Semester of Graduation

Fall 2019

Degree

Master of Science (MS)

Department

Nutrition and Food Science

Document Type

Thesis

Abstract

Microbial growth can be characterized by parameters such as lag time, growth rate, and maximum population density at any specific point of time. Mathematical models that predict microbial growth of foodborne pathogens are increasingly used in the food industry as a viable alternative to traditional methods of microbial enumeration. The Baranyi model has been widely used as the primary model of choice by many authors because of its performance and accuracy. The most recently developed Huang model has been less implemented and few comparisons between the Baranyi and Huang models have been made when modeling pathogenic growth. For this research, pure cultures of E.coli O157:H7 ATCC 43895, Salmonella Typhimurium ATCC 14028 and Listeria monocytogenes V7 (serotype 1/2a) strains were sub-cultured overnight in Brain-Heart Infusion broth at 37 °C for 24 h. Bacteria were grown in a chemically defined media and sampled periodically at regular time intervals to estimate microbial growth. Three repetitions for the growth experiments were conducted. Kinetic parameters of both models from the growth curves were obtained using the USDA Integrated Pathogen Modeling Program. An analysis of variance was performed to determine whether there were any significant differences among means of parameter estimates at a 95.0% confidence level. Additionally, statistic indicators were used to validate the performance of the models based on the bias factor and the accuracy factor. Predictions made by the Baranyi and Huang models for each treatment were evaluated using the Acceptable Prediction Zone, Akaike’s Information Criterion, the Mean Square Error, and the Root Mean Square Error. Graphically, pathogenic growth as a function of time was well described by both models. Bacteria grew faster at 10 mM of glucose compared to a higher (15 mM) or lower (5 mM) nutrient concentration. Both models performed well as indicated by the MSE, RMSE, and AIC. The Baranyi model consistently estimated longer lag phases and higher growth rates than the Huang model. These results provide an insight into modeling growth of pathogens as a function of time and nutrient concentration and may help to choose between the Baranyi or Huang models when determining the best-fitting model.

Date

8-14-2019

Committee Chair

Janes, Marlene

Share

COinS