Development of Predictive Growth Models for Staphylococcus aureus and Bacillus cereus on Various Food Matrices Consisting of Ready-to-Eat (RTE) Foods원문보기
We developed predictive growth models for Staphylococcus aureus and Bacillus cereus on various food matrices consisting primarily of ready-to-eat (RTE) foods. A cocktail of three S. aureus strains, producing enterotoxins A, C, and D, or a B. cereus strain, were inoculated on sliced bread, cooked ric...
We developed predictive growth models for Staphylococcus aureus and Bacillus cereus on various food matrices consisting primarily of ready-to-eat (RTE) foods. A cocktail of three S. aureus strains, producing enterotoxins A, C, and D, or a B. cereus strain, were inoculated on sliced bread, cooked rice, boiled Chinese noodles, boiled bean sprouts, tofu, baked fish, smoked chicken, and baked hamburger patties at an initial concentration of 3 log CFU/g and stored at 8, 10, 13, 17, 24, and $30^{\circ}C$. Growth kinetic parameters were determined by the Gompertz equation. The square-root and Davey models were used to determine specific growth rate and lag time values, respectively, as a function of temperature. Model performance was evaluated based on bias and accuracy factors. S. aureus and B. cereus growth were most delayed on sliced bread. Overall, S. aureus growth was significantly (p<0.05) more rapid on animal protein foods than carbohydrate-based foods and vegetable protein foods. The fastest growth of S. aureus was observed on smoked chicken. B. cereus growth was not observed at 8 and $10^{\circ}C$. B. cereus growth was significantly (p<0.05) more rapid on vegetable protein foods than on carbohydrate-based foods. The secondary models developed in this study showed suitable performance for predicting the growth of S. aureus and B. cereus on various food matrices consisting of RTE foods.
We developed predictive growth models for Staphylococcus aureus and Bacillus cereus on various food matrices consisting primarily of ready-to-eat (RTE) foods. A cocktail of three S. aureus strains, producing enterotoxins A, C, and D, or a B. cereus strain, were inoculated on sliced bread, cooked rice, boiled Chinese noodles, boiled bean sprouts, tofu, baked fish, smoked chicken, and baked hamburger patties at an initial concentration of 3 log CFU/g and stored at 8, 10, 13, 17, 24, and $30^{\circ}C$. Growth kinetic parameters were determined by the Gompertz equation. The square-root and Davey models were used to determine specific growth rate and lag time values, respectively, as a function of temperature. Model performance was evaluated based on bias and accuracy factors. S. aureus and B. cereus growth were most delayed on sliced bread. Overall, S. aureus growth was significantly (p<0.05) more rapid on animal protein foods than carbohydrate-based foods and vegetable protein foods. The fastest growth of S. aureus was observed on smoked chicken. B. cereus growth was not observed at 8 and $10^{\circ}C$. B. cereus growth was significantly (p<0.05) more rapid on vegetable protein foods than on carbohydrate-based foods. The secondary models developed in this study showed suitable performance for predicting the growth of S. aureus and B. cereus on various food matrices consisting of RTE foods.
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문제 정의
, 1988). This study aimed to develop predictive growth models for S. aureus and B. cereus on various food matrices. The developed models will be used to quantify the effect of temperature on the growth of S.
제안 방법
In this study, the bias factor (Bf) and accuracy factor (Af), as indexes of model performance, were used to evaluate the ability of the developed growth models to describe the experimental data adequately (Table 3). The results show that both the Bf and Af values of the SGR and LT models were close to 1, indicating that the induced secondary models had suitable performance to predict the growth of B.
The fish (frozen pollack) and hamburger patties were purchased from a local grocery store and were baked without oil for 3 min and 4 min, respectively. Since S. aureus and B. cereus were not detected in these samples, we cut them into 10 g portions and placed them into Petri dishes under aseptic conditions.
cereus on various food matrices. The developed models will be used to quantify the effect of temperature on the growth of S. aureus and B. cereus on RTE foods according to the characteristics of various food matrices, as well as to determine the shelf-life of RTE foods at the retail market.
4) as a function of temperature. The model described by Davey was used to evaluate the LT in each food as a function of temperature, namely at 13, 17, 24, or 30℃ where growth was possible. Since B.
대상 데이터
aureus producing enterotoxin A (ATCC 13565) and D (ATCC 23235) strains were obtained from Gyeong Sang University, and wild type, enterotoxin C was obtained from the Korea Food and Drug Administration (KFDA). B. cereus (ATCC 11778) was purchased from the Korean Federation of Culture Collections (KFCC). The S.
데이터처리
The experiment was repeated twice and the obtained results were analyzed using the SAS (Statistical Analysis System) program. The data are expressed as means ± standard deviations (SD).
The significant differences among the groups were determined by analysis of variance (ANOVA) and the means were separated using Duncan’s multiple range tests (p<0.05).
이론/모형
The growth kinetic parameters including lag time (LT) and specific growth rate (SGR) in the primary model were determined at each temperature with the Gompertz equation (Gibson et al., 1987) using GraphPad Prism V4.0 (GraphPad Sofrware, USA).
The water activity meter was calibrated using a calibration solution of 6 M NaCl. The salt concentration was measured by the Mohr method (AOAC, 1995). For the direct titration method, 10 g of weighed sample was placed into a 250 mL Erlenmeyer flask with 90 mL of distilled water and allowed to stand for 5 to 10 min with occasional swirling.
성능/효과
00) were close to 1. For the SGR model, the Bf values of B. cereus on the boiled Chinese noodles (1.09), cooked rice (0.96), sliced bread (0.92), tofu (0.94), boiled soybean sprouts (0.92), hamburger patties (0.99), smoked chicken (0.90), and baked fish (0.91) indicated the predictions were generally fail-safe except for the boiled Chinese noodles, which was still in the acceptable range of 0.70 to 1.15. On the other hand, the Af values of the SGR model were closer to 1 than those for the LT model (Table 3), indicating that overall the SGR model was more accurate and had a lower prediction bias than the LT model developed for the model foods tested in the present study.
In conclusion, the present study showed the growths of S. aureus and B. cereus to be the slowest on sliced bread. Furthermore, the critical food component for S.
Therefore, interpolation and extrapolation with independent sets of data are important for the proper evaluation of model performance (Oscar, 2005). Overall, the Bf values of the LT model were more close to 1 compared to the SGR model, indicating that the LT model was more accurate and had lower prediction bias than the SGR model. Comparisons of the best-fit values for SGR and LT were also made by R2 (the coefficient of determination).
), as indexes of model performance, were used to evaluate the ability of the developed growth models to describe the experimental data adequately (Table 3). The results show that both the Bf and Af values of the SGR and LT models were close to 1, indicating that the induced secondary models had suitable performance to predict the growth of B. cereus in each food matrices. For the Davey LT models of B.
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