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- W2463994304 abstract "One of the most widely used and most effective means of preventing the harmful proliferation of pathogenic and spoilage microorganisms in food is a heat treatment [1]. An acceptable threshold level of the surviving microorganisms is the major target after implementing a heat-treatment process. The capacity of certain bacteria to resist and survive heat treatment is a cause of concern, for example for the milk industry [2]. A possible explanation for the deviation from an acceptable, predefined threshold level is the occurrence of non-loglinear survival curves [3]. The present research has three major aims: (i) to present a general predictive modelling cycle, in which several steps can be distinguished, (ii) to illustrate the mathematical features of existing non-loglinear survival models and associated secondary modelling approaches, and (iii) to present a case study of inactivation of Escherichia coli K12 where two methodologies of parameter estimation are compared. Additionally, a short notice is included concerning the recently developed GInaFiT (Geeraerd et al. Inactivation Model Fitting Tool), a freeware add-in for Microsoft® Excel, aimed at bridging the gap between people developing predictive modelling approaches and end-users in the food industry or research groups not equipped with advanced non-linear regression-analysis tools." @default.
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- W2463994304 date "2004-01-01" @default.
- W2463994304 modified "2023-09-24" @default.
- W2463994304 title "Accurate modelling of non-loglinear survival curves" @default.
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