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Praedicere Possumus: An Italian web-based application for predictive microbiology to ensure food safety
The use of predictive modelling tools, which mainly describe the response of microorganisms to a particular set of environmental conditions, may contribute to a better understanding of microbial behaviour in foods. In this paper, a tertiary model, in the form of a readily available and userfriendly...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PAGEPress Publications, Pavia, Italy
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5913704/ https://www.ncbi.nlm.nih.gov/pubmed/29732330 http://dx.doi.org/10.4081/ijfs.2018.6943 |
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author | Polese, Pierluigi Torre, Manuela Del Stecchini, Mara Lucia |
author_facet | Polese, Pierluigi Torre, Manuela Del Stecchini, Mara Lucia |
author_sort | Polese, Pierluigi |
collection | PubMed |
description | The use of predictive modelling tools, which mainly describe the response of microorganisms to a particular set of environmental conditions, may contribute to a better understanding of microbial behaviour in foods. In this paper, a tertiary model, in the form of a readily available and userfriendly web-based application Praedicere Possumus (PP) is presented with research examples from our laboratories. Through the PP application, users have access to different modules, which apply a set of published models considered reliable for determining the compliance of a food product with EU safety criteria and for optimising processing throughout the identification of critical control points. The application pivots around a growth/no-growth boundary model, coupled with a growth model, and includes thermal and non-thermal inactivation models. Integrated functionalities, such as the fractional contribution of each inhibitory factor to growth probability (f) and the time evolution of the growth probability (P(t)), have also been included. The PP application is expected to assist food industry and food safety authorities in their common commitment towards the improvement of food safety. |
format | Online Article Text |
id | pubmed-5913704 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | PAGEPress Publications, Pavia, Italy |
record_format | MEDLINE/PubMed |
spelling | pubmed-59137042018-05-04 Praedicere Possumus: An Italian web-based application for predictive microbiology to ensure food safety Polese, Pierluigi Torre, Manuela Del Stecchini, Mara Lucia Ital J Food Saf Article The use of predictive modelling tools, which mainly describe the response of microorganisms to a particular set of environmental conditions, may contribute to a better understanding of microbial behaviour in foods. In this paper, a tertiary model, in the form of a readily available and userfriendly web-based application Praedicere Possumus (PP) is presented with research examples from our laboratories. Through the PP application, users have access to different modules, which apply a set of published models considered reliable for determining the compliance of a food product with EU safety criteria and for optimising processing throughout the identification of critical control points. The application pivots around a growth/no-growth boundary model, coupled with a growth model, and includes thermal and non-thermal inactivation models. Integrated functionalities, such as the fractional contribution of each inhibitory factor to growth probability (f) and the time evolution of the growth probability (P(t)), have also been included. The PP application is expected to assist food industry and food safety authorities in their common commitment towards the improvement of food safety. PAGEPress Publications, Pavia, Italy 2018-04-09 /pmc/articles/PMC5913704/ /pubmed/29732330 http://dx.doi.org/10.4081/ijfs.2018.6943 Text en ©Copyright P. Polese et al., 2018 http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Article Polese, Pierluigi Torre, Manuela Del Stecchini, Mara Lucia Praedicere Possumus: An Italian web-based application for predictive microbiology to ensure food safety |
title | Praedicere Possumus: An Italian web-based application for predictive microbiology to ensure food safety |
title_full | Praedicere Possumus: An Italian web-based application for predictive microbiology to ensure food safety |
title_fullStr | Praedicere Possumus: An Italian web-based application for predictive microbiology to ensure food safety |
title_full_unstemmed | Praedicere Possumus: An Italian web-based application for predictive microbiology to ensure food safety |
title_short | Praedicere Possumus: An Italian web-based application for predictive microbiology to ensure food safety |
title_sort | praedicere possumus: an italian web-based application for predictive microbiology to ensure food safety |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5913704/ https://www.ncbi.nlm.nih.gov/pubmed/29732330 http://dx.doi.org/10.4081/ijfs.2018.6943 |
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