Hildebrandt IM, Riddell LM, Hall NO, James MK, Marks BP. Demonstration of Inappropriate Validation Method for a Cracker Baking Process Using Predictive Modeling.
J Food Prot 2024;
87:100298. [PMID:
38734415 DOI:
10.1016/j.jfp.2024.100298]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 05/01/2024] [Accepted: 05/06/2024] [Indexed: 05/13/2024]
Abstract
Validation of baking processes for the inactivation of Salmonella is complicated by the combined effects of product heating and drying. The goal of this study was to quantitatively evaluate a previously disseminated approach to validating baking processes utilizing a predictive model developed using only isothermal and single-moisture inactivation data for the initially formulated dough. A simple cracker dough was formulated using flour inoculated with a five-strain cocktail of Salmonella. Side-by-side isothermal and baking experiments were performed to estimate Salmonella inactivation kinetics and to quantify survivors in a dynamic environment, respectively. Isothermal, single-moisture inactivation experiments were performed with cracker dough (water activity, aw = 0.956 ± 0.002; moisture content = 0.50 ± 0.01 dry basis) at three temperatures (56, 60, or 63°C) with ≥6 time intervals. Baking experiments were performed in a convection oven at 177°C with samples pulled every 30 s up to 360 s, with an endpoint product aw (25°C) of 0.45. The Salmonella isothermal, single-moisture inactivation kinetics in cracker dough resulted in D60°C and z-values of 4.6 min and 4.9°C, respectively; this model was then integrated over the dynamic product temperature profiles from the baking experiments. In the baking experiments, an average of 5-log reductions of Salmonella was achieved by 150 s of treatment; however, >100-log reductions were predicted by the dough-based models at that time point. This fail-dangerous overestimation of Salmonella lethality in crackers explicitly demonstrated that single-level moisture-based prediction models are inappropriate for describing inactivation in a process with both dynamic temperature and moisture, and that model-based validations must incorporate moisture/aw. Furthermore, end-users should exercise caution when utilizing unvalidated models to validate preventive control processes.
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