Abstract #240
Section: ADSA-SAD Dairy Production ORAL Competition
Session: SAD Undergraduate Production Oral Presentation Competition
Format: Oral
Day/Time: Monday 2:30 PM–2:45 PM
Location: Room 200 A
Session: SAD Undergraduate Production Oral Presentation Competition
Format: Oral
Day/Time: Monday 2:30 PM–2:45 PM
Location: Room 200 A
# 240
Automated temperature reading systems to detect fever in dairy cattle.
Megan M. Woodrum*1, Gustavo Mazon1, Joao H. C. Costa1, 1University of Kentucky, Lexington, KY.
Key Words: disease, health, precision dairy technology
Automated temperature reading systems to detect fever in dairy cattle.
Megan M. Woodrum*1, Gustavo Mazon1, Joao H. C. Costa1, 1University of Kentucky, Lexington, KY.
Fever is a biological response in animals that comes from their co-evolution with pathogens. When the immune system recognizes pathogens, a chain of events is activated that stimulates the hypothalamus to raise the body temperature above thermal homeostatic levels. Cattle’s normal body temperature range is from 38.0 to 39.3°C. Fever is defined as a cow’s body temperature reaching a temperature of 39.5°C. The rise in body temperature makes it difficult for bacteria and some viruses to replicate within cattle, giving a better chance for the animal to overcome the illness. The rapid immuno-response that produces fever often makes it the first detectable sign of illness, coming before changes in physical appearance. Rectal temperature has been the gold standard for disease detection for decades. However, reliance on rectal temperature is being questioned for its accuracy and convenience. To detect the onset of illness via initial change in body temperature, rectal temperature would need to be taken continuously. Individuals’ body temperatures can vary between animals, throughout the day, and in response to disease or stress. Because of this variance, a single temperature measurement has a high probability of being a false positive or false negative when identifying a fever. All individuals’ temperature patterns should be considered for accurate fever detection. The act of taking the rectal temperature of an animal may increase temperature, reducing the accuracy of the reading further. Automated temperature reading systems may provide a solution for inaccurate fever detection. Systems including infrared cameras, rumen boluses, and implanted or vaginally inserted temperature data loggers automatically measure temperature. Automated temperature measurements can provide more accurate readings and early fever detection. Studies show improvement with non-invasive and automatic systems that could allow for management practices and early detection of diseases. This would allow producers to limit the spread of disease and more effectively treat their livestock, reducing disease cost, and improving overall cattle health and welfare in the dairy field.
Key Words: disease, health, precision dairy technology