Predictive Modeling for the Growth of <i>Salmonella</i> spp. in Liquid Egg White and Application of Scenario-Based Risk Estimation

Abstract

The objective of the study was to develop a predictive model of Salmonella spp. growth in pasteurized liquid egg white (LEW) and to estimate the salmonellosis risk using the baseline model and scenario analysis. Samples were inoculated with six strains of Salmonella, and bacterial growth was observed during storage at 10–37 °C. The primary models were developed using the Baranyi model for LEW. For the secondary models, the obtained specific growth rate (μmax) and lag phase duration were fitted to a square root model and Davey model, respectively, as functions of temperature (R2 ≥ 0.98). For μmax, the values were satisfied within an acceptable range (Af, Bf: 0.70–1.15). The probability of infection (Pinf) due to the consumption of LEW was zero in the baseline model. However, scenario analysis suggested possible salmonellosis for the consumption of LEW. Because Salmonella spp. proliferated much faster in LEW than in egg white (EW) during storage at 20 and 30 °C (p inf may be obtained for LEW when these products are stored at the same conditions. The developed predictive model can be applied to the risk management of Salmonella spp. along the food chain, including during product storage and distribution.

Keywords

• <i>Salmonella</i> spp.
• liquid egg white
• predictive model
• validation
• probability of infection