Literature DB >> 32182547

Predictive model of growth kinetics for Staphylococcus aureus in raw beef under various packaging systems.

Hwan Hee Yu1, Ye Ji Song1, Yeon Jin Kim1, Hee Young Lee2, Yun-Sang Choi3, Na-Kyoung Lee1, Hyun-Dong Paik4.   

Abstract

This study describes a model of the growth kinetics for S. aureus in raw beef under wrapped packaging (WP), modified atmosphere packaging (MAP), vacuum packaging (VP), and vacuum skin packaging (VSP). Beef samples were inoculated with S. aureus and stored at 10, 15, 20, and 25 °C. VP and VSP showed lower maximum bacteria counts and higher lag time than WP and MAP at all temperatures. At 10 °C, S. aureus in VP and VSP decreased to about 2.5 Log CFU/g. Two primary models (modified Gompertz model and reparameterized Gompertz survival model) were used in the study. The secondary models were described using a polynomial equation and the Davey model. The bias factor (Bf), accuracy factor (Af), and root mean square error (RMSE) of the secondary models were 0.91-1.09, 1.00-1.13, and 0.00-0.68, respectively. The predictive models for kinetics of S. aureus in various packaged raw beef could help to predict the fate of S. aureus more accurately.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Growth kinetics; Packaging system; Predictive model; Raw beef; Staphylococcus aureus

Year:  2020        PMID: 32182547     DOI: 10.1016/j.meatsci.2020.108108

Source DB:  PubMed          Journal:  Meat Sci        ISSN: 0309-1740            Impact factor:   5.209


  2 in total

1.  Characterization of the Inclusion Complexes of Isothiocyanates with γ-Cyclodextrin for Improvement of Antibacterial Activities against Staphylococcus aureus.

Authors:  Jianan Liu; Hongyan Wu; Xinying Ao; Hongshun Hao; Jingran Bi; Hongman Hou; Gongliang Zhang
Journal:  Foods       Date:  2021-12-27

2.  Dimensional Analysis Model Predicting the Number of Food Microorganisms.

Authors:  Cuiqin Li; Laping He; Yuedan Hu; Hanyu Liu; Xiao Wang; Li Chen; Xuefeng Zeng
Journal:  Front Microbiol       Date:  2022-02-08       Impact factor: 5.640

  2 in total

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