• Food Science and Biotechnology
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• 제17권6호
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• pp.1352-1356
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• 2008

Bootstrap method, a computer-intensive statistical technique to estimate the distribution of a statistic was applied to deal with uncertainty and variability of the experimental data in stochastic prediction modeling of microbial growth on a chill-stored food. Three different bootstrapping methods for the curve-fitting to the microbial count data were compared in determining the parameters of Baranyi and Roberts growth model: nonlinear regression to static version function with resampling residuals onto all the experimental microbial count data; static version regression onto mean counts at sampling times; dynamic version fitting of differential equations onto the bootstrapped mean counts. All the methods outputted almost same mean values of the parameters with difference in their distribution. Parameter search according to the dynamic form of differential equations resulted in the largest distribution of the model parameters but produced the confidence interval of the predicted microbial count close to those of nonlinear regression of static equation.

• Preventive Nutrition and Food Science
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• 제16권4호
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• pp.364-369
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• 2011

Levels of carbon dioxide gas, a metabolite of microbial growth, have been reported to parallel the onset of microbial spoilage and may be used as a convenient index for a packaged food's shelf life. This study aimed to establish a kinetic model of $CO_2$ production from perishable food for the potential use for shelf life control in the food supply chain. Aerobic bacterial count and package $CO_2$ concentration were measured during the storage of seasoned pork meat at four temperatures (0, 5, 10 and $15^{\circ}C$), and their interrelationship was investigated to establish a mathematical model. The microbial growth at constant temperature was described by using model of Baranyi and Roberts. $CO_2$ production from the stored food could be explained by taking care of its yield and maintenance factors linked to the microbial growth. By establishing the temperature dependence of the microbial growth and $CO_2$ yield factor, $CO_2$ partial pressure or concentration in package headspace could be estimated to a limited extent, which is helpful for controlling the shelf life under constant and dynamic temperature conditions. Application and efficacy of the model needs to be improved with further refinement in the model.

• Biotechnology and Bioprocess Engineering:BBE
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• 제5권5호
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• pp.382-385
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• 2000

A mathematical model was developed, based on the time dependent changes of the specific growth rate, for prediction of the typical microbial cell growth in batch cultures. This model could predict both the lag growth phase and the stationary growth phase of batch cultures, and it was tested with the batch growth of Trichoderma reesei and Lactobacillus delbrueckii.

• Food Science and Biotechnology
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• 제27권6호
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• pp.1865-1869
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• 2018

This study examined the effects of alfalfa seed germination on growth of Salmonella enterica. We investigated the population changes of S. enterica during early sprout development. We found that the population density of S. enterica, which was inoculated on alfalfa seeds was increased during sprout development under all experimental temperatures, whereas a significant reduction was observed when S. enterica was inoculated on fully germinated sprouts. To establish a model for predicting S. enterica growth during alfalfa sprout development, the kinetic growth data under isothermal conditions were collected and evaluated based on Baranyi model as a primary model for growth data. To elucidate the influence of temperature on S. enterica growth rates, three secondary models were compared and found that the Arrhenius-type model was more suitable than others. We believe that our model can be utilized to predict S. enterica behavior in alfalfa sprout and to conduct microbial risk assessments.

• Preventive Nutrition and Food Science
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• 제13권2호
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• pp.104-111
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• 2008

As a way to account for the variability of the primary model parameters in the secondary modeling of microbial growth, three different regression approaches were compared in determining the confidence interval of the temperature-dependent primary model parameters and the estimated microbial growth during storage: bootstrapped regression with all the individual primary model parameter values; bootstrapped regression with average values at each temperature; and simple regression with regression lines of 2.5% and 97.5% percentile values. Temperature dependences of converted parameters (log $q_o$, ${\mu}_{max}^{1/2}$, log $N_{max}$) of hypothetical initial physiological state, maximum specific growth rate, and maximum cell density in Baranyi's model were subjected to the regression by quadratic, linear, and linear function, respectively. With an advantage of extracting the primary model parameters instantaneously at any temperature by using mathematical functions, regression lines of 2.5% and 97.5% percentile values were capable of accounting for variation in experimental data of microbial growth under constant and fluctuating temperature conditions.

• 한국식품저장유통학회지
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• 제24권6호
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• pp.778-785
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• 2017

본 연구는 시중 유통되고 있는 새싹채소 재배용 적콜라비 종자에서 분리한 E. coli strain RC-4-D의 생장예측모델을 개발하기 위해 수행되었다. 각 온도조건(10, 15, 20, 25, $30^{\circ}C$) 별로 적콜라비 중 E. coli strain RC-4-D 밀도 변화를 조사하였고 Baranyi model을 1차 생장예측모델로 이용하였고 각 온도별로 최대생장률(${\mu}max$)과 $10^{\circ}C$를 제외한 유도기(LPD) 값을 도출하였다. E. coli strain RC-4-D의 최대생장률에 대한 2차 생장예측모델로써 suboptimal Ratkowsky square-root, suboptimal Huang square-root, suboptimal Arrhenius-type 세 종류의 모델을 비교하였다. 모델 적합성 검정 결과, suboptimal Huang square-root 모델이 정확도가 가장 높고 suboptimal Ratkowsky square-root 모델이 편차가 가장 적은 것으로 나타났다. 종합적으로, RMSE가 0.100, $A_f$가 1.255, $B_f$가 0.999인 suboptimal Ratkowsky square-root 모델이 온도의 영향을 설명하는 가장 적합한 2차 생장예측 모델인 것으로 나타났다. 본 연구에서 개발한 모델은 적콜라비 새싹채소 생산에 있어서 E. coli의 생장을 예측하고 미생물 위해성평가를 수행하는데 활용될 것으로 기대된다.

• Food Science and Biotechnology
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• 제18권1호
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• pp.137-142
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• 2009

One of the most important aspects of conducting this microbial risk assessment (MRA) is determining the model in microbial behaviors in food systems. However, to fully these modeling, large expenditures or newly laboratory experiments will be spent to do it. To overcome these problems, it has to be considered to develop the new strategies that can be used data in the published literatures. This study is to show whether or not the data set from the published experimental data has more value for modeling for MRA. To illustrate this suggestion, as example of data set, 4 published Salmonella survival in Cheddar cheese reports were used. Finally, using the GInaFiT tool, survival was modeled by nonlinear polynomial regression model describing the effect of temperature on Weibull model parameters. This model used data in the literatures is useful in describing behavior of Salmonella during different time and temperature conditions of cheese ripening.

• 한국물환경학회지
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• 제21권6호
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• pp.602-608
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• 2005

A laboratory-scale experiment was conducted to investigate control of soluble microbial products (SMP) by the internal recycle rate in the submerged membrane separation activated sludge process. The internal recycle rate of the reactor RUN 1 and RUN 2 were 100 % and 200 %, respectively. SMP concentration was rapidly accumulated in the reactor (RUN 1). The variation of accumulated SMP concentration was related to the denitrification rate at the beginning experiment however SMP concentration decreased without correlatively to the denitrification rate during long operation time. The microbial kinetic model was rapidly presented in the both microbial growth and extinction in the reactor (RUN 1). In the SMP kinetic model, Internal recycle rate is the lower, value of UAP and BAP which SMP matter were presented low. The study about development of kinetic model is relatively well adjusted to the experiment exception SMP. In the future, SMP formation equation must be thought that continually research is necessary.

• 한국식품위생안전성학회지
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• 제14권4호
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• pp.319-326
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• 1999

최근 국내에서는 Escherichia coli O157:H7, Listeria monocytogenes등의 미생물에 대한 건강위해성이 강조되면서 미생물 위해성평가에 대한 필요성이 제기되고 있고, U.S.FPA, U.S.DA, FAO/WHO를 비롯한 국제기구 및 외국 유관기관들에서도 미생물 위해성평가 방법을 식품관리에 활용하고자 방법론 연구에 주력하고 있다. 미생물 위험성은 화학물질과 달리 인체건강에 대한 영향이 즉각적이고, 심각하게 나타나 정량적인 위해성평가가 용이하지 않고 유해화학물질과는 다른 평가방법이 요구된다. 식품중 미생물의 위해성평가는 크게 4단계로 구분되는데, 미생물관련질환 추세파악 및 미생물 관련질병에 관한 역학조사 등을 활용하는 위험성확인 단계와 실제 식품원료, 식품가공, 수송, 포장단계 중 식품의 물리적, 화학적 조건에 따른 미생물 변화를 고려하여 식품중 미생물에 대한 노출을 정량화하는 노출평가 단계, 미생물의 용량에 따른 질병발생에 근거하여 용량-반응관계를 규명하는 용량-반응평가 단계, 규명된 모델을 활용하여 모든 평가결과를 통합함으로 위해 도치 예측과 불확실성 분석 등을 수행하는 위해도결정단계로 구성되어 있다. 미생물 용량-반응평가는 크게 비역치(Nonthreshold)와 역치(Threshold) 평가 방법론으로 구분되는데, 비역치 평가방법론은 단일 병원균이 감염을 일으킬 수 있다는 것과 감염을 일으킬 수 있는 확률이 독립적이라는 가정을 전제로 하고, 역치평가방법론은 미생물이 감염을 일으키기 위해서 각기 개별 역치가 존재하는데 어느 정도의 미생물수가 모여 서로 작용해야 독성유발물질을 만들어 낸다는 가정을 전제로 한다. 현재 받아들여지고 있는 비역치 모델로는 Exponential, Beta-poisson, Gompertz, Gamma-weibull 모델 등이 있으며, 역치모델로는 Log-normal, Log-logistic모델 등이 있다. 본 연구에서는 인체 volunteer자료를 활용하여 용량-반응자료를 입력하고 용량-반응자료를 토대로 적합한 수학적 모델을 찾아내어, 선별한 모델의 적합도 검정을 실시하는 방법론 연구를 실시하였으며, 노출평가 자료와 용량-반응평가 결과를 연계하여 위해도를 결정하는 과정에 대해 연구하였다 이 밖에도 모델(Food MicroModel)을 이용하여 식품의 염도, 수분활성도, 온도, pH등의 조건에 따른 미생물의 성장률, 사멸률 등 변화를 예측할 수 있는 방법론 연구를 통해 식품의 최적 보관 조건등을 찾아내는 방법을 습득하였다. 미생물 위해성평가는 외국에서도 아직 초기 연구단계에 있으며 현재로서 사후조사자료인 역학자료보다 건강한 성인남자를 대상으로 한 volunteer 자료를 우선적으로 활용하고 있으나 노약자나 민감그룹에 대한 실험은 현실적으로 불가능하여 동물실험을 이용한 평가방법을 연구중에 있다. 추후 연구방향으로는 국내 volunteer들을 대상으로 한 미생물별 용량-반응결과를 토대로 population sensitivity를 비교할 수 있는 기초자료를 확보함으로써 미생물에 대한 인구집단의 반응 민감성 차이를 비교하고 시료채취 후 즉각적인 실험실적 분석이 가능토록하여 정확한 인체노출평가를 수행함으로써 미생물 위해성평가방법론을 식품미생물관리에 적용하는 것이다.

• Journal of Microbiology and Biotechnology
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• 제34권7호
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• pp.1501-1510
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• 2024

Inflammatory bowel disease (IBD), characterized by chronic inflammation of the gut, is caused by several factors. Among these factors, microbial factors are correlated with the gut microbiota, which produces short-chain fatty acids (SCFAs) via anaerobic fermentation. Fermented foods are known to regulate the gut microbiota composition. Ganjang (GJ), a traditional fermented Korean soy sauce consumed worldwide, has been shown to exhibit antioxidant, anticancer, anti-colitis, and antihypertensive activities. However, its effects on the gut microbiota remain unknown. In the present study, we aimed to compare the anti-inflammatory effects of GJ manufactured using different methods and investigate its effect on SCFA production in the gut. To evaluate the anti-inflammatory effects of GJ in the gut, we performed animal experiments using a mouse model of dextran sulfate sodium (DSS)-induced colitis. All GJ samples attenuated DSS-induced colitis symptoms, including reduced colonic length, by suppressing the expression of inflammatory cytokines. In addition, GJ administration modulated SCFA production in the DSS-induced colitis model. Overall, GJ exerted anti-inflammatory effects by reducing DSS-induced symptoms via regulation of inflammation and modulation of SCFA levels in a DSS-induced colitis model. Thus, GJ is a promising fermented food with the potential to prevent IBD.