Microbial growth models: A general mathematical approach to obtain μmax and λ parameters from sigmoidal empirical primary models

Abstract

Empirical sigmoidal models have been widely applied as primary models to describe microbial growth in foods. In predictive microbiology, the maximum specific growth rate (μmax) and the lag phase (λ) are the parameters of some models and have been considered as biological parameters. The objective of the current study was to propose mathematical equations to obtain the parameters μmax and λ for any sigmoidal empirical growth model. In a case study, the performance was compared of two models based on empirical parameters and two models based on biological parameters. These models were fitted to experimental data for Lactobacillus plantarum in six isothermal conditions. Some advantages of the proposed approach were the practical and biological interpretation of these parameters, and the useful information of the secondary modeling describing the dependence of μmax and λ with the temperature.