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Tian Ding,Jun Wang,오덕환 한국식품과학회 2011 Food Science and Biotechnology Vol.20 No.6
The objective of the present study was to develop predictive models for the growth of Staphylococcus aureus on fresh-cut spinach influenced by temperature (15,25, and 35ºC) and relative humidity (60, 70, and 80%)using newly developed OH-Fit V1.0 software. The experimental data at each combined condition were collected and indicated that temperature played a more important role than relative humidity on growth behavior of S. aureus. Firstly, primary and secondary models were developed in sequence using the modified Gompertz and polynomial equation, respectively. After external validation using independent data sets, the established models were demonstrated qualified enough to provide reliable predictions to S. aureus growth on spinach for risk assessment purpose. During the modeling process, OH-Fit V1.0 software was applied to simplify the process of establishing predictive models. It has been proved to be a pretty simple and fast tool for predictive modeling investigators and stakeholder.
Development of Predictive Model for the Growth of Staphylococcus aureus in Kimbab
Tian Ding,Young-Hwan Shim,Ha-Na Kim,오덕환,하상도,정명섭,In-Gyun Hwang 한국식품과학회 2011 Food Science and Biotechnology Vol.20 No.2
This study was conducted to develop predictive models for the growth of Staphylococcus aureus in kimbab as a function of storage temperatures (7, 10, 12, 14, 16, 20,25, and 30^oC). The growth data were fitted into the modified Gompertz model and the Logistic model, and the goodness-of-fit of primary models was compared using determination of coefficient, mean square error, and Akaike’s information criterion. The modified Gompertz model was found to be more suitable to describe the growth data. Therefore, the growth rate (GR) and lag time (LT) obtained from the modified Gompertz model were employed to establish the secondary models. The newly developed models were validated using root mean square error (RMSE), bias factor (B_f), and accuracy factor (A_f). The results showed that RMSE<0.20 and Bf and A_f values were within the reliable range, which indicated that the presented predictive models can be used to assess the risk of S. aureus infection in kimbab.
Significance of Viable but Nonculturable Escherichia coli: Induction, Detection, and Control
( Tian Ding ),( Yuanjie Suo ),( Qisen Xiang ),( Xihong Zhao ),( Shiguo Chen ),( Xingqian Ye ),( Donghong Liu ) 한국미생물 · 생명공학회 2017 Journal of microbiology and biotechnology Vol.27 No.3
Diseases caused by foodborne or waterborne pathogens are emerging. Many pathogens can enter into the viable but nonculturable (VBNC) state, which is a survival strategy when exposed to harsh environmental stresses. Pathogens in the VBNC state have the ability to evade conventional microbiological detection methods, posing a significant and potential health risk. Therefore, controlling VBNC bacteria in food processing and the environment is of great importance. As the typical one of the gram-negatives, Escherichia coli (E. coli) is a widespread foodborne and waterborne pathogenic bacterium and is able to enter into a VBNC state in extreme conditions (similar to the other gram-negative bacteria), including inducing factors and resuscitation stimulus. VBNC E. coli has the ability to recover both culturability and pathogenicity, which may bring potential health risk. This review describes the concrete factors (nonthermal treatment, chemical agents, and environmental factors) that induce E. coli into the VBNC state, the condition or stimulus required for resuscitation of VBNC E. coli, and the methods for detecting VBNC E. coli. Furthermore, the mechanism of genes and proteins involved in the VBNC E. coli is also discussed in this review.
Tian Ding,Yong-Guo Jin,S. M. E. Rahman,Jai-Moung Kim,Kang-Hyun Choi,Gye-Sun Choi,오덕환 한국식품위생안전성학회 2009 한국식품위생안전성학회지 Vol.24 No.3
This study was conducted to develop a model for describing the effect of storage temperature (4, 10, 15, 20, 25, 30 and 35oC) on the growth of Escherichia coli O157 : H7 in ready-to-eat (RTE) lettuce treated with or without (control) alkaline electrolyzed water (AIEW). The growth curves were well fitted with the Gompertz equation, which was used to determine the specific growth rate (SGR) and lag time (LT) of E. coli O157 : H7 (R2 = 0.994). Results showed that the obtained SGR and LT were dependent on the storage temperature. The growth rate increased with increasing temperature from 4 to 35oC. The square root models were used to evaluate the effect of storage temperature on the growth of E. coli O157 : H7 in lettuce samples treated without or with AIEW. The coefficient of determination (R2), adjusted determination coefficient (R2 Adj), and mean square error (MSE) were employed to validate the established models. It showed that R2 and R2 Adj were close to 1 (> 0.93), and MSE calculated from models of untreated and treated lettuce were 0.031 and 0.025, respectively. The results demonstrated that the overall predictions of the growth of E. coli O157 : H7 agreed with the observed data. This study was conducted to develop a model for describing the effect of storage temperature (4, 10, 15, 20, 25, 30 and 35oC) on the growth of Escherichia coli O157 : H7 in ready-to-eat (RTE) lettuce treated with or without (control) alkaline electrolyzed water (AIEW). The growth curves were well fitted with the Gompertz equation, which was used to determine the specific growth rate (SGR) and lag time (LT) of E. coli O157 : H7 (R2 = 0.994). Results showed that the obtained SGR and LT were dependent on the storage temperature. The growth rate increased with increasing temperature from 4 to 35oC. The square root models were used to evaluate the effect of storage temperature on the growth of E. coli O157 : H7 in lettuce samples treated without or with AIEW. The coefficient of determination (R2), adjusted determination coefficient (R2 Adj), and mean square error (MSE) were employed to validate the established models. It showed that R2 and R2 Adj were close to 1 (> 0.93), and MSE calculated from models of untreated and treated lettuce were 0.031 and 0.025, respectively. The results demonstrated that the overall predictions of the growth of E. coli O157 : H7 agreed with the observed data.
Mathematical Modeling on the Growth of Staphylococcus aureus in Sandwich
Tian Ding,Young-Hwan Shim,Na-Jung Choi,하상도,황인균,오덕환,Myung-Sub Chung 한국식품과학회 2010 Food Science and Biotechnology Vol.19 No.3
The growth of Staphylococcus aureus in sandwich fillings at different incubation temperatures was tested. These growth data were fitted into the Gompertz model, Logistic model, and Baranyi model in order to compare the goodness-of-fit of the 3 primary models using several factors such as coefficient of determination (R2), the standard deviation (Sy.x), and the Akaike’s information criterion (AIC). The Gompertz model showed the best statistical fit. Hence, growth parameters such as specific growth rate (SGR) and lag time (LT) obtained from the Gompertz model were used to construct the secondary models. Further, developed models were evaluated by bias factor (Bf) and accuracy factor (Af). For the SGR, the Bf value was 0.993 and Af value was 1.156 which indicated conservative predictions. While for LT, a clear deviation was observed between predictions and observations (Bf=0.635and Af=1.592). The results, however, were also considered acceptable after comparing with previous publications.