Evaluation of Several Mathematical Models for Fitting the Growth and Kinetics of the Catechol-degrading Candida parapsilopsis: Part 1 (Journal of Environmental Bioremediation and Toxicology, 2014)
Predictive microbiology is a field often associated with food microbiology as it allows prediction of food spoilage. One of the key features of bacterial growth on solid and complex food under low water and oxygen is a long lag time. This long lag time is often observed in bacteria growing on toxic xenobiotics. In this work we modelled the growth of the yeast strain of Candida parapsilopsis based on available published work in the literature using several growth modelssuch as modified logistic, modified Gompertz, modified Richards, modified Schnute, Baranyi- Roberts, Von Bertalanffy, Huang and the Buchanan three-phase linear model. Statistical analysis results indicated that the Buchanan model was the best with highest adjusted R2, lowest RMSE and AICc values and Bias and Accuracy Factor values closest to unity. The fitted value of maximal growth rate showed a decline when the concentration of catechol was higher than 114 mg/L indicating substrate inhibition. The other fitted parameters such as lag period and maximal growth asymptote showed a general increase and a general decrease for the former and latter parameters, respectively. The results from this work can be used in the further optimization works of this alga in the future.
Keywords: growth curve, yeast, Candida parapsilopsis, Buchanan three-phase, statistical analysis