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The Inclusion of the Food Microstructural Influence in Predictive Microbiology: State-of-the-Art
Predictive microbiology has steadily evolved into one of the most important tools to assess and control the microbiological safety of food products. Predictive models were traditionally developed based on experiments in liquid laboratory media, meaning that food microstructural effects were not repr...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8468028/ https://www.ncbi.nlm.nih.gov/pubmed/34574229 http://dx.doi.org/10.3390/foods10092119 |
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author | Verheyen, Davy Van Impe, Jan F. M. |
author_facet | Verheyen, Davy Van Impe, Jan F. M. |
author_sort | Verheyen, Davy |
collection | PubMed |
description | Predictive microbiology has steadily evolved into one of the most important tools to assess and control the microbiological safety of food products. Predictive models were traditionally developed based on experiments in liquid laboratory media, meaning that food microstructural effects were not represented in these models. Since food microstructure is known to exert a significant effect on microbial growth and inactivation dynamics, the applicability of predictive models is limited if food microstructure is not taken into account. Over the last 10–20 years, researchers, therefore, developed a variety of models that do include certain food microstructural influences. This review provides an overview of the most notable microstructure-including models which were developed over the years, both for microbial growth and inactivation. |
format | Online Article Text |
id | pubmed-8468028 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-84680282021-09-27 The Inclusion of the Food Microstructural Influence in Predictive Microbiology: State-of-the-Art Verheyen, Davy Van Impe, Jan F. M. Foods Review Predictive microbiology has steadily evolved into one of the most important tools to assess and control the microbiological safety of food products. Predictive models were traditionally developed based on experiments in liquid laboratory media, meaning that food microstructural effects were not represented in these models. Since food microstructure is known to exert a significant effect on microbial growth and inactivation dynamics, the applicability of predictive models is limited if food microstructure is not taken into account. Over the last 10–20 years, researchers, therefore, developed a variety of models that do include certain food microstructural influences. This review provides an overview of the most notable microstructure-including models which were developed over the years, both for microbial growth and inactivation. MDPI 2021-09-08 /pmc/articles/PMC8468028/ /pubmed/34574229 http://dx.doi.org/10.3390/foods10092119 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Verheyen, Davy Van Impe, Jan F. M. The Inclusion of the Food Microstructural Influence in Predictive Microbiology: State-of-the-Art |
title | The Inclusion of the Food Microstructural Influence in Predictive Microbiology: State-of-the-Art |
title_full | The Inclusion of the Food Microstructural Influence in Predictive Microbiology: State-of-the-Art |
title_fullStr | The Inclusion of the Food Microstructural Influence in Predictive Microbiology: State-of-the-Art |
title_full_unstemmed | The Inclusion of the Food Microstructural Influence in Predictive Microbiology: State-of-the-Art |
title_short | The Inclusion of the Food Microstructural Influence in Predictive Microbiology: State-of-the-Art |
title_sort | inclusion of the food microstructural influence in predictive microbiology: state-of-the-art |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8468028/ https://www.ncbi.nlm.nih.gov/pubmed/34574229 http://dx.doi.org/10.3390/foods10092119 |
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