Polese Pierluigi, Torre Manuela Del, Stecchini Mara Lucia
Polytechnic Department of Engineering and Architecture.
Department of Agricultural, Food, Environmental and Animal Sciences, University of Udine, Italy.
Ital J Food Saf. 2018 Apr 9;7(1):6943. doi: 10.4081/ijfs.2018.6943. eCollection 2018 Mar 31.
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 (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), 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.
预测建模工具主要用于描述微生物对特定环境条件的反应，其应用有助于更好地理解食品中的微生物行为。本文以一个易于获取且用户友好的基于网络的应用程序（PP）的形式，展示了一个三级模型，并列举了我们实验室的研究实例。通过PP应用程序，用户可以访问不同的模块，这些模块应用了一组经认定可靠的已发表模型，用于确定食品是否符合欧盟安全标准，以及在整个关键控制点识别过程中优化加工过程。该应用程序围绕一个生长/不生长边界模型，并结合一个生长模型，还包括热灭活模型和非热灭活模型。此外，还纳入了一些综合功能，如每个抑制因子对生长概率的分数贡献（f）以及生长概率随时间的变化（P）。预计PP应用程序将有助于食品行业和食品安全当局共同致力于提高食品安全。
