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What’s in a healthy cow?

Think about the healthiest cows in your herd. What defines them as your healthiest?

Is it their older age? Is it the fact they’ve never had mastitis? Or are they the ones that leave the fresh pen quickly after calving because they don’t have the lingering effects that come with milk fever, metritis, a retained placenta, ketosis or a DA?

We’re willing to bet that your healthiest cows are the ones you don’t even notice. They’re not on your radar because they simply go about their business, producing high-quality milk with no troubles to you or your team of employees.

We call those unnoticed cows, the four-event cows. If you look at a cow card on your herd management software program, you’ll recognize a four-event cow by the lack of items on her list. Throughout her lactation, she experiences only four events: 1-fresh; 2-bred; 3-confirmed pregnant; and 4-dry.

When those are the only four events in a cow’s lactation, chances are she’s profitable and healthy.

A healthy cow is the resulting sum of many parts: a solid nutrition program, exceptional transition and fresh cow care, proper milking procedures, comfortable housing – and the right genetics!

While genetics makes up only a small part of the full equation, it’s a real and measurable aspect of what’s in a healthy cow.

Healthy genetics?

In April of 2018, the Council on Dairy Cattle Breeding (CDCB) released a new set of health traits. These traits are based on the database of recorded cases of common, costly health problems in dairy cattle. These six new traits measure the resistance that animals will have to each respective health and metabolic issue and are in place to help dairy producers breed a next generation of healthier cows.

They include mastitis, labeled as MAST, ketosis (KETO), retained placenta (RETP), metritis (METR), displaced abomasum (DA), and milk fever (MFEV).

Taking advantage of the new health traits in your genetic plan offers a great opportunity to create healthier cows. Most of these new traits are also correlated with Productive Life, so if you want the simplest approach to healthier genetics, Productive Life has you covered.

 Healthier genetics, plain and simple

For more than two decades, PL has told us how many more, or fewer, months a cow is expected to produce within any given herd. While cows are most often culled because of low production or poor fertility, those reasons typically trace back to more specific health issues in the cow’s life.

Selecting for PL or the new health traits within your genetic plan will help you address any specific health issues in your herd.

We know this from the DairyComp analyses we’ve done on many large, progressive herds. In the following example, we analyzed the a well-managed, 2400-cow dairy that does a great job at accurately recording health events. We compared the animals whose sires had the highest average PL against the animals whose sires had the lowest PL values.

No animals are given preferential treatment – they are all cared for with the same, high level management practices. With no other differences separating these animals except their sires’ PL values, we compared how many health events each group had. We looked specifically at cases of mastitis, ketosis, retained placentas, metritis, displaced abomasum, and milk fever.

As expected, Table 1 shows that the cows in the High PL group had far fewer cases for each health event.

Table 1# of cowsAvg. Sire PLMastitisKetosisRetained PlacentaMetritisDisplaced Abomasum
Low PL cows6071.325822323329
High PL cows6006.279316167
Difference4.917919161722

The economics of healthy genetics

We know these health events have a cost attached to each case, and CDCB has calculated those figures. The dollar value put on each case is modest – not accounting for lost production or decreased fertility. Their calculated values only measure the direct costs associated with each trait.

Let’s take those costs and apply them to our example herd. To do this, we multiplied the dollar value per health event by the difference in number of events between the low PL group and the high PL group. Table 2 shows the economic impact of Productive Life within a 2100-cow dairy.

Table 2MastitisKetosisRetained PlacentaMetritisDisplaced AbomasumMilk Fever
CDCB-calculated cost per health event$75 $28 $68 $112 $197 $34
Difference in health events based on sire PL1791916172212
Total cost in this herd$13,425 $532 $1,088 $1,904 $4,334 $408
=$21,691

This farm saves a total of $21,691 just because of the genetics in its healthy cows!

Want healthier cows? Genetics will help.

If you include Productive Life, or any of the six new health traits, within your customized genetic plan, you will create a next generation of unnoticed cows – the type that produce well and go about their business with few health troubles.

Environment, cow comfort and management practices all play a leading role in the health of your herd. Now you also see how genetics can positively impact both cow health and the economic health of your dairy.

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The proof is in your numbers

Let us show you…

We can show you the proof that genetics are one of the cheapest investments you can make to improve the profitability and efficiency of your herd. Proof sheet numbers may seem unclear or unrealistic. So we break them down to see how they translate within your own herd.

When you use a herd management software program, we can create a genetic assessment of your herd to see if genetics really work on your farm.

Do your 2-year-olds give as many pounds of milk as their sires’ proofs predict? Do these cows become pregnant as quickly as their sires’ DPR numbers suggest? And do daughter stillbirth numbers prove to be accurate indicators of DOAs?

When we do a genetic assessment for your herd, it’s important to realize that we only take into account first-lactation animals in order to minimize environmental effects. Phenotype equals genetics plus environment. So when we eliminate – or at least minimize – environmental influences, the actual performance differences we see are due to genetics.

We want to show you how those proof numbers translate to more pounds of milk, more pregnancies and fewer stillborn calves. So here, we take one of our real DairyComp 305 analyses of a real 1,500-cow herd for answers.

The proof in genetics: PTA Milk (PTAM)

We start with PTAM, which tells us how many more pounds of milk a first-lactation animal will produce compared to herdmates on a 305-day ME basis. We set out to find if higher PTAM values on this farm actually convert to more pounds of milk in the tank.

In this example, we sort all first-lactation animals with a known Holstein sire ID, solely on their sires’ PTAM values. We then compare that to their actual 305-day ME milk records.

As Table 1 shows, based on genetics, we expect the top 25 percent of first-lactation heifers to produce 1,541 more pounds of milk on a 305ME basis than their lower PTAM counterparts. In reality, we see a 2,662-pound difference between the top PTAM animals and the bottom in actual daughter performance.

Table 1: How does selection for PTAM affect actual 305ME performance?
# of cowsAvg. Sire PTAMAvg. 305ME Production
Top 25% high sire PTAM178150844080
Bottom 25% low sire PTAM171-3341418
Difference15412662
This means that for every pound of milk this herd selects for, they actually get an additional 1.69 pounds of milk. So these first-lactation animals are producing well beyond their genetic potential.

Why do they get more than expected?

When we do most on-farm genetic assessments, we find that the 305ME values closely match the predicted difference based on sire PTAM. However, in this example, the production exceeds what’s expected by more than 1,100 pounds.

We often attribute that bonus milk top-level management, where genetics are allowed to express themselves. This particular herd provides a comfortable and consistent environment for all cows. All of these 2-year-olds are fed the same ration, housed in the same barn and given the same routine. At more than a 40,000-pound average 305ME, this is certainly a well-managed herd, which allows the top genetic animals to exceed their genetic production potential.

Perhaps even more importantly, the identification in this herd is more than 95 percent accurate. Without accurate identification, this analysis simply won’t work. That’s because some cows whose real sire information puts them in the bottom quartile will actually appear in the top quartile and vice-versa.

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Inbreeding: manage it to maximize profit

Inbreeding is a hot topic…

Are you concerned about whether genomics is creating too much inbreeding in the dairy cattle population? Many producers express their concern that sire options to prevent negative inbreeding effects continues to dwindle. We certainly don’t want to mate an animal to her father or brother, but we do need to ask what the real goal is in terms of inbreeding. Should we aim for zero percent inbreeding or rather manage it to maximize profit?

The linear effect of inbreeding depression

As animals become more related to each other, inbreeding depression, or sub-par productive performance, can occur. Inbreeding depression is not ideal. Yet you should still weigh the negative effects against the added profit you could see from greater genetic gains.

Many producers buy in to the common misconception of a magic level of inbreeding that we should never exceed. In reality, we’ve seen results from numerous studies over time that show the effects of inbreeding depression to be linear.

For every 1% increase in inbreeding for a mating, you will realize $22-24 less profit over the life of the resulting offspring. You will see the same cost, or loss, when going from 9% to 10% inbreeding as you see between 1% and 2%.

Genetic progress

It’s well-documented that inbreeding has risen each year since the mainstream adoption of AI. Despite this increase, dairy cattle have made significant strides in production traits like milk, fat, and protein. It’s safe to say that producers would not trade today’s high producing cows for the less inbred, but also lower producing, cows of the 1960’s.

Inbreeding and milk production graph

Real-herd examples

Let’s look into the records of a random cross-section of 10 upper Midwest dairies averaging 1,500 cows, who implement a mating program on their farm. This analysis shows how cows with superior genetics are more productive than cows with inferior genetics, despite the more highly productive group also being more inbred.

In this analysis, cows born between 2005 and 2010, with at least one lactation on record were included. Each individual herd was first analyzed separately, and cows were split into quartiles based on their individual level of inbreeding.

Total # of cows% InbredNM$Milk Deviation1st Lact 305-Day MilkPTA DPRAvg. 1st Lact Preg RatePTA PL
25% MOST inbred from each herd38107.0158649282580.422.51.4
25% LEAST inbred from each herd37844.5121296278750.422.60.9

Here, you can see the difference in genetics, 1st lactation milk production, and NM$ between the top 25% most inbred from each herd and top 25% least inbred animals from each herd. The most highly inbred quartile of cows was also the most genetically superior group of cows in each of these ten herds.

When we measure actual performance, genetics more than make up for inbreeding depression. The NM$ levels, pounds of milk and milk deviations were all favorable for the more highly inbred, but also more genetically superior group.

This doesn’t mean that a mating resulting in 25% inbreeding is the best option. Rather, when managed properly as part of a program, excellent genetics can outweigh the results of inbreeding depression.

You may not realize that current proof values already account for the bull’s level of predicted future inbreeding. Outcross sires see favorable adjustments. Whereas, PTA’s on sires that are more closely related to the average population are negatively impacted because of these adjustments.

Determining matings

Let’s check out an example to see how managing, rather than avoiding, inbreeding is the best route.

The example below shows three sire options to use for a mating in your herd. Sire 1 and sire 2 both offer high Net Merit $ levels. However, their 8% and 6.5% inbreeding levels would be above the suggested 6.25% industry standard. That alone could eliminate them as potential mating sires in many breeding programs. Sire 3 would be a logical outcross mating in this example, resulting in a mere 1% inbreeding.

Sire OptionSire NM$Inbreeding % with cow being bredEconomic loss due to inbreedingAdjusted NM$ for level of inbreeding
18548.0184693
28456.5150695
36051.023582
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