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Defeat the ‘gray’ area of cow health with actionable data

Shane St. Cyr Published on 30 April 2014

Observation skills and experience are extremely beneficial to managing the health and performance of a dairy herd. Perceptive practitioners of animal husbandry can often tell you at a glance whether an animal is under the weather or is feeling perfectly fine by walking pens, observing feed intakes and monitoring cow behaviour for important hints.

And they are investing in technology like rumination monitoring to help with this essential task.

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But the best herd managers are always searching for ways to improve, whether through improved tools or greater understanding of cows.

They understand that an animal’s health status is not always so clear-cut, so black and white. A certain percentage of animals at any given time fall into a health status “gray area.” These animals do not show visual signs of illness, but they aren’t functioning at full strength, either.

They’re just a bit “off,” even though you may not be able to see it. These are the cows that benefit significantly from early interventions.

It may be less complicated to simply sort animals into “sick” or “well” categories, but not all cows fit neatly into these categories because not all health indicators are easily seen by the human eye.

There have been many studies documenting that fresh cow disease is preceded by nonspecific symptoms as much as five to 10 days prior to the onset of specific clinical signs.

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Some can be seen or visually measured: elevated core body temperature, reduced activity, drop in milk production, decline in dry matter intake and change in milk composition (high fat-to-protein ratios of more than 1.4). All of these are signals that indicate a need for immediate attention.

Meanwhile, other important health status indicators, such as time spent ruminating, are not so readily apparent, which is why astute managers are turning their focus toward this important parameter and moving out of the black-and-white mindset of animal health.

Rumination information
Data available via rumination monitoring technology enable users to track rumination levels, which is an early indicator of potential health and performance challenges.

An animal’s rumination will often drop 24 hours or more prior to the appearance of physical symptoms such as decreased feed intake or a reduction in milk production.

“If a cow is getting sick, we can catch it about a day earlier than we used to, before seeing it in lower milk production,” notes Joel Sutter, herd manager at Fertile Ridge Dairy, a 600-cow dairy near Mount Horeb, Wisconsin. “If we put her on medication, we’ll know much faster if she’s getting better or not.”

Monitoring cows for activity, rumination and temperature can really help with early detection of health disorders, agrees Marcia Endres, University of Minnesota Extension dairy scientist. “Treating cows earlier will help prevent large drops in production and reduce cow mortality on the farm,” she says, adding that access to this actionable data is critical from an animal welfare perspective as well as a management perspective.

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Health implications
While a “gray” health scenario can occur at any age or any stage of lactation, it commonly occurs during transition – the three weeks prior to and three weeks following calving.

This is when cows are most vulnerable to disease and metabolic disorders due to the many social, environmental and physiological changes that take place during this time frame.

Cows often fail to adapt to these metabolic and management changes, resulting in 75 percent of dairy cow disease incidence during the first month after calving and substantial economic losses to the dairy industry.

Also, one-third of dairy cows may be affected by some form of metabolic or infectious disease in early lactation.

The ability to head off transition disorders has longer-term health implications because of the negative and cumulative effect of these challenges.

  • Cows with milk fever had four times more risk of retained placenta and 24 times more incidence of ketosis than cows that did not have milk fever.

  • The risk of ketosis was elevated in cows that had either a retained placenta, displaced abomasum or case of milk fever.

  • In addition, subclinical ketosis in the first or second week after calving is associated with increased risk of displaced abomasum, metritis, clinical ketosis, endometritis, prolonged postpartum anovulation, increased severity of mastitis and lower milk production in early lactation.

Data in action
The following example highlights what could happen if you detect transition period “gray area” cows with rumination monitoring data. Remember, the goal is to quickly identify these animals, intervene as necessary and rapidly return them to healthy, productive status.

In this case, rumination data helped identify a cow with lower prepartum dry matter intake. The drop in rumination time is important because research shows that cows with lower rumination time before calving also often have lower rumination time after calving – and suffer a larger frequency of disease than cows with higher rumination time in late pregnancy.

Rumination data for a cow with decreased rumination

Click here or on the image above to view it at full size in a new window. (PDF, 118 KB)

Figure 1 shows rumination data for a cow with decreased rumination prior to calving and the resulting metabolic challenges she faced in early lactation.

These rumination data show:

  • December 24: Rumination nearly 600 minutes
  • January 1: A steady, week-long decline in rumination minutes
  • January 2: Calving
  • January 2-4: Slight recovery
  • January 5: Displaced abomasum

An intervention at the time of the decrease in rumination and a proactive approach at the time of calving could have helped improve this cow’s health status after calving.

Instead, this cow suffered a displaced abomasum, which ultimately led to nearly a full month of diminished health and productivity.

Putting it all together
“This technology is really exciting,” says Endres. “Not only does it help dairy managers prioritize their attention on individual cows that require extra attention or interventions, the data generated on a herd basis help producers and their management team track larger health trends so they can adjust management strategies accordingly.

“Individual cows become sentinel cows – the canary in the coal mine, if you will – that signify when a practice, treatment protocol or other management decisions needs to be adjusted to improve animal health and well-being,” she says. “It is helping farmers do a better job.” PD

References omitted due to space but are available upon request. Click here to email an editor.

Shane St Cyr
Shane St. Cyr
Field Support Manager
SCR Dairy Inc.

 

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