Elle Andreen, a master’s student at Penn State University, was featured in a January webinar hosted by Mat Haan, Dan McFarland and John Tyson, all of Penn State Extension. In this webinar, Andreen explained her research exploring the relationship between rumination data and nutritional management, which she conducted alongside Dr. Kevin Harvatine. While their research is not completely finished, Andreen shared the initial findings of the project, as well as some of the information that can be found through rumination monitoring systems.
There are various monitoring systems that have been validated by researchers, a few of which Andreen addressed in her webinar. Some of the more popular monitors that are commercially available in the U.S. are SCR collars, SensOor eartags (which are distributed by Select Sires) and MooMonitor neck collars, made by DairyMaster. These systems “use an accelerometer to detect motion and an algorithm to interpret movements as behaviors.” The detection of rumination may vary, which Andreen explained by using an example where cows wearing both CowManager and SCR sensors reported 39 percent greater rumination times on average in the SCR sensors.
These systems can help farmers in many ways with the data they provide, and Andreen’s presentation explored a few of the things that can be monitored.
Baseline rumination
While there is no single factor that solely determines baseline rumination time, there are various factors that can help predict it – three of these being diet, milk production and individual cow variability. Rumination monitoring systems are built to detect the amount of time that a cow spends ruminating, which can then lead to more information relating to these three factors. Along with production factors, rumination data has also been successfully incorporated into heat cycles and breeding. Although it can sometimes provide false positives or negatives, the technology has proven to be trustworthy and can give farmers a better indication of the heat cycles of their animals. Rather than waiting for the vet to check each animal, this can give a good idea of cycles before the vet can get to the farm.
Events that may cause deviation
Not only can rumination monitors indicate a baseline of rumination time, but they can also detect variables that could cause the baseline to be skewed. There are multiple events that may cause rumination to deviate from the baseline, some of which include estrus, calving, metabolic conditions (especially around the transition period), gastric or other illnesses, and changes in milking or feeding frequency.
In the webinar, Andreen said monitors were able to detect a decrease in rumination leading up to and during the estrus period. Research also indicated the changes during estrus were not uniform in every cow.
Through the detections of rumination changes, these sensors are also able to tell farmers which event is causing the deviation in the baseline, which can be extremely helpful in managing each cow and her production.
Proper rumen function
Rumination plays a large role in indicating proper rumen function in cows, as well as impacting the function itself. Through increasing rumen pH, encouraging motility and mixing, and increasing the availability of substrate for microbes, optimal rumination leads to optimal feed digestion, which in turn leads to optimal production in the herd.
Andreen also explained some of the benefits of using rumination monitoring systems in a herd. Farmers who use this technology are able to detect any abnormalities that may be present in a specific cow, which means they are then able to make the appropriate changes in the appropriate area. These systems can provide a large amount of data relating to rumination, which can then give us information about other aspects of the cow’s daily life. Herd health and comfort are the most important things to a farmer who cares about his or her herd, and rumination monitoring systems can help farmers monitor each of these to provide the best care possible.
Callista Van De Hei is an English student at University of Wisconsin – Green Bay.