Development and Validation of a Dynamic Predictive Model for Growth of Salmonella spp. in Scrambled Egg Mix

Introduction: Liquid egg is widely used as an ingredient in various food products. Salmonella spp. contamination of liquid egg products can be a major human health concern. Tools to evaluate potential risk of Salmonella spp. growth and the resulting safety of the liquid egg product are needed. 

Purpose: Develop and validate a dynamic predictive model for the growth of Salmonella spp. in Scrambled Egg Mix under continuously varying temperature conditions.

Methods: Scrambled Egg Mix was inoculated with ca. 2.0 log CFU/ml of a five serovar cocktail of Salmonella spp. The inoculated product (10 ml) was distributed in sterile vacuum bags and immersed in water baths set at specific temperatures. Salmonella spp. growth data at isothermal temperatures (10, 15, 20, 25, 30, 35, 37, 39, 41, 43, 45, and 47°C) was collected. The Baranyi model was used as a primary model to fit growth data; modified Ratkowsky model was fitted to the secondary model, and a dynamic model was developed using 4^th-order Runge-Kutta method. The dynamic model was validated using two sinusoidal temperature profiles, 5-15°C for 480 h and 10-40°C for 48 h, respectively.

Results: The mean Root Square Mean Error (RMSE) and pseudo-R² value for primary model were 0.33 log CFU/ml and 0.98, and for the secondary model were 0.06 and 0.99, respectively. The RMSE values for the sinusoidal low and high temperature profiles were 0.31 and 0.46 log CFU/ml, respectively.

Significance: The developed model can be used to evaluate the risk of Salmonella spp. growth in Scrambled Egg Mix during egg processing, storage and distribution.