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Bioinactivation FE: A free web application for modelling isothermal and dynamic microbial inactivation
Alberto Garre1, Marta Clemente-Carazo1, Pablo S Fernández1
1Departamento de Ingeniería de Alimentos y del Equipamiento Agrícola, Instituto de Biotecnología Vegetal, Universidad Politécnica de Cartagena (ETSIA), Paseo Alfonso XIII, 48, 30203 Cartagena, Spain.
Food Research International (Ottawa, Ont.)
|August 23, 2018
Summary
A new web application, Bioinactivation FE, makes advanced predictive microbiology modeling accessible to food scientists. It simplifies microbial inactivation modeling and prediction interval generation, aiding research without requiring programming expertise.
Area of Science:
- Predictive Microbiology
- Food Science
- Computational Biology
Background:
- Mathematical models are crucial in predictive microbiology but require advanced programming skills.
- Existing R package 'bioinactivation' and its web application 'Bioinactivation SE' have limitations for users without programming backgrounds.
- There is a need for user-friendly tools to access complex microbial inactivation modeling functionalities.
Purpose of the Study:
- To present Bioinactivation FE, a new web application extending Bioinactivation SE.
- To provide an interface for all functions within the 'bioinactivation' R package.
- To enhance accessibility of microbial inactivation modeling for food scientists.
Main Methods:
- Development of the Bioinactivation FE web application.
- Integration of all model fitting and prediction functions from the 'bioinactivation' R package.
- User interface improvements based on feedback and demonstration using published data.
Main Results:
- Bioinactivation FE offers a comprehensive interface for isothermal and non-isothermal microbial inactivation modeling.
- The application enables generation of survivor curves and prediction intervals.
- Case studies demonstrated its utility in analyzing induced thermal resistance in Escherichia coli and the effect of nanoemulsified d-limonene on Salmonella Senftenberg.
Conclusions:
- Bioinactivation FE significantly lowers the barrier for food scientists to utilize advanced predictive microbiology tools.
- The application facilitates robust analysis of microbial inactivation data, including dynamic and non-linear processes.
- It supports informed decision-making in food safety and preservation by providing accessible modeling capabilities.
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