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- W4386576385 abstract "Most microbial growth, survival, and inactivation studies rely on large microbial populations, with the behavioral heterogeneity of individual cells not 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 of the behavior of individual microbial cells and spores using time-lapse microscopy. The presented methodology, through the combination of phase-contrast or fluorescence microscopy with image analysis, allows for the generation of large datasets pertinent to different aspects of individual cell microbial behavior and, in tandem with stochastic modeling approaches, constitutes a rather valuable tool in quantitative microbiological risk assessment." @default.
- W4386576385 created "2023-09-10" @default.
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- W4386576385 date "2023-01-01" @default.
- W4386576385 modified "2023-10-16" @default.
- W4386576385 title "Individual Cell-Based Modeling for Microbial Growth and Inactivation Using Time-Lapse Microscopy" @default.
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- W4386576385 doi "https://doi.org/10.1007/978-1-0716-3413-4_7" @default.
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