Thursday, June 30, 2016

The Next Generation

The beef industry values sustainability. We value successful operations that are passed on to generation after generation. That is why beef producers support  youth programs.

Those of you who know me personally, know I am way too busy for my own good.  I've learned to say no and am making strides in simplifying. When the beef project leader in my kid's 4-H club came open, I should have kept my mouth shut. Instead, I volunteered to be the leader, because I value educating youth. I wanted to pay it forward and help kids fall in love with cattle the way I did.

On Friday July 8th will be our Sturgeon Beef Show. I hope those of you in mid-Missouri will come out and enjoy the successes of our youth.

If you are interested in sponsoring a breed champion, please let me know. Thanks to those who have already sponsored.

Watch the blog for pictures of my little ones falling in love with cattle. If you time driving by my house just right,  you might even catch a glimpse of a computational geneticist trying to catch a calf out in the pasture. :)


Saturday, June 25, 2016

BIF 2016: Genomics, return on investment - fact or fiction?

Tonya Amen
Consultant for Illumina, Inc.

One dairy operation was making $35 per year progress for net merit. After using genomics in late 2009, they were making $50 per year in progress for net merit. After they started testing females, this rate increased to nearly $80.
This dairy herd is now seeing $340 more in life time production by using genomics.

From 2005 to 2008, $B was increasing by $3.77 per year.
From 2009 to 2015, $B increased by $5.62 per year.

From 2013 to 2015, $B increased by $9.31 per year.
A 146% increase in genetic trend.

We have seen more rapid genetic improvement in Angus, Hereford and Simmental, all of which line up nicely with the deployment of GE-EPDs. Thus, it is possible (likely?) that this improved genetic improvement is due to the benefit of genomics.

In the dairy industry, genomics is equivalent to 25 production records, 25 conformation records, and 140 fertility records.
Genomics is saving the Canadian dairy industry $111 million dollars annually.
Genomics is saving the New Zealand Farming Coop $4.2 million annually. The genetic gain is increasing despite the cost saving.

A genomic test for Angus gives a breeder the same amount of information as 17 progeny with records for dry matter intake. A $47 test is much cheaper than doing a feeding trial on 17 progeny.

Three benefits:
1) Identify future problems
2) Identify current problems
3) Gives representative proxies for genetic merit of steer mates

There is also value in avoiding inbreeding. Inbreeding decreases performance, thus avoiding inbreeding helps us to avoid decreased performance. In dairy cattle, there is a $20 lost revenue per year for a 1% increase in inbreeding.

Selecting cattle for placement in a feedlot can be worth up to $38 per head. If we are just trying to use this information for different management, the value is less than $1 per head.

CLARIFIDE plus now can directly predict disease risk in Holstein cattle. As discussed previously, we see large reductions in feed efficiency due to health problems.

Amen's is pointing out that we see a $204 premium for heifers with genomics tests in the Show-Me-Plus program. This leads to a return on investment of 167% to 700%.

Friday, June 24, 2016

BIF 2016: Using genomic tools in commercial beef cattle: taking heifer selection to the next level

Tom Short

Can genetic information from a simple DNA sample allow us to reasonable accuracy of the females lifetime performance?

We know that our national cow herd inventory decreased to a very low level in 2014.

When we rebuilt the cow herd did we keep low quality heifers that should have never been cows?

What type of genomic prediction should we be using to select commercial heifers?

GeneMax Advantage was produced by a collaboration of Angus Genetics Inc, Certified Angus Beef, and Zoetis. It is applicable to beef females that are at least 75% Black Angus. These predictions are based on the Zoetis HD50K product for Angus. The correlations between the genomic predictions and the breeding value are all quite good, around 75%.

The individual traits are combined into three indexes. These are a Cow Advantage Score, Feeder Advantage Score, and Total Advantage Score. The correlation between Total Advantage and the Cow and Feeder indexes are about 70%, but the correlation between Cow Advantage and Feeder Advantage is about 50%. So, if in doubt about your breeding objective, use the Total Advantage Score.

The Cow Advantage is 13% Cow Cost, 66% number of calves, and 21% weight of calves. Carcass Advantage is a combination of feedlot and carcass traits.

Maximum genetic economic improvement is made by selecting on indexes.

Check out Bob Weaber's fact sheet on for more information about indexes.

By selecting on GeneMax Total Advantage, we see about 0.5 standard deviation improvement in Calving Ease Direct. We see about 0.9 SD improvement in weaning weight, 0.4 for marbling, calving ease maternal abour 0.6 SD. If we selected only on weaning weight, we would see unfavorable changes in mature weight, mature height, and decreased improvement for calving ease and other economically important traits.

In Short's model, value of the test is measured over a 10 year period based on the performance of the cow's progeny, grand progeny, and great grand progeny.

The heifers that you test and retain have to pay for the heifers that you test and cull. By 7 years, we see a net revenue of $300 per tested heifer. Break-even occurs between years 3 and 4. The value of the future generations is about 1.5X that of tested females. Keep in mind, investments in genetics is a long term investment!

146 heifers tested in SD herd.
By visual apprasial, the top 100 heifers averaged a 56 Total Advantage Score
By index rank, the top 100 heifers averaged a 65 Total Advantage Score.

A $39 test cost is approximately only $15 more than recommended health protocols to first calving for a first heifer.

Also consider other value considerations.
Value added marketing programs, the average of the heifers matches the average of the steers. Could use this information in marketing steers through TopDollar Angus or Reputation Feeder Cattle.

Also a great shout out to Missouri's Show-Me-Plus program!

This tool is also a unique value to commercial producers because historically they do not have access to genetics predictions for commercial heifers.

See for more information.

Thursday, June 23, 2016

BIF 2016: Can Beef Seedstock Producers Afford Genomics?

Breeding objectives indicate value of genomics for beef cattle

Dr. Mike MacNeil

Is genomic testing a good value to seedstock producers? The answer to this question requires several different lines of thought. To answer this we need a system based approach.

What makes up a genetic prediction?

  • Information from relatives
  • Molecular breeding value
  • Correlated phenotypes
  • Phenotype
No individual animal in a genetic prediction ever has an accuracy of prediction of zero. The information from the calf's relatives brings in substantial amount of information.

What are the advantageous of genomic prediction?
1) Increase accuracy of evaluation
2) More exciting is the opportunity to incorporate additional traits
  • costly or difficult to measure
  • measured late in life (after the time of selection decisions)
  • sex-limited
3) Avoid prolonged generation intervals. For many selection decisions in beef cattle, we make many selection decisions around a year of age.
4) Reputation. This is hard to quantify in dollars and cents!

What is improvement???
MacNeil's definition is making cattle that are more profitable in the next generation.
This can be boiled down to income minus expense.

MacNeil uses a computer model to estimate the effect of changing one trait by a unit of measure and seeing how that influences profit.
This model:

  • Is an abstraction of any actual beef production system.
  • Captures sources of income and expense
  • Has economic parameters which reflect future expectation
  • May be discount income and expense streams 
  • Has data-driven biological parameters 

For these models, MacNeil simulates many animals.

For feed efficiency simulations, MacNeil used 5 scenarios.
Scenario 1: Phenotypes only (accuracy = 2√h2)
Scenario 2: Phenotypes + low accuracy genomic prediction
Scenario 3: Phenotypes + higher accuracy genomic prediction
Scenario 4: (Phenotypes + siblings) + low accuracy genomic prediction
Scenario 5: (Phenotypes + siblings) + higher accuracy genomic prediction  

Going from phenotype to genomics has a fairy substantial jump. Going from a low accuracy genomic prediction to a high accuracy genomic prediction also has a big jump. When we have pedigree predictions with lots of phenotypes, there is no benefit from adding genomics.

"If you have a bull with 200 progeny records, don't waste your money on genomics," MacNeil said.

How many breeding objectives (economic selection indexes) should we have? MacNeil did an analysis. In South Africa, you receive discounts when the carcass weighs 500 pounds.
The correlation between the South African index and United States index was 0.68. The breeding objective in South Africa would work fairly well in the United States. The differences in breeding objectives across the United States are minuscule across environments in the United States. In other words, use indexes! They work!

Genomics only helps birth weight predictions by 9%. Genomics helps dry matter feed intake by 41%, because there are many fewer feed intake records.

For a maternal objective, fitness drives the bus. The cow needs to stay in the herd. This accounted for 50% of the value in the breeding objective.

For stayability in beef cattle, adding genomics had a 76% improvement in the accuracy of genetic prediction. This is because this trait is measured later in life and there are fewer phenotypic records.

In a terminal objective, we increase accuracy by 27%. 

If we generate 60 harvested progeny per sire, we earn $169 per genomic tests.
If we generate 15 replacement heifers on a bull, we earn $159 per genomic tests.

"You are on the order of 4 times the cost for return, based on the cost of the test." MacNeil said.

What are the take home messages:
Breeding objectives greatly facilitate multiple-trait selection
Genomic predictions for component traits add substaintal accuracy to prediction of breeding objectives
Genomic technology has greatest promise for traits that are infrequently recorded or recorded after the selection decision point
With reasonable transfer of economic benefits from commercial to seedstock sector, it indeed does appear that seedstock producers can afford genomics, provided they use rational breeding objectives.

"I started this exercise believing the answer was no." MacNeil said. "I believed it was a shell game about the perception of the value of the technology." 

MacNeil proved to himself that he was wrong.

Multi-trait breeding objectives keep you from going too far down the wrong path. They put the right amount of emphasis on each trait.
Tandem selection and independent culling levels are both less effective than breeding objectives through economic selection indexes.
 If we chase one trait, then run into a problem, select for a second trait, run into a new problem, so chase a third trait- this is tandem selection.

MacNeil stated, "I am troubled by the Angus $B index, as it is an incomplete objective" (i.e. it only takes part of the production system into account, not from conception to slaughter). But, using $B is MUCH better than using the individual component traits.

See for PowerPoint and Proceedings.

Decker's Take Home Thoughts
While many of the cattle that are on our farm or ranch are selected at a year of age, the ages of AI sires can vary greatly. Thus, AI sires may be a potential opportunity to decrease the generation interval. While commercial producers should likely use proven AI sires, this may not be the case for most seedstock producers. Using younger AI sires may be low hanging fruit for many seedstock herds.
Use genomics and use economic selection indexes so that your breeding decisions are rational.

Wednesday, June 22, 2016

BIF 2016: Growing profit by understanding cow maintenance efficiency and maintenance requirement in an animal and systems context

Dr. Mark Enns
Colorado State University

If we had the ability to improve maintenance feed consumption likely would improve profitiability of beef production.
To make genetic improvement we need genetic variability. Is there variability for maintenance energy? Hotovy et al 1991 measured intake and fasting heat production on twins to estimate heritability of maintenance energy. The heritability was 0.51.

But, putting a large number of cattle through metabolism chambers is not feasible.

What tools are available to change maintenance energy?

  • Mature weight and height
  • Body condition scores
  • Maintenance energy EPD

For two beef breeds, we see an unfavorable trend for mature size. If we go from a 1000 pound cow to a 1500 pound cow, we have increased the maintenance requirement by 35.5%.

But, maintenance energy is a function of both body weight and milk production. $EN index produced by the Angus Association is an economic index weighting both body weight and milk production.
Maintenance energy EPD (Mcal/Month), which accounts for mature weight and milk, is an EPD that allows selection of cows requiring less feed for maintenance.

Both $EN and ME EPD have both had unfavorable genetic trends (although ME EPD has plateaued the last few years).

Body condition score adjustments.
Let's assume an average mature weight of 1,350 pounds. If a cow has a body condition score of 5, there is no adjustment. If a cow has a body condition score of 7, the adjusted mature weight is 1144 pounds.

Red Angus Association: mature weight and body condition scores represent roughly 20% of the numbers of weaning weight records reported.
For American Angus Association, there are over 9.1 million weaning weight records. There are about 120,000 mature weight records.

The genetic relationship between birth weight and yearling weight is 0.55. Despite this strong relationship, we have successful created curve bender bulls with good calving ease and high growth.

The relationship between mature weight and yearling weight is 0.72. Just as we have broken the genetic antagonism between birth weight and yearling weight, we need to do the same thing for yearling weight and mature weight.

There has been encouraging progress on the research side. We have improvements in genomic predictions for feed intake. The correlation between feed intake on forage and grain is favorable (Shike), but we need to look at this from a genetic correlation perspective.

"There is evidence that selection can be successful for reducing maintenance energy requirements while still improving growth." Enns said.

Using an economic index, a cattle herd in Australia held mature size constant but increased slaughter weights.

Selection indexes work! Think what we can do with EPDs if we have the necessary data.

We need more data for mature weight and body condition scores.

See for more information about this talk.

Tuesday, June 21, 2016

BIF 2016: The 2016 and 2036 cow herd, what we do and what we need to do better

Dr. Dave Lalman
Oklahoma State University

Lalman points out that we have made tremendous change for post weaning growth. Right now finished cattle weights are increasing at a rate of 9.4 pounds per year. Carcass weights are increasing by 5.7 pounds per year.

Marbling has also increased over time.

Compared with 1995, we have seen fewer yield grade 1s and 2s, but we have seen more yield grade 4s and 5s. The number of yield grade 3s has increased from 34.2% to 46.7%.

The cow-calf sector and the entire industry have responded for the need for increased post-weaning performance and carcass quality.

The increase in calf prices has increased by $5.25 per hundred weight (cwt) per year. The increase in costs has increase by $5 per year. Profitability appears to not have changed that much.

Lalman discussed analyses by Pendell and coworkers published in 2015, in which they analyzed Kansas Farm Management Association data. The data had information from 79 operations with data from 2010 through 2014. In this data, the high profit 1/3 averaged $415 more net return per cow compared to low profit 1/3.

When comparing high profitability to low profitability, 32.2% of the difference was due to gross income per cow. However, 67.8% of the difference between high profit and low profit operations was due to reduced expenses.

Increasing weaning weight often leads to break even (due to management?).

Weaning rates have not changed over time. In the northern US, we see high pregnancy rates above 95%. In the southern US, we see much lower pregnancy rates around 90%. The national average for weaning rates is around 85%.

In most areas, we see no trend for weaning weight. In the Kansas data, we see a 1 pound increase per year in weaning weight. For purebred Angus, we see about 2 pound increase per year.

Hay production (use?) per cow is increasing about 66 pounds per year.

1.1 lb/day increase in dry matter intake increases milk yield by 1 lb/day.  But, this requires 27 additional pounds of feed per 1 pound of calf gain.

Please see for more information about this presentation.

Decker's Take Home Message
First of all, I think we must be clear that this research does not mean EPDs don't work. It doesn't even insinuate that EPDs don't work. What it may mean is that the environment may be limiting the expression of an animal's full genetic potential. If that is true, emphasis on selecting for increased weaning weight should be decreased, and selection pressure redirected to different traits.

Based on surveys of cattle producers, I am highly suspicious that the majority of cattle producers are using EPDs at all, and if they are using them, if they are using them appropriately. A BEEF Magazine survey indicated that the top criteria to select bulls is actual birth weight- this is not using EPDs or using them correctly. Those producers who embrace technology, whether new or old tech, will be the heroes who lead the beef industry forward.

Our experience at our Thompson Research Center has been much different than the data reported in the SPA, CHAPS, or Minnesota data. The Thompson Research Center is operated as a highly profitable commercial herd. Calves are not creep feed or otherwise pampered. In our data, from 1996 to 2013, weaning weight increased by 1.5 pounds per year. While this is not as rapid as the 2.6 or 2.1 pounds per year seen in the Angus data, it is much larger than zero. In our experience, if producers use AI sires and apply a consistent breeding objective then phenotypic improvement will be seen.

Lastly, we agree that the environment may be limiting the performance of cattle. That is why we have designed a research project in which the ultimate deliverable will be region specific EPDs and indexes that are tailored to specific environments.

Monday, June 20, 2016

BIF 2016: Extension demonstration project outcomes; Industry adoption and translation of project deliverables

Dr. Matt Spangler
University of Nebraska-Lincoln

A seedstock producer's goal should be faster genetic progress (breeders equation). But, we need to balance this by the cost of the genetic progress.

Although some of these traits are interesting to us as biologist (what Spangler termed "biological intrigue"), what really matters at the end of the day is improving cattle.

What is the difference between an indicator trait and economically relevant traits? Economically relevant traits are traits that directly impact profit by either influencing revenues or expenses. Indicator traits are traits that are recorded because they allow us to more reliably predict economically relevant traits. An example of this would be calving ease direct and birth weight. No one gets paid for or has costs associated with birth weights. But, birth weight is a great indicator of calving ease, because calving ease can have economic impacts through labor, dead calves, cows that don't rebreed, etc.

Which is the economically relevant trait? Residual feed intake or dry matter intake? Residual feed intake is an indicator to make selection decisions. When you feed cattle, you are charged for the actual feed intake, NOT the residual feed intake. Thus, dry matter intake is the economically relevant trait. See Improving Feed Efficiency: Feed Efficiency Project Releases Decision Support Tool for more information.

What is a selection index? When we use an index we select on aggregate merit. The index is a combination of the individual economically relevant traits into a single value, most frequently expressed as a dollar figure.

“There is no easily accessible, objective way for breeders, particularly breeders in the beef and sheep industries where ownership is diverse and production environments vary a great deal, to use these predictions [EPDs] intelligently.” 
- Bourdon
What does this quote mean? Does it means EPDs don't work? Does it mean that beef producers are stupid? No, it means that it is nearly impossible for an individual beef producer to identify how to use the entire set of published EPDs. What EPDs should be emphasized? What are appropriate bounds for EPDs?
Luckily there is a very easy solution, economic selection indexes.

What drives profitability?
Hot carcass weight is the main driver of profitability, accounting for 59.5% of the impact on profit. Dry matter intake is also important at 11%.

There are 24 beef operations from 7 states that are part of the weight trait project. This project has been designed as a demonstration project of genomic selection. Through this project came some of the first observations that genomic predictions (at least in their current form) don't work well across multiple breeds. In other words, genomic predictions designed in Angus don't work well in Hereford or even Red Angus. The weight trait project was expanded at the start of the USDA Beef Feed Efficiency project. As part of the demonstration project, they got semen from bulls used by producers in the Weight Trait Project. They produced progeny out of these bulls and put the progeny through a feed intake trial. This data has then been turned over to the breed associations to use in the development of feed intake genetic predictions.

Please visit and for more information.