Work

Optimal strategies for estimating the parameters of the Baranyi-Ratkowsky model: from (optimal) experiment design to model fitting methods

Year: 2025

Type: article

Abstract: ). Numerical simulations demonstrate that, unlike for two-steps methods, the error of regression from the one-step approach is a realistic estimate of parameter uncertainty/variability, strengthening the case for this method. This motivates restricting the calculation of Optimal Experiment Designs (OEDs) for this approach only. The study clearly demonstrates that the experimental design has a clear impact on parameter dispersion. However, OEDs tend to be impractical, as they focus on conditions that require long experimental runs. Accordingly, a penalty term is introduced in OED definition, resulting in two strategies: to lower the number of experiments at lower temperatures, and to terminate the experiments at lower temperatures before reaching stationary phase. Based on this result, we propose a staggered experimental design that is updated recursively (storage temperature and position of time points) until convergence. Considering that isothermal experiments are still the gold standard in the field, future studies could greatly benefit from these suggestions by minimizing the experimental effort needed to obtain robust estimates for the Baranyi-Ratkowsky model.

Source: Food Research International

DOI: 10.1016/j.foodres.2025.117288

Authors: Alberto Garre, Theocharia Tsagkaropoulou, Silvia Guillén, Kimon Andreas G. Karatzas, Alfredo Palop

Institutions: Universidad Politécnica de Cartagena, University of Reading, Universidad de Zaragoza, Centro de Investigación y Tecnología Agroalimentaria de Aragón

Language: English

Topic: Optimal Experimental Design Methods

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: hybrid

Estimated APC paid: $4,320