Titlebook: Basic Protocols in Predictive Food Microbiology; Ver?nica Ortiz Alvarenga Book 2023 The Editor(s) (if applicable) and The Author(s), under

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Ramaprasad Bhar,Shigeyuki Hamori a valuable tool that merges microbiology, mathematics, and statistics to improve food safety and quality from microbial growth, survival, or inactivation parameters. Predictive models seek to understand the effect of environmental conditions (pH, temperature, aw, etc.) on microbial responses by mat

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https://doi.org/10.1007/b109046 laboratory media, but these predictions often need to be validated in food matrices. Generating accurate and reproducible growth data in food matrices presents particular challenges when compared to experiments in laboratory media. The aim of this chapter is to provide the reader with an introducti

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Nizar Bouguila,Wentao Fan,Manar Amayriort optimization of thermal treatments, due to their ability to?predict the response of microbial populations under fixed temperature conditions (isothermal conditions) or variable (dynamic conditions). These models can also consider intrinsic and extrinsic factors involved in the process. This chap

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Robert J. Elliott,Anatoliy V. Swishchukot being considered. Given the importance of variability in risk-based food safety and quality management, the role of individual cell heterogeneity as a source of variability in predictive models has been recognized from many researchers. The methodology described herein allows for the observation

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