본 연구에서는 축산식품인 편육을 대상으로 황색포도상 구균의 성장예측모델을 개발하였다. 편육에서 황색포도상 구균의 성장패턴은 4, 10, 20, 37oC의 보관온도에서 측정 되었으며, 황색포도상구균은 각각의 저장 온도에서 모두 증가하는 것으로 나타났다. 편육에 오염된 황색포도상구 균의 생육결과를 토대로 Baranyi model을 이용하여 유도 기(LPD)와 최대성장률(μmax)을 산출한 결과, 유도기는 4, 10, 20, 37oC에서 212.81, 79.67, 3.12, 2.21 h으로 온도에 반비례한 것으로 나타났고 최대성장률은 같은 보관온도에 서 0.004, 0.009, 0.130, 0.568 log CFU/g/h으로 온도에 비 례한 것으로 조사되었다. 2차 모델은 μmax의 경우, square root model, LPD는 polynomial equation을 사용하여 산출 하였고, 개발한 모델의 적합성을 평가하기 위해 통계적 지 표인 RMSE 값을 계산한 결과, 비교적 0에 가까운 0.42로 도출되어 모델이 적합한 것으로 확인되었다. 따라서 개발된 모델이 편육에 대한 황색포도상구균의 성장 예측모델로 사용 가능하다고 판단되어지며, 편육에서의 식중독을 예방하고 미생물학적 위생관리기준을 설정하는데 기초자 료로 활용될 수 있을 것으로 사료된다.

본 연구는 정량적 미생물 위해평가(Quantitative microbial risk assessment: QMRA)에 절대적으로 필요한 9종의 식중독 세균, 2종의 바이러스, 1종의 원생동물에 대한 최소 감염량(minimum infective dose)을 선정한 연구이다. 주요 식 중독 미생물들의 최소 감염량을 선정하기 위하여, 1980년부터 2012년까지 PubMed, ScienceDirect database 등에서 주요 식중독 미생물들의 최소 감염량 및 위해평가 자료 82종을 수집하였다. 수집된 자료는 메타분석(mata-analysis) 에서 사용되고 있는 relative frequency(fi, 상대빈도 값)를 계 산하여 가장 적정한 최소 감염량을 추정 및 선정하였다. 주요 식중독 미생물들의 최소 감염량은, B. cereus 105 cells/g (fi = 0.32), C. jejuni 500 cells/g (fi = 0.57), Cl. perfringens 107 cells/g (fi = 0.56), Pathogenic E. coli 중 EHEC 10 cells/ g (fi = 0.47), ETEC 108 cells/g (fi = 0.71), EPEC 106 cells/g (fi = 0.70), EIEC 106 cells/g (fi = 0.60), L. monocytogenes 102~103 cells/g (fi = 0.23), Salmonella spp. 10 cells/g (fi = 0.30), Shigella spp. 100 cells/g (fi = 0.32), S. aureus 105 cells/g (fi = 0.45), V. parahaemolyticus 106 cells/g (fi = 0.64), Hepatitis A virus 10~102 particles/g (fi = 0.33), Noro virus 10 particles/g (fi = 0.71), C. pavum 10~102 oocyst/g (fi = 0.33)으로 나타났다. 본 연구결과는 향후 국내 QMRA를 통한 위해수준 추정결과의 정확성을 향상시키는데 기여할 수 있을 것으로 기대된다.

본 연구는 정량적 미생물 위해평가(Quantitative microbial risk assessment: QMRA)에 절대적으로 필요하지만 국내의 경우 관련 정보 및 자료가 부족한 주요 식중독 원인 미생물에 대한 용량-반응모델(dose-response models) 관련 자료를 수집·정리하여 가장 적합한 용량-반응 모델을 분석 및 선정하였다. 1980년부터 2012년까지 식중독 발생과 관련이 있는 26종의 세균, 9종의 바이러스, 8종의 원생동물 관련 용량-반응 모델 및 위해평가 자료들을 중심으로 국내 NDSL (National Digital Science Library), 국외 PubMed, ScienceDirect database에서 총 193개의 논문을 추출하여 정리하였다. 조사된 자료로부터 세균별, 바이러스별, 원생 동물별 용량-반응 모델의 미생물 위해평가 활용여부를 확인하고, 위해평가에 활용된 모델들을 메타분석(meta-analysis) 에서 사용되고 있는 Relative frequency (fi, 상대빈도 값) 를 계산하여 가장 적정한 용량-반응 모델을 제시하였다. 주요 식중독 원인 미생물들인 Campylobacter jejuni, pathogenic E. coli O157:H7 (EHEC / EPEC / ETEC), Listeria monocytogenes, Salmonella spp., Shigella spp., Staphylococcus aureus, Vibrio parahaemolyticus, Vibrio cholera, Rota virus, Cryptosporidium pavum의 적정 용량-반응 모델 은 beta-poisson (α = 0.15, β = 7.59, fi = 0.72), beta-poisson (α = 0.49, β = 1.81 × 105, fi = 0.67) / beta-poisson (α = 0.22, β = 8.70 × 103, fi = 0.40) / beta-poisson (α = 0.18, β = 8.60 × 107, fi = 0.60), exponential (r = 1.18 × 10−10, fi = 0.14), betapoisson (α = 0.11, β = 6,097, fi = 0.09), beta-poisson (α = 0.21, β = 1,120, fi = 0.15), exponential (r = 7.64 × 10−8, fi = 1.00), beta-poisson (α = 0.17, β = 1.18 × 105, fi = 1.00), betapoisson (α = 0.25, β = 16.2, fi = 0.57), exponential (r = 1.73 × 10−2, fi = 1.00), and exponential (r = 1.73 × 10−2, fi = 0.17) 로 각각 선정하였다. 본 연구에서 제시된 용량-반응 모델 들은 향후 국내 QMRA 관련 연구 및 진행에 많은 도움이 될 것으로 기대된다.

Recently pathogenic E. coli is one of the main foodborne pathogens resulting in many patients in Korea. To understand the characteristics of pathogenic E. coli outbreaks in Korea, the epidemiological investigation reports of pathogenic E. coli outbreak in 2009 (41 reports) and in 2010 (27 reports) were collected in the web site of the Korea Centers for Disease Control and Prevention, reviewed and analysed in this study. The main places of the pathogenic E. coli outbreaks were food catering service area (64.8%) and restaurants (25.0%). The main type of the pathogens were EPEC (44.7%) and ETEC (34.2%). EAEC and EHEC was responsible for 10.5 and 9.2%, respectively. Eight of 68 outbreak cases were caused by more than 2 types of pathogenic E. coli which implicates the complicated contamination pathways of pathogenic E. coli. The incidence rate of pathogenic E. coli was 33.6 ± 30.5% and the main symptoms were diarrhea, stomach ache, nausea, vomiting, and fever etc. The two identified food sources were identified as frozen hamburger pattie and squid-vegetable mixture. To improve the food source identification by epidemiological investigation, food poisoning notification to the agency should not be delayed, whole food items attributed the outbreak should be collected and detection method of the various pathogenic E. coli in food has to be improved. In conclusion, the characteristics between the EHEC outbreaks in the western countries and the EPEC or ETEC outbreaks in Korea needs to be distinguished to prepare food safety management plan. In addition, the development of the trace back system to find the contamination pathway with the improved detection method in food and systemic and cooperative support by the related agencies are necessary.

This study was conducted to investigate the microbiological contamination levels in rice cakes and rice flour due to climate change in three areas classified to their temperature and precipitation. We investigated the contamination levels of total aerobic bacteria, coliforms, Escherichia coli, Bacillus cereus, Staphylococcus aureus, Clostridium perfringens of rice flour and 3 rice cakes such as Garaetteok, Sirutteok and Gyeongdan. Contamination levels of total aerobic bacteria in rice flour were 4.9 log CFU/g. In a total of 70 rice flour, yeasts & molds and coliforms were detected in 42 and 52 samples at the levels of 43 CFU/g and 1.29 log CFU/g, respectively. S. aureus were detected in only 1 rice flour (1.66 log CFU/g) out of 70. In an investigation of contamination levels in rice cakes, the population of total aerobic bacteria were highest in Gyeongdan (5.18 log CFU/g) and coliforms were highest in Gareattock (2.93 log CFU/g). There was no detection of E. coli and B. cereus except for only 1 Gareattock (1.20 log CFU/g). There were no differences of contamination levels among the three areas. If constant monitoring of rice cakes and rice flour is conducted on the basis of this study, it is expected to be able to analyze the change of contamination levels in rice cakes and rice flour due to climate change.

This study was conducted to evaluate microbial contamination levels of Korea traditional rice cakes such as Sirutteok, Garaetteok and Gyeongdan in the manufacturing process and environment. The microbial contamination levels such as total aerobic bacteria, fungi, coliforms, Escherichia coli, Staphylococcus aureus, Bacillus cereus and Clostridium perfringens of rice cake products were analyzed. The contamination levels of total aerobic bacteria, coliforms, fungi and B. cereus in raw materials were in the range of 2.4~4.5, ND~1.9, 1.2~2.1 and 1.0~2.1 log CFU/g, respectively. The microbial contamination levels of total aerobic bacteria, coliforms, fungi and B. cereus in manufacturing process of rice cakes were increased in the soaking and grinding steps and were decreased in steaming step. E. coli, S. aureus and C. perfringens were not detected in any manufacturing process and environment. The microbial contamination levels of raw materials and final products of rice cake were suitable for microbial safety standard in Korea. However, the manufacturing environment such as equipments and employee's sanitation were in trouble for microbial safety. The results of this study suggest that safety education for personal hygiene and safety management in processing environment are continuously required to assure safety in working environment and employee's individual hygiene.

In this study, the contamination levels of total aerobic bacteria, E. coli, total coliform and S. aureus of seasoned dried fishes (SDF) in Korea were investigated. A total of 81 SDF samples were purchased randomly from 28 stores. Contamination range of total aerobic bacteria, total coliform and S. aureus were 150~1,700,000, 10~31,000and 10~220 CFU/g, respectively. E. coli was detected in only one samples in the qualitative test. We have analyzed quantitatively Staphylococcal enterotoxins (SE-type A, C and D) produced by S. aureus contaminated in SDF using a TECRA kit and standard curve. The curve equation was Y = 0.1499 * X + 0.1183 and maximum amount of SEs in SDF was 0.71 ng/ml. Reduction speed of S. aureus in SDF stored at 37 ℃ was the highest among the samples stored for 8 days at different temperature of 7, 18 and 37℃ . On the basis of the results, SDF in Korea can be contaminated by a variety of pathogenic bacteria. Therefore, precautionary measures are necessary for consumer protection, including the improvement of sanitary conditions in the processing plants in Korea.

Predictive mathematical models were developed for predicting the kinetics of growth of Listeria monocytogenes in smoked salmon, which is the popular ready-to-eat foods in the world, as a function of temperature (4, 10, 20 and 30℃). At these storage temperature, the primary growth curve fit well (r² = 0.989~0.996) to a Gompertz equation to obtain specific growth rate (SGR) and lag time (LT). The Polynomial model for natural logarithm transformation of the SGR and LT as a function of temperature was obtained by nonlinear regression (Prism, version 4.0,GraphPad Software). Results indicate L. monocytogenes growth was affected by temperature mainly, and SGR model equation is 365.3-31.94*Temperature+0.6661*Temperature^2 and LT model equation is 0.1162-0.01674*Temperature+0.0009303*Temperature^2. As storage temperature decreased 30℃ to 4℃, SGR decreased and LT increased respectively. Polynomial model was identified as appropriate secondary model for SGR and LT on the basis of most statistical indices such as bias factor (1.01 by SGR, 1.55 by LT) and accuracy factor (1.03 by SGR, 1.58 by LT).

Risk ranking must be determined for various hazards/food combinations to conduct microbial risk management effectively. Risk Ranger is a simple, easy-to-use calculation tool developed in Microsoft Excel and designed to rank the risk (low, medium, and high) for semi-quantitative microbial risk assessment. The user is required to answer 11 questions in Risk Ranger related to 1) severity of the hazard, 2) likelihood of a disease-causing dose of the hazard being present in the meal, and 3) the probability of exposure to the hazard in a defined time. This study determined the risk ranking for twenty three combinations of foodborne pathogens/potentially hazardous foods (PHFs) using a Risk Ranger. In this study, pathogenic E. coli in fresh cut produce salad was scored as 79, which was the highest rank among the 23 combinations of the foodborne pathogens and PHFs. On the other hand, zero risk was obtained with V. parahaemolyticus in sushi, Salmonella in meat products and E. coli O157:H7 in hamburger patties. Although Risk Ranger is very simple method to rate the risk of foodborne pathogens and PHFs combination, the accuracy of result was mainly affected by the availability and accuracy of data in the literature. According to the result of literature review, the data are needed for contamination rate of raw materials, consumption amount/frequency of PHFs, and the effect of processing on pathogen. Risk ranking must be continuously revalidated with new data.

In this study, predictive mathematical models were developed to predict the kinetics of Listeria monocytogenes growth in the mixed fresh-cut vegetables, which is the most popular ready-to-eat food in the world, as a function of temperature (4, 10, 20 and 30oC). At the specified storage temperatures, the primary growth curve fit well (r2 = 0.916~0.981) with a Gompertz and Baranyi equation to determine the specific growth rate (SGR). The Polynomial model for natural logarithm transformation of the SGR as a function of temperature was obtained by nonlinear regression (Prism, version 4.0, GraphPad Software). As the storage temperature decreased from 30oC to 4oC, the SGR decreased, respectively. Polynomial model was identified as appropriate secondary model for SGR on the basis of most statistical indices such as mean square error (MSE = 0.002718 by Gompertz, 0.055186 by Baranyi), bias factor (Bf = 1.050084 by Gompertz, 1.931472 by Baranyi) and accuracy factor (Af = 1.160767 by Gompertz, 2.137181 by Baranyi). Results indicate L. monocytogenes growth was affected by temperature mainly, and equation was developed by Gompertz model (−0.1606 + 0.0574*Temp + 0.0009*Temp*Temp) was more effective than equation was developed by Baranyi model (0.3502 − 0.0496*Temp + 0.0022*Temp* Temp) for specific growth rate prediction of L. monocytogenes in the mixed fresh-cut vegetables.

This research was conducted to assess applicability of photostimulated luminescence (PSL) and Thermoluminescence (TL) methods for investigation of infant and young children products, nut, seasoned dried fish,spice, dried fruits, fruit & vegetable, grain and marine products, which are not approved for irradiation in Korea. PSL results show that the photon counts of non-irradiated samples were lower than 700, while those of irradiated samples were higher than 700. In TL measurement, TL ratio of irradiated samples were higher than 0.1 or ones can decrease below 0.1 whereas the temperature range of TL Glow curve was between 150-250℃. Monitoring result about 8 class of 325 not approved to irradiated foods, photon counts of samples were less than 700, and after re-irradiation TL Ratio (TL₁/TL₂) through re-irradiation step at 1 kGy were higher than 0.1 for the all samples. Therefore, these results suggested that PSL and TL measurements were useful detection methods for 8 class food products not approved to irradiation in Korea and all sample (325 cases) were not irradiated when we analysed by PSL and TL methods.

This research was conducted to know application of Photostimulated luminescence (PSL) and Thermoluminescence (TL) methods by irradiation dose for leaching tea, sauces and starch approved in Korea. Leaching tea, sauces and starch powder were treated with 60Co gamma ray at dose 0~10 kGy for detection trial whether they are irradiated or not by measuring PSL and TL for whole samples. PSL values were less than threshold value 700 and were negative for non-irradiated samples but more than 5,000 and were positive for irradiated ones. PSL results of leaching tea and sauces showed the correct identification for non-irradiated and irradiated samples, respectively except starch samples. To enhance the reliability of the TL result, the first glow curve (TL1) was compared with the second glove curve (TL2) obtained after a re-irradiation step at 1 kGy. The TL ratio (TL₁/TL₂) was in good agreement with the reported TL threshold for both the non-irradiated (< 0.1) and irradiated (> 0.1) samples. TL results of leaching tea, sauces, starch showed the correct identification for non-irradiated and irradiated samples, respectively. This study was performed to know application of PSL and TL methods for leaching tea, sauces and starch, and the methods were able to detect the irradiation products.

As Standards and Specifications of the Saengsik-classes has been established since 2005 by KFDA. The microbial Standards and Specifications of the Saengsik-classes is as follows; no detection in Escherichia coli, colony forming unit less then 1,000/g in Bacillus cereus, colony forming unit less then 100/g in Clostridium perfringens respectively. Contamination levels of Total aerobic bacteria, Escherichia coli,, Bacillus cereus and Clostridium perfringens in Saengsik-classes were monitored. Total aerobic bacteria counts in Saengsik-classes was 1×10¹~5.3×107 cfu/g, for Bacillus cereus 1×10²~9×10² cfu/g, for Clostridium perfringens 1×10¹ cfu/g. Escherichia coli, was not isolated from all Saengsik-classes. Thess results will provide information for introduction of HACCP system to ensure microbial safety of Saengsik-classes.

In this study, microbial investigation is accomplished for 554 Jeot-kal samples (102 of Jeot-kal, 448 of Seasoned Jeot-kal and 4 of Sik-khe, respectively) that corresponds with Coliform-bacteria, Escherichia coli, Aerobic live bacteria as hygienic indicator microorganisms, and Staphylococcus aureus, Vibrio parahaemolyticus as Food-borne pathogenic microorganisms. Based on the methods in Korea Food Code, reliable data are obtained as follows; in 31.9% rate of the samples, Coliform bacteria are verified in the extent of 0~20,000 CFU/g as 2.3 logCFU/g. Especially, Seasoned Jeot-kal (37.7%, 2.3 logCFU/g) are detected to 6 and 2 folds higher than those of Jeot-kal, 5.9% and 1.4 logCFU/g. Likewise, Escherichia coli is detected from 9 samples only in Seasoned Jeot-kal, that includes seasoned squid, seasoned octopus, seasoned roe of pollack, seasoned large-eyed herring and seasoned hairtail. Aerobic live bacteria are also detected in the range of 0~8.9 × 108 CFU/g. Against salinity, E. coli are detected in samples only less than 10% salinity. Concomitantly, aerobic live bacteria count is decreased to 5.5~3.6 log CFU/g upon the salinity is increased up to 25%. However, S. aureus and V. parahaemolyticus are not detected in 554 samples, presumptively referring Jeot-kal products are somehow free from such food-borne pathogens. As the results above, we deliberately consider that the sanitary control in Jeot-kal, which be necessarily fermented- as well as non-microbially inactivated should be ensured in near future and also suggest an effectual microbial standard corresponding to the Negativity in E. coli for Jeot-kal products.