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Modeling the growth of Salmonella in raw ground pork under dynamic conditions of temperature abuse.

Authors :
Haque M
Wang B
Mvuyekure AL
Chaves BD
Source :
International journal of food microbiology [Int J Food Microbiol] 2024 Sep 16; Vol. 422, pp. 110808. Date of Electronic Publication: 2024 Jun 26.
Publication Year :
2024

Abstract

Salmonella contamination of pork products is a significant public health concern. Temperature abuse scenarios, such as inadequate refrigeration or prolonged exposure to room temperature, can enhance Salmonella proliferation. This study aimed to develop and validate models for Salmonella growth considering competition with background microbiota in raw ground pork, under isothermal and dynamic conditions of temperature abuse between 10 and 40 °C. The maximum specific growth rate (μ <subscript>max</subscript> ) and maximum population density (MPD) were estimated to quantitatively describe the growth behavior of Salmonella. To reflect more realistic microbial interactions in Salmonella-contaminated product, our model considered competition with the background microbiota, measured as mesophilic aerobic plate counts (APC). Notably, the μ <subscript>max</subscript> of Salmonella in low-fat samples (∼5 %) was significantly higher (p < 0.05) than that in high-fat samples (∼25 %) at 10, 20, and 30 °C. The average doubling time of Salmonella was 26, 4, 2, 1.5, 0.8, and 1.1 h at 10, 15, 20, 25, 30, and 40 °C, respectively. The initial concentration of Salmonella minimally impacted its growth in ground pork at any temperature. The MPD of APC consistently exceeded that of Salmonella, indicating the growth of APC without competition from Salmonella. The competition model exhibited excellent fit with the experimental data, as 95 % (627/660) of residual errors fell within the desired acceptable prediction zone (pAPZ >0.70). The theoretical minimum and optimum growth temperatures for Salmonella ranged from 5 to 6 °C and 35 to 36 °C, respectively. The dynamic model displayed strong predictive performance, with 90 % (57/63) of residual errors falling within the APZ. Dynamic models could be valuable tools for validating and refining simpler static or isothermal models, ultimately improving their predictive capabilities to enhance food safety.<br />Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2024 Elsevier B.V. All rights reserved.)

Details

Language :
English
ISSN :
1879-3460
Volume :
422
Database :
MEDLINE
Journal :
International journal of food microbiology
Publication Type :
Academic Journal
Accession number :
38955022
Full Text :
https://doi.org/10.1016/j.ijfoodmicro.2024.110808