Three dairymen who installed rumination and activity monitoring systems over five years ago share their experiences and advice from the East, Midwest and West regions.

Dairyman Michael Johnson’s journey toward activity monitoring started several years ago when he realized his plate was getting too full to handle everything.

The importance of transition cow management is well-known. But until recently, there have been unknowns about early disease indicators which impact the health of transition cows and heifers.

Estrus detection in dairy cattle is one of the biggest issues in the dairy industry. Thus, technology has brought us automated activity monitors (AAMs) to better identify estrus behaviour, with the goal of getting cows pregnant efficiently.

Collecting and analyzing critical data points, from activity to rumination, for every individual cow can be a struggle for many dairy farms. But this type of information is paramount in maintaining the health and well-being of an entire herd.

There are so many factors that affect how efficiently you can get cows pregnant. Cow comfort. Cow cooling. Nutrition. Herd health. Genetics. Dry cow, transition and fresh cow management. And the list goes on.

“I installed an automated heat detection system, but it is flagging cows that are not in heat. I’m so frustrated.” This is a very common complaint from dairy farmers. They are told an activity system will find the cows in heat better than their personnel, which is true, but they are never told what to do with the extra cows on the list. 

Normally, the cattle and beef production discussion in the February report would reflect cattle inventory data from the USDA National Agricultural Statistics Service (NASS) Cattle report in this month’s report. However, due to the government shutdown, the Cattle report was not to be released until Feb. 28.

The onset of estrus in dairy cattle is accompanied by changes in physiological activity, rumination and feeding behavior. These alterations can be monitored via direct observation or through the use of automatic sensors to identify deviations associated with estrus, subclinical illness or lameness.