Dynamic predictive model for growth of Salmonella spp. in scrambled egg mix

• Lin Li ^[2] ; Jihan Cepeda ^[2] ; Jeyamkondan Subbiah ^[2] ; Glenn Froning ^[2] ; Vijay K. Juneja ^[1] ; Harshavardhan Thippareddi ^[2]
  1. [1] United States Department of Agriculture

     United States Department of Agriculture

     Estados Unidos

     
  2. [2] Department of Food Science and Technology, University of Nebraska, Estados Unidos
• Localización: Food microbiology, ISSN 0740-0020, Vol. 64 (June), 2017, págs. 39-46
• Idioma: inglés
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• Resumen

  • Liquid egg products can be contaminated with Salmonella spp. during processing. A dynamic model for the growth of Salmonella spp. in scrambled egg mix - high solids (SEM) was developed and validated. SEM was prepared and inoculated with ca. 2 log CFU/mL of a five serovar Salmonella spp. cocktail. Salmonella spp. growth data at isothermal temperatures (10, 15, 20, 25, 30, 35, 37, 39, 41, 43, 45, and 47 °C) in SEM were collected. Baranyi model was used (primary model) to fit growth data and the maximum growth rate and lag phase duration for each temperature were determined. A secondary model was developed with maximum growth rate as a function of temperature. The model performance measures, root mean squared error (RMSE, 0.09) and pseudo-R2 (1.00) indicated good fit for both primary and secondary models. A dynamic model was developed by integrating the primary and secondary models and validated using two sinusoidal temperature profiles, 5–15 °C (low temperature) for 480 h and 10–40 °C (high temperature) for 48 h. The RMSE values for the sinusoidal low and high temperature profiles were 0.47 and 0.42 log CFU/mL, respectively. The model can be used to predict Salmonella spp. growth in case of temperature abuse during liquid egg processing.