A random effect multiplicative heteroscedastic model for bacterial growth

Background: Predictive microbiology develops mathematical models that can predict the growth rate of a microorganism population under a set of environmental conditions. Many primary growth models have been proposed. However, when primary models are applied to bacterial growth curves, the biological variability is reduced to a single curve defined by some kinetic parameters (lag time and growth rate), and sometimes the models give poor fits in some regions of the curve. The development of a prediction band (from a set of bacterial growth curves) using non-parametric and bootstrap methods permits to overcome that problem and include the biological variability of the microorganism into the modelling process. Results: Absorbance data from Listeria monocytogenes cultured at 22, 26, 38, and 42

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Ricardo Cao, Mario Francisco-Fernández, Emiliano J. Quinto
• Keywords: Bacterial Growth, BMCBI 2010, Growth Rate, Prediction Bands