Investigating the Growth of Bacteria using Double Sigmoid Model with Reparameterization

Abstract

The growth of an organism can be modeled using a growth curve. However, bacteria's growth pattern differs from other organisms. Bacterial growth is divided into four phases: lag, logarithmic, stationary, and death. The experts re-parameterized the growth curve to match the growth phase of the bacteria. Bacterial growth patterns generally do not show a single sigmoid pattern but form two curves. Therefore, the double sigmoid model is more suitable. This study modeled the growth of the Pseudomonas putida bacteria by observing the optical density of the medium. Model parameters are estimated using the Non-Linear Least Square (NLS) method with the Gauss-Newton algorithm. The modeling results show that the double sigmoid model fits the growth curve of Pseudomonas putida better than the single sigmoid model. The Double Logistic model outperforms all models with the highest adjusted R2 and the smallest RMSE, AIC, and BIC values.