Revisiting secondary model features for describing the shoulder and lag parameters of microbial inactivation and growth models

for Geeraerd; λ and μ for Baranyi), reducing the number of unknown model parameters from four to three. Using data from the scientific literature, we illustrate the applicability of these results, being able to improve the robustness of parameter estimates. The identification of these links are of great relevance for the field of predictive microbiology, as they resolve the uncertainty regarding the functional form of secondary models. Our results also provide a way to assess the validity of those dynamic hypotheses using data gathered under isothermal conditions, something that was hardly possible using data gathered under dynamic conditions. Although this study is limited to the effect of temperature, the general approach and methodology are also applicable to other type of secondary models, so this article can be a blueprint for future studies.