본 연구는 국내 배추 주산단지 5지역을 대상으로 배추 재배에 활용되는 농업용수를 각 지역의 수확 시기에 채취 하여 위생지표세균(총대장균군, 대장균, 장구균)과 이화학 성분을 분석함으로써 농업용수의 수질의 오염도를 조사하기 위하여 수행되었다. 그 결과 지하수 보다 지표수에서 위생지표세균이 높은 수준으로 검출되었다. 지표수의 경 우 총대장균군 1.96-4.96 log MPN/100 mL, 지하수의 경우 0-3.98 log MPN/100 mL 수준이었다. 장구균의 경우 지표 수에서 95% (72/75), 지하수에서 22% (8/36) 빈도로 검출 되었으며, 대장균의 경우 지표수에서 100% (72/75), 지하수에서 22% (8/36) 빈도로 검출되었다. 위생지표세균과 이 화학성분의 상관관계를 조사한 결과, 지표수의 경우 대장균군과 대장균은 총인과 상관성을 보였으며, 장구균은 부유물질과 생물학적산소요구량에 상관성을 보였다. 지하수의 경우 위생지표세균은 부유물질과 화학적산소요구량에 상관성을 보였다. 본 연구의 결과는 엽채류 재배에 사용되는 농업용수의 미생물 기준을 설정하기 위한 기초자료 로 활용될 수 있을 것으로 판단된다.

The purpose of this study was to investigate the main source of contamination of dried red pepper by assessing microbial loads on red peppers, washing water, washing machines, harvesting containers, and worker gloves that had come in contact with the dried red pepper. To estimate microbial loads, indicator bacteria (total bacteria, coliform bacteria and Escherichia coli) and pathogenic bacteria (E. coli O157:H7, Salmonella spp., Listeria monocytogenes, and Clostridium perfringens) were enumerated. The results showed that the numbers of indicator bacteria increased significantly after washing red peppers compared with that before washing (p<0.05). Moreover, E. coli and Listeria spp. were recovered from the red peppers after washing and from the ground water used in the washing process. The number of indicator bacteria on red peppers dried in the green house was lower than that on red peppers dried in a dry oven (p<0.05). However, E. coli O157:H7, Salmonella spp., L. monocytogenes, and C. perfringens were not detected. These results suggested that a disinfection technique may be needed during the washing step in order to prevent potential contamination. In addition, hygienic practices during the drying step using the dry oven, such as establishment of an optimal temperature, should be developed to enhance the safety of dried red pepper.

To establish good storage practices for hulled barley against mycotoxin contamination, we measured occurrence of fungi and mycotoxin in hulled barley grains under various storage conditions. Hulled barley grains collected from two places were stored in five different warehouses: 1) two without temperature control, 2) one with temperature controlled at 12°C, 3) a chamber set at 15°C/65% relative humidity, and 4) one seed storage set at 10°C. The samples were stored for six month with temperature and relative humidity monitored regularly. Every stored samples were retrieved after 0, 1, 3, and 6 month to investigate fungal and mycotoxin contamination. From the stored grains, Fusarium, Epicoccum, Alternaria, and Drechslera spp. were frequently detected. In the warehouses without temperature control, Fusarium and Alternaria spp. constantly decreased, whereas Drechslera spp. increased along with storage period. In the other warehouses with temperature controlled, Fusarium spp. decreased slowly and more than 2.5 log CFU/g of Fusarium spp. were detected after 6 month storage. The level of nivalenol was maintained during 0-3 month but increased after 6 month storage. There was no difference in the nivalenol levels between the warehouses. Therefore reducing storage period less than 6 months could be more effective to control nivalenol contamination in hulled barley grains.

This study was conducted to develop a predictive model for the growth of Escherichia coli strain RC-4-D isolated from red kohlrabi sprout seeds. We collected E. coli kinetic growth data during red kohlrabi seed sprouting under isothermal conditions (10, 15, 20, 25, and 30°C). Baranyi model was used as a primary order model for growth data. The maximum growth rate (μmax) and lag-phase duration (LPD) for each temperature (except for 10°C LPD) were determined. Three kinds of secondary models (suboptimal Ratkowsky square-root, Huang model, and Arrhenius-type model) were compared to elucidate the influence of temperature on E. coli growth rate. The model performance measures for three secondary models showed that the suboptimal Huang square-root model was more suitable in the accuracy (1.223) and the suboptimal Ratkowsky square-root model was less in the bias (0.999), respectively. Among three secondary order model used in this study, the suboptimal Ratkowsky square-root model showed best fit for the secondary model for describing the effect of temperature. This model can be utilized to predict E. coli behavior in red kohlrabi sprout production and to conduct microbial risk assessments.