• Food Science and Biotechnology
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• v.18 no.1
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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.

• Korean Journal of Food Science and Technology
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• v.42 no.3
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• pp.373-376
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• 2010

The objective of this study was to present the proper probability distribution model based on the data obtained from surveys on domestic refrigerator food storage temperatures in home. Domestic refrigerator temperatures were determined as risk factors in foodborne disease outbreaks for microbial risk assessment (MRA). The temperature was measured by directly visiting 139 homes using a data logger from May to September of 2009. The overall mean temperature for all the refrigerators in the survey was $3.53{\pm}2.96^{\circ}C$, with 23.6% of the refrigerators measuring above $5^{\circ}C$. Probability distributions were also created using @RISK program based on the measured temperature data. Statistical ranking was determined by the goodness of fit (GOF, i.e., the Kolmogorov-Smirnov (KS) or Anderson-Darling (AD) test) to determine the proper probability distribution model. This result showed that the LogLogistic (-10.407, 13.616, 8.6107) distribution was found to be the most appropriate for the MRA model. The results of this study might be directly used as input variables in exposure evaluation for conducting MRA.

• Journal of Food Hygiene and Safety
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• v.18 no.3
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• pp.107-112
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• 2003

Probabilistic exposure assessment has been recognized as an important tool in microbial risk assessment, because of obtained the desired results to characterize of variability and uncertainty associated with the microbial hazards. In addition, it will be provided much more actuality information than the point-estimate approaches. In this study, we present methodology using mathematical probability distribution in exposure assessment and estimating of contamination level of Listeria monocytogenes in meat and meat products as a case study. The result of estimation contaminatin level was mean ($50^{th}$ percentile) -4.08 Log CFU/g minimum ($5^{th}$ percentile) -4.88 Log CFU/g, maximum ($95^{th}$ percentile) -3.56 Log CFU/g.

• Journal of Food Hygiene and Safety
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• v.24 no.1
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• pp.63-68
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• 2009

The statistics probability approach for microbial risk assessment (MRA) has been recognized as an efficient method because this probability approach, which can be presented the diversity, variability, and uncertainty for the environmental factors of food processing, provide better realistic results than point estimate. This study was conducted to determine of probability statistics for the environmental factors of the pork-cutting processing i.e. the processing time, the pork meat temperature, and processing room temperature etc. As the input parameters for the MRA, triangular distribution and normal distribution were selected as an efficient probability distribution model, these distributions were analyzed by the simulation. The simulation results showed the processing time estimated 53 min as mean (5% - 22 min and 95% - 98 min), pork meat temperature estimated $4.83^{\circ}C$ as mean (5% - $2.25^{\circ}C$ and 95% - $7.12^{\circ}C$, 48.78% exceed $5^{\circ}C$), and processing room temperature estimated $17^{\circ}C$ as mean (5% - $10.92^{\circ}C$ and 95% - $22.56^{\circ}C$, 71.178% exceed $15^{\circ}C$).

• The Korean Journal of Community Living Science
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• v.15 no.2
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• pp.167-177
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• 2004

The number of foodborne salmonellosis was estimated by using microbial risk assessment(MRA) methodology and the possibility of application was studied through comparison with previous results. The contamination levels of Salmonella sp. were estimated by using published domestic studies(1997∼2000) and monitoring data (1999∼2001) from food-safety related institutes. Data on food consumption came from the 2001 National Health and Nutrition Survey, and dose-response models from studies in other countries. Simulation results showed that there were 753,368 cases of salmonellosis in Korea in 1 year, which is about 115 times that reported in previous years and lower than the WHO's estimation increase. From these results, microbial risk assessment is likely to be available for estimation of the number of foodborne illnesses and determination of the order of priority in food-safety management. Butthe verification methods are not established and most of the data on contamination levels of foodborne bacteria, food consumption, and dose-response relationships have not been established. In addition, the actual conditions of circulation, storage and cooking must be studied further.

• Journal of Food Hygiene and Safety
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• v.34 no.2
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• pp.199-204
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• 2019

This study aimed to generate a probability distribution model based on temperature data of frozen food storage facility as input variables for microbial risk assessment (MRA). We visited 8 food-handling businesses to collect temperature data from their cold storage warehouses. The overall mean temperature inside the storage facilities was $-20.48{\pm}3.08^{\circ}C$, with 20.4% of the facilities having above $-18^{\circ}C$, with minimum and maximum temperature values of -10.3 and $-25.80^{\circ}C$ respectively. Temperature distributions by space locations of natural and forced convection were $-22.57{\pm}0.84$ and $-17.81{\pm}1.47^{\circ}C$, $-22.49{\pm}1.05$ and $-17.94{\pm}1.44^{\circ}C$, and $-22.68{\pm}1.03$ and $-18.08{\pm}1.42^{\circ}C$ in the upper (2.4~4 m), middle (1.5~2.4 m), and lower (0.7~1.5 m) shelves, respectively. Probability distributions from the temperature data were obtained using the program @RISK. Statistical ranking was determined using goodness of fit to determine the probability distribution model. Our results show that a log-normal distribution [5.9731, 3.3483, shift (-26.4281)] is most appropriate for relative MRA conduction.

• Journal of Food Hygiene and Safety
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• v.27 no.3
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• pp.312-316
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• 2012

This study was to present the proper probability distribution models that based on the data for surveys of food cold storage temperatures as the input variables to the further MRA (Microbial risk assessment). The temperature was measured by directly visiting 7 food plants. The overall mean temperature for food cold storages in the survey was $2.55{\pm}3.55^{\circ}C$, with 2.5% of above $10^{\circ}C$, $-3.2^{\circ}C$ and $14.9^{\circ}C$ as a minimum and maximum. Temperature distributions by space-locations was $0.80{\pm}1.69^{\circ}C$, $0.59{\pm}1.68^{\circ}C$, and $0.65{\pm}1.46^{\circ}C$ as an upper (2.4~4 m), middle (1.5~2.4 m), and lower (0.7~1.5 m), respectively. Probability distributions were also created using @RISK program based on the measured temperature data. Statistical ranking was determined by the goodness of fit (GOF) to determine the proper probability distribution model. This result showed that the LogLogistic (-4.189, 5.9098, 3.2565) distribution models was found to be the most appropriate for relative MRA conduction.

• Journal of Food Hygiene and Safety
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• v.24 no.1
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• pp.50-55
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• 2009

Ready-to-eats fresh cut-vegetables that may be consumed without further cooking or reheating can be grouped as potentially high risk foods. The foodborne disease outbreaks associated with consumption of the fresh cut-vegetables have been related with the contamination of Listeria monocytogenes. The food survey and consumption data sets for fresh cut-vegetables and also the published dose-response models for L. monocytogenes, was used to estimate the risk of L. monocytogenes for fresh cut-vegetables in Korea. Also, the simulation model and formulas with Microsoft@ Excel spreadsheet program using these data sets and chose dose-response model was developed. The mean case of listeriosis by consumption of the fresh cut-vegetables per 10 million per year was estimated as $3.23{\times}10^{-6}$. Results suggest that additional studies were needed to allow for a more realistic and accurate microbial risk assessment (MRA) in the future.

• Journal of Food Hygiene and Safety
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• v.24 no.3
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• pp.226-231
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• 2009

The aim of this study was to determine exposure assessment of pathogenic bacteria in edible ices by using the monitoring data from the previous study. According to the results of exposure assessment of edible ices contaminated with S. aureus, the contamination level of S. aureus in raw materials was higher than other foodborne pathogens, and the contamination level of S. aureus in mixed samples increased much before sterilization. The most significant reduction in contamination level was observed in mixed samples after sterilization, thus, the contamination levels in frozen final products was less than that of raw materials. Overall, the possibility for the infection of foodborne bacteria from the intake of edible ices per person per day was ranged from minimum $5.89{\times}10^{-7}$ to maximum $5.01{\tims}10^{-5}$. For more realistic estimates, consumption of edible ices and dose-response model must be studied further.

• Journal of Food Hygiene and Safety
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• v.32 no.1
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• pp.20-26
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• 2017

Foodborne disease outbreaks associated with produces have been increasing in occurrence worldwide. This study investigated microbial contamination levels on thirteen kinds of agricultural products from farms stage to evaluate potential hazards associated with foodborne illness. A total of 1,820 samples were collected in major cultivating area from 2013 through 2015, and analyzed to enumerate aerobic bacterial counts, coliforms/E. coli, Bacillus cereus and Staphylococcus aureus. In addition, the prevalence study for four kinds of microorganisms (Escherichia coli, E. coli O157:H7, Salmonella spp. and Listeria monocytogenes) was performed on each sample. Aerobic bacterial counts ranged from 0.01 to 7.18 log CFU/g, with the highest bacterial cell counts recorded for watermelon. Coliforms were detected in 651 samples (35.8%) with a minimum of 0.01 log CFU/g and a maximum of more than 5 log CFU/g. B. cereus was detected in 169 samples (9.3%) ranging from < 0.01 to 2.48 log CFU/g among total samples analyzed. S. aureus was detected in 14 samples (0.7%) with a minimum of 0.01 log CFU/g and a maximum of 1.69 log CFU/g. E. coli was detected in 101 samples (5.5%) among 1,820 samples. E. coli O157:H7, Salmonella spp. and L. monocytogenes were not detected in any of the samples. The microbial contamination levels of several agricultural products determined in this study may be used as the fundamental data for microbiological risk assessment (MRA).