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. 2024 Dec;55(4):3477-3485.
doi: 10.1007/s42770-024-01499-4. Epub 2024 Aug 30.

Modeling nonlinear inactivation of hygiene indicator bacteria in pig carcasses during scalding at different pHs

Affiliations

Modeling nonlinear inactivation of hygiene indicator bacteria in pig carcasses during scalding at different pHs

Richeli Aline Stefanello et al. Braz J Microbiol. 2024 Dec.

Abstract

This study aimed to investigate the influence of adding an alkalizing agent to the scalding water of a slaughterhouse in Brazil to inactivate hygiene indicator bacteria in pig carcasses. Scalding is critical during carcass processing because slaughterhouses' scalding water is constantly renewed; therefore, it is usually contaminated with organic matter, such as faeces and dirt from the previous carcasses. The treatments evaluated consisted of counting Enterobacteriaceae and mesophilic bacteria in pork jowls at 62 °C, 65 °C, 68 C, and 72 °C after 0.0, 1.5, 3.0, 4.5, 6.0, and 7.5 min of simulated scalding at the pHs of 7.0 (control) and 11.0 (after addition of alkalizing agent). Decimal reduction times of hygiene indicator bacteria for all treatments were estimated with different nonlinear bacterial inactivation models. As a result, adding the alkalizing agent did not significantly inactivate most of the bacteria in the studied samples. However, it contributed to the inactivation of some bacteria, mostly belonging to the mesophilic group, at some specific temperatures. The results obtained in the current study can provide useful insights into dealing with pig carcass contamination in a real-world scenario and applying the obtained information in the industrial environment.

Keywords: Enterobacteriaceae; Decimal reduction time; Food industry process; Food safety; Pig slaughter; Predictive microbiology.

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Conflict of interest statement

Declarations. Conflict of interest: On behalf of all authors, the corresponding author states that there is no conflict of interest.

Figures

Fig. 1
Fig. 1
Schematic diagram showing the procedure adopted for the analyses
Fig. 2
Fig. 2
Violin plots for all goodness-of-fit indices obtained after fitting the five models to all datasets
Fig. 3
Fig. 3
Values of the parameter δ as a function of the temperature for mesophilic bacteria and Enterobacteriaceae
Fig. 4
Fig. 4
Values of the parameter formula image as a function of the temperature for mesophilic bacteria and Enterobacteriaceae
Fig. 5
Fig. 5
Values of the parameter formula image as a function of the temperature for mesophilic bacteria and Enterobacteriaceae

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