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A New Approach to Estimate Salmonella Inactivation Parameters During Dynamic Elevated Heat Treatment: A Case Study
Natoavina T Faliarizao1, Yawei Lin2, E Shaney Rump2
1Department of Food Science and Human Nutrition, Michigan State University, East Lansing, MI 48824, USA; Department of Biosystems and Agricultural Engineering, Michigan State University, East Lansing, MI 48824, USA.
Abstract:
Limited studies have been conducted on treating Salmonella in low-moisture foods (LMFs) at elevated temperature (>90 °C) without direct contact with the heating medium. However, nearly all LMFs are heated under nonisothermal conditions (above 90 °C) during commercial processes such as baking, toasting, roasting, etc. In this study, flaxseeds were equilibrated to a water activity of 0.55 ± 0.03 after being inoculated with Salmonella enterica Enteritidis PT 30. Heat treatment was performed using a heated circulator with silicon oil at 95, 105, or 120 °C for 11 evenly spaced time points with intervals of 15-30 s. Two aluminum test cells with 0.8 g of inoculated flaxseed and one thermocouple-equipped cell with 0.8 g of uninoculated flaxseed per time point were used for each biological replicate. Two secondary inactivation models (log-linear/Bigelow and Weibull/Bigelow) and three primary inactivation models (log-linear, Weibull, and Geeraerd) were compared for dynamic elevated temperature conditions. Salmonella inactivation parameters in flaxseed were estimated using ordinary least squares (OLSs). Statistical analysis indicated that the log-linear/Bigelow model was the model that best described the thermal inactivation kinetics at higher temperatures, based on the lowest Akaike information criterion (AICc) values. A tenfold increase in the lethality rate for Salmonella at elevated temperatures in flaxseeds (D105°C-value = 24.17-30.02 s) required a 35.9 °C increase from the reference temperature of 105 °C. Because the scaled sensitivity coefficients are larger, experiments at higher oil bath temperatures are better for estimating the D-value, z-value, and n. Overall, this new approach allows estimation of Salmonella's inactivation parameters at elevated temperatures under dynamic conditions. Food processors can use these findings to develop or refine Salmonella prediction models for real-world processing of low-moisture foods under high-temperature conditions.
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