Liquid egg products can be contaminated with Salmonella spp. during processing. A predictive model for the growth of Salmonella spp. in unpasteurized liquid eggs was developed and validated. Liquid whole egg, liquid yolk, and liquid egg white samples were prepared and inoculated with Salmonella mixt...
Liquid egg products can be contaminated with Salmonella spp. during processing. A predictive model for the growth of Salmonella spp. in unpasteurized liquid eggs was developed and validated. Liquid whole egg, liquid yolk, and liquid egg white samples were prepared and inoculated with Salmonella mixture (approximately 3 Log CFU/mL) containing five serovars (S. Bareilly, S. Richmond, S. Typhimurium monophasic, S. Enteritidis, and S. Gallinarum). Salmonella growth data at isothermal temperatures (5, 10, 15, 20, 25, 30, 35, and $40^{\circ}C$) was collected by 960 h. The population of Salmonella in liquid whole egg and egg yolk increased at above $10^{\circ}C$, while Salmonella in egg white did not proliferate at all temperature. These results demonstrate that there is a difference in the growth of Salmonella depending on the types of liquid eggs (egg yolk, egg white, liquid whole egg) and storage temperature. To fit the growth data of Salmonella in liquid whole egg and egg yolk, Baranyi model was used as the primary model and the maximum growth rate and lag phase duration for each temperature were determined. A secondary model was developed with maximum growth rate as a function of temperature. The model performance measures, bias factor ($B_f$, 0.96-0.99) and $r^2$ (0.96-0.99) indicated good fit for both primary and secondary models. In conclusion, it is thought that the growth model can be used usefully to predict Salmonella spp. growth in various types of unpasteurized liquid eggs when those are exposed to various temperature and time conditions during the processing.
Liquid egg products can be contaminated with Salmonella spp. during processing. A predictive model for the growth of Salmonella spp. in unpasteurized liquid eggs was developed and validated. Liquid whole egg, liquid yolk, and liquid egg white samples were prepared and inoculated with Salmonella mixture (approximately 3 Log CFU/mL) containing five serovars (S. Bareilly, S. Richmond, S. Typhimurium monophasic, S. Enteritidis, and S. Gallinarum). Salmonella growth data at isothermal temperatures (5, 10, 15, 20, 25, 30, 35, and $40^{\circ}C$) was collected by 960 h. The population of Salmonella in liquid whole egg and egg yolk increased at above $10^{\circ}C$, while Salmonella in egg white did not proliferate at all temperature. These results demonstrate that there is a difference in the growth of Salmonella depending on the types of liquid eggs (egg yolk, egg white, liquid whole egg) and storage temperature. To fit the growth data of Salmonella in liquid whole egg and egg yolk, Baranyi model was used as the primary model and the maximum growth rate and lag phase duration for each temperature were determined. A secondary model was developed with maximum growth rate as a function of temperature. The model performance measures, bias factor ($B_f$, 0.96-0.99) and $r^2$ (0.96-0.99) indicated good fit for both primary and secondary models. In conclusion, it is thought that the growth model can be used usefully to predict Salmonella spp. growth in various types of unpasteurized liquid eggs when those are exposed to various temperature and time conditions during the processing.
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제안 방법
In this study, we predicted the growth of Salmonella in unpasteurized liquid whole egg and egg yolk stored at 10–40℃, where Salmonella mainly proliferate, using a growth predictive model.
In this study, we predicted the growth of Salmonella in unpasteurized liquid whole egg and egg yolk stored at 10–40℃, where Salmonella mainly proliferate, using a growth predictive model. The purpose of this study was to establish a proper storage temperature and the expiration dates of unpasteurized liquid eggs using the model predicting the growth of Salmonella.
This study demonstrated there is a difference in the proliferation of Salmonella in unpasteurized liquid eggs depending on the types of liquid eggs (egg yolk, egg white, whole egg) and storage temperature, using Salmonella growth predictive model. Therefore, it is desirable to reset the expiration dates of liquid eggs taking into account of the product type, storage conditions (temperature and time), and microbiological factors.
대상 데이터
The 10 liter of unpasteurized liquid whole eggs used in this experiment was purchased from an egg processing plant in Anseong, Gyeonggi-do in 2012. At the same time, 400 shell eggs were prepared and separated into egg yolk and egg white.
To artificially contaminate the unpasteurized liquid whole egg, egg yolk, and egg white described above, 5 kinds of Salmonella serovars — the two reference strains of S. Enteritidis ATCC 13076 and S. Gallinarum ATCC 9184, and S. Typhimurium monophasic, S. Bareilly, and S. Richmond which are the main issues in liquid eggs in South Korea (Kim et al., 2015) were used in the experiment.
데이터처리
A significant difference (p<0.05) between LPD and μmax was analyzed using a one-way ANOVA which utilizes the Duncan's multiple test method.
In addition, t-test was used to analyze the significant difference in μmax and the LPD of liquid whole egg and egg yolk (p<0.05).
이론/모형
The LPD and μmax calculated in the primary study was used to derive a secondary growth model by applying to a Davey model (Davey, 1989) and a square-root model (Ratkowsky et al., 1982), respectively (Fig. 3).
, the variables of a primary model calculated in each temperature, were used to develop a secondary growth predictive model. The secondary model was developed on the basis of a Davey model (Davey, 1989) and a square-root model (Ratkowsky et al., 1982), using Graph Pad Prism V4.0 (Graph Pad Software, USA).
To verify the suitability of the growth predictive model, growth curves of Salmonella in liquid whole egg and yolk were fitted to the Baranyi model. Measured values of Salmonella in the unpasteurized liquid whole egg and egg yolk stored at 20℃and 30℃, which were not used in the predictive model, were applied for validation.
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