A predictive model for the inactivation of Salmonella in dry foods
Trimble, Lisa Michelle
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Low water activity (aw) foods and ingredients such as milk powder, almond butter, spices, and cake mix are naturally dry or have been dried through processing to aw=<0.85. These products typically have a long shelf life, do not require a lethality step and do not require heating before consumption. Salmonella will not grow in such foods, but can survive for extended periods of time if introduced into the food or the process. Little is known about the influence of fat content on Salmonella survival in low aw foods. The aim of this study was to determine the influence of fat content on the survival of Salmonella in dry foods and use this information to modify an existing predictive model so that it is valid for low and high fat foods. Survival data was obtained in whey protein powder supplemented with peanut oil which was equilibrated to various water activities below 0.60 and held at 21-80ºC for 0-168 days. The Weibull model was selected to describe the data and a previously developed secondary model was modified to include foods with a fat content ≤50% (w/w) based on the influence of temperature, aw and fat content on survival. Predictions were validated in 4 foods within the range of the modeled data. The model was useful in predicting survival in low and high fat dry foods with a prediction performance of 66% and improved % bias and % accuracy compared to the unmodified model. Fat content (20% and 50% w/w) provided a protective effect toward survival at temperatures ≥50ºC and additional fat content did not increase this effect. The presence of an emulsifier did not influence survival. Fat and sugar content did not influence the relative survival of 3 out of 4 serovars during storage. S.Tennessee was the most prevalent serovar and S. Typhimurium was not detected after 6 months of storage at 37ºC. The revised model can be used as a quantitative support tool in risk mitigation strategies for low aw foods containing fat.