• Korean Journal of Food Science and Technology
• /
• v.42 no.4
• /
• pp.494-501
• /
• 2010

The purpose of this study was to examine the presence of Bacillus cereus, aerobic bacteria and coliforms in the raw material of infant formulas and investigate the manufacturing process in terms of microbial safety. Among ten kinds of raw infant formula material samples (n=20), Bacillus cereus appeared in two (n=4). Aerobic bacteria were not detected in raw infant formula material or maximum 4.15 log CFU/g. Eleven species of aerobic bacteria were isolated and 76% of them were Sphingomonas paucimobilis, Pseudomonas fluorescens, Rhizobium radiobactor, or Stenotrophomonas maltophilia. A Pearson's correlation analysis revealed that the most influential factors for detecting Bacillus cereus were aerobic bacteria and coliforms. In other words, when the measured values of aerobic bacteria and coliforms were higher, the possibility that Bacillus cereus would appear increased. In a regression model to predict Bacillus cereus, the rate of appearance was correlated with aerobic bacteria and coliforms, and its contribution rate for effectiveness was 86%. Improving microbial quality control by pasteurization, spray dry, popping and extrusion resulted in a decrease in the numbers of Bacillus cereus, aerobic bacteria and coliforms in the raw materials. The results suggest that a hazard analysis and critical control point system might be effective for reducing microbiological contamination.

• Korean Journal of Remote Sensing
• /
• v.36 no.5_1
• /
• pp.679-692
• /
• 2020

We coupled a CFD model to the WRF-Chem model (WRF-CFD model) and investigated the characteristics of flows and carbon monoxide (CO) distributions in a building-congested district. We validated the simulated results against the measured wind speeds, wind directions, and CO concentrations. The WRF-Chem model simulated the winds from southwesterly to southeasterly, overestimating the measured wind speeds. The statistical validation showed that the WRF-CFD model simulated the measured wind speeds more realistically than the WRF-Chem model. The WRF-Chem model significantly underestimated the measured CO concentrations, and the WRF-CFD model improved the CO concentration prediction. Based on the statistical validation results, the WRF-CFD model improved the performance in predicting the CO concentrations by taking complicatedly distributed buildings and mobiles sources of CO into account. At 04 KST on May 22, there was a downdraft around the AQMS, and airflow with a relatively low CO concentration was advected from the upper layer. Resultantly, the CO concentration was lower at the AQMS than the surrounding area. At 15 KST on May 22, there was an updraft around the AQMS. This resulted in a slightly higher CO concentration than the surroundings. The WRF-CFD model transported CO emitted from the mobile sources to the AQMS measurement altitude, well reproducing the measured CO concentration. At 18 KST on May 22, the WRF-CFD model simulated high CO concentrations because of high CO emission, broad updraft area, and an increase in turbulent diffusion cause by wind-shear increase near the ground.