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 | Dimensione | Formato | |
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Procedia Food Science 2016 1-s2.0-S2211601X16300098-main.pdf
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