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 ± 3.55oC, with 2.5% of above 10oC, −3.2oC and 14.9oC as a minimum and maximum. Temperature distributions by space-locations was 0.80 ± 1.69oC, 0.59 ± 1.68oC, and 0.65 ± 1.46oC 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.

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 ℃ as mean (5% - 2.25 ℃ and 95% - 7.12 ℃, 48.78% exceed 5 ℃), and processing room temperature estimated 17 ℃ as mean (5% - 10.92 ℃ and 95% - 22.56 ℃, 71.178% exceed 15 ℃).