Guidelines for the design of (optimal) isothermal inactivation experiments
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Peñalver Soto, José Lucas; Garre Pérez, Alberto; Esnoz Nicuesa, Arturo; Fernández Escámez, Pablo Salvador; Egea Larrosa, José AlbertoKnowledge Area
Tecnología de los AlimentosSponsors
The financial support of this research work was provided by the Ministry of Science, Innovation and Universities of the Spanish Government and European Regional Development Fund (ERDF) through project AGL2017-86840-C2-1-R, as well as the Fundación Séneca. Alberto Garre is grateful to Fundación Séneca for awarding him a post-doctoral grant (Ref: 20900/PD/18). The authors wish to acknowledge Ms. Carmen M. Ruiz Sáez for her participation in the initial steps of this research.Publication date
2019Publisher
ElsevierBibliographic Citation
Peñalver-Soto, J. L., Garre, A., Esnoz, A., Fernández, P. S., & Egea, J. A. (2019). Guidelines for the design of (optimal) isothermal inactivation experiments. Food Research International, 126, 108714. DOI: 10.1016/j.foodres.2019.108714 3Keywords
Parameter estimationPredictive microbiology
Pasteurization
Microbial kinetics
Robust statistics
Abstract
Kinetic models are nowadays a basic tool to ensure food safety. Most models used in predictive microbiology have model parameters, whose precision is crucial to provide meaningful predictions. Kinetic parameters are usually estimated based on experimental data, where the experimental design can have a great impact on the precision of the estimates. In this sense, Optimal Experiment Design (OED) applies tools from optimization and information theory to identify the most informative experiment under a set of constrains (e.g. athematical model, number of samples, etc). In this work, we develop a methodology for the design of optimal isothermal inactivation experiments. We consider the two dimensions of the design space (time and temperature), as well as a temperature-dependent maximum duration of the experiment. Functions for its application have been included in the bioOED R package.We identify design patterns that remain optimum regardless of the number of sampling points for three ...
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