Today, European legislation considers predictive microbiology as a tool to define food safety. People in the food industry, including those in small-sized enterprises, even if they are unable to avail themselves of specific knowledge, are encouraged to use the same approach. To extend a bridge between both sides, a user-friendly, simplified, web-based application (Praedicere Possumus, PP) has been developed. Through this application, users have access to different modules, which apply a set of models, some of them already validated and considered reliable for determining the compliance of a food product with EU safety criteria(1). In particular, the PP applies the growth/no-growth boundary model(2), coupled with a three-phase linear growth model and thermal/non-thermal models. Two complementary 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(3). The PP application is expected to assist users in defining processing and storage conditions to attain a desirable food safety level and to support food safety authorities in demonstrating compliance with legislation.

A web-based application customized to food safety requirements of small-sized enterprises

STECCHINI, Mara Lucia
Ultimo
2016-01-01

Abstract

Today, European legislation considers predictive microbiology as a tool to define food safety. People in the food industry, including those in small-sized enterprises, even if they are unable to avail themselves of specific knowledge, are encouraged to use the same approach. To extend a bridge between both sides, a user-friendly, simplified, web-based application (Praedicere Possumus, PP) has been developed. Through this application, users have access to different modules, which apply a set of models, some of them already validated and considered reliable for determining the compliance of a food product with EU safety criteria(1). In particular, the PP applies the growth/no-growth boundary model(2), coupled with a three-phase linear growth model and thermal/non-thermal models. Two complementary 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(3). The PP application is expected to assist users in defining processing and storage conditions to attain a desirable food safety level and to support food safety authorities in demonstrating compliance with legislation.
File in questo prodotto:
File Dimensione Formato  
Procedia Food Science 2016 1-s2.0-S2211601X16300098-main.pdf

accesso aperto

Descrizione: Articolo principale
Tipologia: Versione Editoriale (PDF)
Licenza: Creative commons
Dimensione 120.08 kB
Formato Adobe PDF
120.08 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11390/1102018
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? 1
social impact