• Journal of Dairy Science and Biotechnology
• /
• v.36 no.4
• /
• pp.196-207
• /
• 2018

This study was carried out to investigate the rheological properties and composition of unsaturated fatty acid of farm butter made from the milk of cows grazing at high mountain pasture in Pyronogchang SKY ranch (above sea level, 935 m). From two groups containing 7 cows each, a group was fed in-door with TMR (total mixed ration) feed and whereas the other group was grazed pastures for 12 h. The daily intake of feed on basis of dry matter (DMI), milk yields, concentration of milk constituents, and fatty acid profile of pasture milk were compared with control TMR milk. In addition, the physiochemical properties and composition of unsaturated fatty acids of the butter were also compared with those of the butter made from control TMR milk. Upon comparison, the health-promoting index (HPI) of fatty acids; the ratio of omega-6 fatty acids to omega-3 fatty acids (n-6 to n-3 UFA), the atherogenicity index (AI), and the ratio of linoleic acid to ${\alpha}$-linolenic acid (LA to ALA) was apparently improved in farm butter than those of control butter. Thus, it could make the dairy farm visitors to consume the farm butter containing the health-promoting fatty acids from the milk of cows grazing on mountain pasture.

• Journal of Food Hygiene and Safety
• /
• v.38 no.4
• /
• pp.228-235
• /
• 2023

Peanut is a well-known food allergen that causes adverse reactions ranging from mild urticaria to life-threatening anaphylaxis. Consumers suffering from peanut allergies should thus avoid consuming undeclared peanuts in processed foods. Therefore, effective cleaning methods are needed to remove food allergens from manufacturing facilities. To address this, wet cleaning methods with washing water at different temperatures, abstergents (peracetic acid, sodium bicarbonate, dilute sodium hypochlorite, detergent), and cleaning tools (brush, sponge, paper towel, and cotton) were investigated to remove peanuts from materials used in food manufacture, including plastics, wood, glass, and stainless steel. Peanut butter was coated on the surface of the glass, wood, stainless steel, and plastic for 30 min and cleaned using wet cleaning. The peanut residue on the cleaned surfaces was swabbed and determined using an optimized enzyme-linked immunosorbent assay (ELISA). Cleaning using a brush and hot water above 50℃ showed an effective reduction of peanut residue from the surface. However, removing peanuts from wooden surfaces was complicated. These results provide information for selecting appropriate materials in food manufacturing facilities and cleaning methods to remove food allergens. Additionally, the cleaning methods developed in this study can be applied to further research on removing other food allergens.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.20 no.2
• /
• pp.60-74
• /
• 2017

To facilitate prevention of highly pathogenic avian influenza (HPAI), a GIS is widely used for monitoring, investigating epidemics, managing HPAI-infected farms, and eradicating the disease. After the outbreak of foot-and-mouth disease in 2010 and 2011, the government of the Republic of Korea (ROK) established the GIS-based Korean Animal Health Integrated System (KAHIS) to avert livestock epidemics, including HPAI. However, the KAHIS is not sufficient for controlling HPAI outbreaks due to lack of responsibility in fieldwork, such as sterilization of HPAI-infected poultry farms and regions, control of infected animal movement, and implementation of an eradication strategy. An outbreak prediction model to support efficient HPAI control in the ROK is proposed here, constructed via analysis of HPAI outbreak patterns in the ROK. The results show that 82% of HPAI outbreaks occurred in Jeolla and Chungcheong Provinces. The density of poultry farms in these regions were $2.2{\pm}1.1/km^2$ and $4.2{\pm}5.6/km^2$, respectively. In addition, reared animal numbers ranged between 6,537 and 24,250 individuals in poultry farms located in HPAI outbreak regions. Following identification of poultry farms in HPAI outbreak regions, an HPAI outbreak prediction model was designed using factors such as the habitat range for migratory birds(HMB), freshwater system characteristics, and local road networks. Using these factors, poultry farms which reared 6,500-25,000 individuals were filtered and compared with number of farms actually affected by HPAI outbreaks in the ROK. The HPAI prediction model shows that 90.0% of the number of poultry farms and 54.8% of the locations of poultry farms overlapped between an actual HPAI outbreak poultry farms reported in 2014 and poultry farms estimated by HPAI outbreak prediction model in the present study. These results clearly show that the HPAI outbreak prediction model is applicable for estimating HPAI outbreak regions in ROK.