Date of this Version
Arciniega, A. (2017). Modeling the Survival of Salmonella in Soy Sauce-Based Products Stored at Two Different Temperatures (Masters thesis). University of Nebraska-Lincoln. Food Science and Technology. 99pp.
Acidified foods are defined in the regulations as “low acid foods to which acid(s) has been added to bring finished pH to 4.6 or below”. As the market for these products expands, an increasing number of them are being processed with reduced heat treatment, relying on acid alone to ensure the destruction of pathogens. When considering the survival rate of microbial pathogens in these products, pH, water activity, temperature, salt content and holding time are integral and must be considered together.
Despite improvements in production, handling, and distribution of food products in recent years, protecting consumers from foodborne illness still remains a challenge. Although most food products undergo a kill step at the point of production, there is often a lack of scientific proof. This has created an urgent need in the industry for developing a scientific validation that can better ensure product safety. Predictive models can be used to obtain data on the survival rates of bacteria which can be applied to all stages of the manufacturing process; for instance, new product development, changes to product recipes, etc.
For this study, Salmonella has been selected to inoculate soy sauce based products because this pathogen has adaptive responses such as acid tolerance, which is responsible for bacterial survival under extreme acid conditions. Several pH levels (3.0, 4.0 and 5.0), soy sauce (0%, 50% and 100%) and salt (2%, 7% and 14%) were considered. A total of 18 combinations were stored at two different temperatures 18.3oC (65oF) and 23.8oC (75oF). A model was developed to predict the maximum death rate as a response of the interaction of several factors such as pH, storage temperature, salt and soy sauce percentages. The model predicted successfully the response of the pathogen in 83% of the tested cases. The results of this study indicated that the developed model predicts satisfactorily the death rate of Salmonella in soy sauce based products and can provide useful quantitative data for the development of safer food products and processes.
Advisor: Jayne Stratton