Related Experiment Video
Updated: Feb 14, 2026

Chronic Salmonella Infected Mouse Model
Published on: May 31, 2010
Predictive modeling of Salmonella Thompson growth in unpasteurized liquid egg products
Chang Geun Lim1, Seung Hee Baek2, In Sik Nam3,4
1Department of Animal Convergence Science, Hankyoung National University, Anseong, Korea.
Objective:
Salmonella Thompson is a major cause of large-scale foodborne disease outbreaks worldwide; however, research on S. Thompson remains limited. This study investigates the development of a predictive model for the growth of S. Thompson in unpasteurized liquid egg products, such as liquid egg white, liquid egg yolk, and liquid whole egg, to understand the associated health risks.
Methods:
Unpasteurized liquid egg products, confirmed to be free of Salmonella spp., were inoculated with S. Thompson and incubated at various temperatures. Growth kinetic parameters were estimated using both primary and secondary predictive models, including the Baranyi and Roberts model and second-order polynomial models. The effects of environmental factors on S. Thompson growth were analyzed to establish a comprehensive risk assessment framework.
Results:
The growth curves of S. Thompson exhibited a typical bacterial sigmoidal pattern characteristic of bacterial proliferation, with the Baranyi model providing the best fit for describing the growth kinetics. The secondary model accurately predicted the effect of temperature on growth rate, demonstrating that S. Thompson proliferates rapidly under specific environmental conditions. Model validation indicated high accuracy, confirming the reliability of the developed model for risk assessment applications.
Conclusion:
The established predictive model enables quantitative assessment of the growth behavior of S. Thompson in unpasteurized liquid egg products. This model can be used in risk assessment and food safety management strategies to mitigate the risk of foodborne pathogen contamination in the food industry.
Related Concept Videos
Predicting Products: Substitution vs. Elimination
The following factors can influence the mechanisms competing against each other:
Predicting Products: SN1 vs. SN2
With increased substitution on the alkyl halide,...
Predicting Molecular Geometry
Growth Models with Integration: Problem Solving
Exponential Equations for Modeling Growth
Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.

