated using a wide range of models, including the logistic, Gompertz, Richards, Schnute, Baranyi-Roberts, Buchanan three-phase, von Bertalanffy and most recently, the Huang model. Based on statistical tests including root-mean-square error (RMSE), bias factor (BF), adjusted coefficient of determination (adjR2), accuracy factor (AF), and corrected Akaike information criterion (AICc), the logistics model was found to be the best model for representing the Mo-blue production curve of Bacillus sp. strain khayat. The fitting technique resulted in the calculation of three parameters: specific reduction rate (h-1), Lag period (h), and maximum Mo-blue production (nmole Mo-blue). In this study, we utilize a mathematical technique to determine the reduction parameters for Mo-blue production from sodium molybdate. The calculated parameter constants will be used to create secondary models, such as the influence of substrate and environment on Mo-blue synthesis.