To investigate the epidemiological characteristics of 68 Listeria monocytogenes isolates, including 11 reference strains and 57 isolates from imported US beef, domestic meats(beef, pork, chicken meat), raw milk, and milk plants. L. monocytogenes was to evaluate the production of virulence proteins, such as hemolysin(LLO) and lecithinase(LCP), the adsorption of Congo red(CRA), and to detect virulence genes using the polymerase chain reaction(PCR). In the study of virulence protein production, 68(100%), 62(91.2%), and 54(79.4%) of the 68 L. monocytogenes strains were positive for LLO production, the LCP test, and the CRA test, respectively, while strains of other species, such as L. innocua, L. gray, L. murrayi, and L. welshimeri, were not. There were no significant differences between L. monocytogenes serotypes and the ability to produce LLO or LCP. L. monocytogenesstrains had very high hemolytic titers(2 to 16 fold), while the other Listeria species, other than L. ivanovii and L. seeligeri, did not. The hemolysin activities of L. monocytogenes, L. ivanovii, and L. seeligeri usually exceeded 1.0 HU/mg, while those of other Listeria spp. were less than 0.04 HU/mg. In the PCR assay, all of the L. monocytogenes strains contained the hlyA, plcA, plcB, inlA, and inlB virulence genes and produced a product of the expected size. In the PCR of the actA gene, the expected 385-bp product was seen in 39(57.4%) L. monocytogenesstrains, while an unexpected 268-bp product was seen in 29(42.6%) strains. Most L. monocytogenes strains isolated from Hanwoo beef produced the 385-bp actA gene product, while strains of imported US beef usually produced the 268-bp actA gene product. By contrast, no virulence gene products were amplified in the other Listeria spp.
Agriculture is a primary industry that influenced by the weather or meterological factors more than other industry. Global warming and worldwide climate changes, and unusual weather phenomena are fatal in agricultural industry and human life. Therefore, many previous studies have been made to find the relationship between weather and the productivity of agriculture. Meterological factors also influence on the distribution of agricultural product. For example, price of agricultural product is determined in the market, and also influenced by the weather of the market. However, there is only a few study was made to find this link. The objective of this study is to investigate the effects of meterological factors on the distribution of agricultural products, focusing on the distribution of chinese cabbages. Chinese cabbage is a main ingredient of Kimchi, and basic essential vegetable in Korean dinner table. However, the production of chinese cabbages is influenced by weather and very fluctuating so that the variation of its price is so unstable. Therefore, both consumers and farmers do not feel comfortable at the unstable price of chinese cabbages. In this study, we analyze the real transaction data of chinese cabbage in wholesale markets and meterological factors depending on the variety and geography. We collect and analyze data of meterological factors such as temperatures, humidity, cloudiness, rainfall, snowfall, wind speed, insolation, sunshine duration in producing and consuming region of chinese cabbages. The result of this study shows that the meterological factors such as temperature and humidity significantly influence on the volume and price of chinese cabbage transaction in wholesale market. Especially, the weather of consuming region has greater correlation effects on transaction than that of producing region in all types of chinese cabbages. Among the whole agricultural lifecycle of chinese cabbages, 'seeding - harvest - shipment - wholesale', meterological factors such as temperature and rainfall in shipment and wholesale period are significantly correlated with transaction volume and price of crops. Based on the result of correlation analysis, we make a regression analysis to verify the meterological factors' effects on the volume and price of chines cabbage transaction in wholesale market. The results of stepwise regression analysis are shown in