Abstract #20
Section: CSAS Symposium: From Data to Decisions—The Next Step for Technology in Dairy Production (Invitation Only)
Session: CSAS Symposium: From Data to Decisions—The Next Step for Technology in Dairy Production
Format: Oral
Day/Time: Monday 11:30 AM–12:00 PM
Location: Room 206
Presentation is being recorded
Session: CSAS Symposium: From Data to Decisions—The Next Step for Technology in Dairy Production
Format: Oral
Day/Time: Monday 11:30 AM–12:00 PM
Location: Room 206
Presentation is being recorded
# 20
Monitoring dairy cow feeding behavior to optimize nutritional management.
T. J. DeVries*1, 1Department of Animal Biosciences, University of Guelph, Guelph, ON, Canada.
Key Words: automation, feeding behavior, nutrition
Monitoring dairy cow feeding behavior to optimize nutritional management.
T. J. DeVries*1, 1Department of Animal Biosciences, University of Guelph, Guelph, ON, Canada.
The dairy industry has an increasing availability of equipment that is readily available for the automation of management tasks, including milking and feeding, as well as the monitoring of dairy cow behavior. Such automation not only has the ability to improve production and time efficiency on farm, but also increases our ability to monitor individual cows. Much research has been focused on the use of individual behavioral monitoring to detect health disorders, both in occurrence and in advance of clinical symptoms. This, in turn, has the potential to allow producers to identify and implement prevention and treatment protocols at earlier time points. There is, however, also an opportunity to use behavioral monitoring to inform management decisions on farm. Given the inherent relationship between feeding behavior, feed intake, dietary composition, and nutritional management, there is opportunity to use information of feeding behavior to optimize nutritional management. This presentation will, thus, specifically focus on how when, and what cows eat and ruminate their feed and the relationship of that behavior with nutrient intake, health, and production. Specific examples will then be provided to demonstrate the utility of monitoring changes in said behavior, with the goal of informing decisions related to nutritional management. Limitations and challenges associated with such monitoring will also be discussed. Long-term, it is anticipated that through precision monitoring of feeding behavior, particularly with the aid of automation, dairy producers will be able to make more timely decisions for altering and adjusting nutritional programs, both at a cow and herd level, to optimize cow health, welfare, and production.
Key Words: automation, feeding behavior, nutrition