Mathematical Modeling of Inactivation During Apple Drying and Pre-Drying Heating in Closed Environments.

Foods

Department of Industrial & Systems Engineering, University of Washington, P.O. Box 352650, Seattle, WA 98195, USA.

Published: November 2024


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Article Abstract

Drying is one of the most effective preservation methods for extending the shelf-life of perishable foods. The microbial safety of low-moisture food products had not been recognized as a concern until outbreaks reported over the past decade in products contaminated with bacterial pathogens, in particular . There is now an urgent need to understand the influence of process conditions on the thermal inactivation of pathogens in various drying operations. This study aimed to develop a predictive model for inactivation in diced apples during hot air drying and in high-humidity heating in closed environments. Fresh-cut apple cubes (6 mm) inoculated with a cocktail of strains (Enteritidis PT30, Montevideo 488275, and Agona 447967) were placed in a customized box inside an oven for three different treatments: (1) open-box drying at oven temperature 90 °C (Drying-90); (2) close-box pre-drying heating at 90 °C (PD heating-90); and (3) close-box pre-drying heating at 70 °C (PD heating-70). Air temperature, relative humidity (RH), and sample temperatures were monitored, and survival was measured at multiple time intervals. After 10 min, the air RH reached 66% in PD heating-90 and 74% in PD heating-70, versus 30% in Drying-90. A 5-log reduction in was achieved in 8.5 min in PD heating-90, and 14 min in PD heating-70, compared to 28.7 min in Drying-90. A mathematical model using sample surface RH and sample temperature profiles accurately predicted inactivation across all treatments (RMSE = 0.92 log CFU/g, R = 0.86), with thermal death parameters comparable to isothermal studies. This study underscores the role of humidity in enhancing microbial reduction during drying and proposes high-humidity pre-drying heating as an effective control step. The developed model shows promise for real-time prediction of microbial inactivation in complex drying environments with dynamic temperature and humidity conditions.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11640392PMC
http://dx.doi.org/10.3390/foods13233877DOI Listing

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