Mathematical modeling of molybdenum blue production from Serratia marcescens strain DR.Y10

A. Othman, W. Johari, F. Dahalan, M. Shukor
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引用次数: 4

Abstract

The pollution of heavy metals and toxic xenobiotics has become a central issue worldwide. Bioremediation of these toxicants are being constantly carried out using novel microbes. Molybdenum reduction to molybdenum blue is a detoxification process and mathematical modelling of the reduction process can reveal important parameters such as specific reduction rate, theoretical maximum reduction and whether reduction at high molybdenum concentration affected the lag period of reduction. The used of linearization method through the use of natural logarithm transformation, although popular, is inaccurate and can only give an approximate value for the sole parameter measured; the specific growth rate. In this work, a variety of models for such as logistic, Gompertz, Richards, Schnute, Baranyi-Roberts, Von Bertalanffy, Buchanan three-phase and more recently Huang were utilized for the first time to obtain values for the above parameters or constants. The modified Gompertz model was the best model in modelling the Mo-blue production curve from Serratia marcescens strain DR.Y10 based on statistical tests such as root-mean-square error (RMSE), adjusted coefficient of determination (R2), bias factor (BF), accuracy factor (AF) and corrected AICc (Akaike Information Criterion). Parameters obtained from the fitting exercise were maximum Mo-blue production rate (um), lag time (l) and maximal Mo-blue production (Ymax) of X (h-1), Y (h) and Z (nmole Mo-blue), respectively. The application of primary population growth models in modelling the Mo-blue production rate from this bacterium has become a successful undertaking. The model may also be used in other heavy metals detoxification processes. The parameters constants extracted from this work will be a substantial help for the future development of further secondary models.
粘质沙雷氏菌DR.Y10产钼蓝的数学模型
重金属和有毒外源物污染已成为世界性的中心问题。这些毒物的生物修复正在不断使用新的微生物进行。钼还原为钼蓝是一个脱毒过程,还原过程的数学建模可以揭示比还原率、理论最大还原量以及高钼浓度下的还原是否影响还原滞后期等重要参数。利用自然对数变换的线性化方法虽然流行,但不准确,只能给出唯一测量参数的近似值;特定增长率。在这项工作中,各种各样的模型,如logistic、Gompertz、Richards、Schnute、Baranyi-Roberts、Von Bertalanffy、Buchanan三相和最近的Huang,首次被用来获得上述参数或常数的值。经根均方误差(RMSE)、校正决定系数(R2)、偏倚因子(BF)、精度因子(AF)和校正后的赤池信息准则(Akaike Information Criterion)等统计检验,修正的Gompertz模型是建立粘质沙雷菌DR.Y10产钼曲线的最佳模型。拟合得到的参数分别为X (h-1)、Y (h)和Z (nmol Mo-blue)的最大Mo-blue产率(um)、滞后时间(l)和最大Mo-blue产率(Ymax)。应用初级种群增长模型模拟这种细菌的钼蓝产量已经成为一项成功的事业。该模型也可用于其他重金属解毒过程。从这项工作中提取的参数常数将为进一步的二次模型的发展提供实质性的帮助。
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