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Dr. Jamie Courter is your Mizzou Beef Genetics Extension Specialist

By Jared E. Decker Many of you have probably noticed that things have been a lot less active on the A Steak in Genomics™   blog, but you probably haven't known why. In January 2021, I was named the Wurdack Chair in Animal Genomics at Mizzou, and I now focus on research, with a little bit of teaching. I no longer have an extension appointment. But, with exciting news, the blog is about to become a lot more active! Jamie Courter began as the new MU Extension state beef genetics specialist in the Division of Animal Sciences on September 1, 2023. I have known Jamie for several years, meeting her at BIF when she was a Masters student. I have been impressed by Jamie in my interactions with her since that time.  Dr. Courter and I have been working closely together the last 6 weeks, and I am excited to work together to serve the beef industry for years to come! Jamie holds a bachelor’s degree in animal science from North Carolina State University and earned a master's degree in animal

Beefmaster Breeders United Convention: EPDs and Selection Indexes

Matt Spangler
University of Nebraska-Lincoln

In the past, the only way we made improvement was through visual appraisal.

Photo from Harlan Ritchie's Beef Review. Difference between 1835 and 1937 champion.
As the picture above shows, we can make a change, but how many of us want to wait 100 years?

Improvement can be accomplished through management and genetics.

In the past we (animal breeding scientist) have probably done a disservice to the industry by producing lots of EPDs, then dumping those in beef producers lap and then expect you all to make meaningful decisions with them. In some situations, this may be as valuable as a free cat.

There are many factors that can influence an animals record, for example a weaning weight. Weaning weight may be affected by age of the calf, age of the dam, how much it was feed, and other environmental factors.

So, we need to compare animals to their contemporaries, Contemporaries are animals of the same sex, raised at the same ranch with the same management. We can calculate a ratio of how different from the contemporary group each animal is. These ratios are helpful for making within herd selection, but it cannot be used to make selection decisions across herds. EPDs allow us to make selection decisions across herds.

What we need to be selecting on is the genetics, because this is inherited from generation and generation and allows us to make genetic progress.

Breeders often misunderstand EPD accuracy. Accuracy is not a measurement of the consistency of the calf crop. Accuracy is a measure of how certain we are of the EPD estimate. Accuracy is really a measure of the possible change we might see in that EPD. The EPD may be 40, but the 68% confidence interval might be between 35 and 45 pounds.

Consider two bulls with a weaning weight EPD of 40. The first bull has an EPD ACC of 0.3, which means a possible change 8.1 pounds. The second bull has an EPD ACC = 0.8, which means a possible change of about 2 pounds.

Another very important tool is percentile rank. If a bull is in the 25th percentile, he is better than 75% of the other bulls in the breed and worse than 24% of the bulls in the breed.

The across-breed EPD adjustment factors are a tool to compare EPDs across different breeds. By adding or subtracting by the adjustment factors.

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
This is not a question of the intelligence of beef producers. This is commentary on the difficulty of using EPDs. The solution to this is to use economic selection indexes. Profit is of course revenue minus cost. It is quite easy for us to create EPDs for revenue traits. It is harder to create EPDs for the cost side.

Seedstock producers need to discuss the customers needs. Spangler shared the experience of seedstock producers calling him up to sell him bulls to use in the University of Nebraska's cattle herd. They start telling him about the bulls in the sale he should be looking at. These breeders have not asked him about his needs. Seedstock producers need to do a better job of asking their customers about their production. What is the customer's breeding objective? When are they marketing their calves? What is their production environment like?

We need to focus on economically relevant traits, and not indicator traits. Indicator traits are important to measure, record, and report because they help us predict economically relevant traits.
Lets consider pairs of traits. Which one is the economically relevant trait?
BWT vs CE: Birth weight is an indicator of calving ease. Calving ease can cause increased labor costs and leads to problems for cattle rebreeding.
REA vs YG: Ribeye area is a component of Yield Grade. Yield grade is the trait that influences the sale price, thus is the economically relevant trait.
YWT vs CWT: This comparison depends on when cattle are sold. But, for the overall industry, Carcass Weight is the economically relevant trait.
MWT vs DMI: Mature weight is an indicator of the dry matter intake of the cow. The dry matter intake is the economically relevant trait.
RFI vs FI: No one gets paid for residuals. You have to pay the entire feed bill. Feed intake, not residual feed intake, is the economically relevant trait.

There are different traits that are important depending on the production sector of the industry. If you are selecting for cattle

There are three methods for selecting for multiple traits.
First is tandem selection. In this strategy we select for birth weight till it reaches an appropriate level. Then we select for weaning weight. The problem with this strategy is that when we select for increase weaning weight we loose ground on the progress we made for birth weight (birth weight goes up), because the two traits are correlated. This is a very inefficient selection strategy!

Independent culling levels. In this method, you set minimum levels for birth weight, weaning weight, marbling, etc. This method is also inefficient because it fails to recognize bulls that are excellent for several traits but barely misses the cutoff for a trait. This also does not weight traits according to their economic importance.

Selection indices were first developed in 1943. The first selection index in the beef industry was published in 2004. This was a 60 year time lapse.
"This would be similar to corn producers hitching up the mules to plant the corn in the spring," Spangler said. This is a proven technology and needs to be adopted by the beef industry.

When designing a selection index we are trying to make improvement for traits in our breeding objective. The breeding objective may contain things like calf survival, weaning weight, fertility, etc. The more closely the traits for which there are EPDs match the traits in the breeding objective, the better the selection index works. When the breeding objective trait is not predicted, we need to use an indicator trait.

Why do we use the past five years of economic data and not the current prices and spreads? We are selecting cattle to use in the future, not today. A five year average is going to give us a better prediction of future prices than current prices will.

For the Beefmaster Terminal Economic Index, carcass weight is the most impactful trait, followed by feed intake and third by marbling.

For Beefmaster Maternal Economic Index, smaller mature weight is the most important trait, while increased weaning weight and increased maternal effect on growth (milk) are the second and third most importnat traits. This index selects bulls that will producer daughters that are smaller cows that wean heavier calves.

As Spangler and his group developed these indexes, they looked at how sensitive their indexes are to the assumed genetic correlations and the assumed economic values. Whether or not the calves were all calf feeds or yearling slaughter, had no effect on the index.
They found that the indexes were very robust (insensitive) to changes to genetic correlations or economic assumptions.

Lets look at two bulls, one with an index of 100 and the second with an index of 76. Lets assume that over 4 years, these two bulls are exposed to 120 cows.
120 exposure X ($100 - $76) = $2880 in profit difference between the two bulls.

Improvement in current indices can be made by increasing the number of economically relevant traits that have EPD predictions.

  • Input traits
  • Fertility

Enterprise level profitability should move closer to industry level profitability. Cow-calf producers don't get paid for tenderness, but tenderness is a big driver of consumer demand.

Seedstock producers should focus on the indexes that influence their customer's profitability. If a seedstock producer's customers retain ownership, then the seedstock producer should focus on the terminal index. If the majority of the customers retain females and sell at weaning, then the seedstock producer should focus on the maternal index.

Progeny receive half of their genetic material from each parent.
Breeding Value = 1/2 Sire Breeding Value + 1/2 Dam Breeding Value + Theta.
What is theta? Theta is the Mendelian sampling term. This accounts for the random sample of genes a calf inherited from its sire and dam. Even really good bulls can produce bad calves due to this random shuffle of genes (see fact sheet).

Seedstock producers are not truly cattle producers, they are genetic providers. Genetic improvement, driven by accuracy, selection intensity, and generation interval, should be the focus of seedstock producers. Seedstock producers need to realize that using younger sires can decrease their generation interval and increase their genetic progress.

Keep in mind, that a genomic test increases accuracy. The accuracy will always increase, but the EPD estimate can go up or down. But, the incrase in accuracy can allow us to use younger bulls with more confidence.

GE-EPDs allow commercial producers more confidence that they are picking the right bull.

In the past, we have seen producers only testing what they thought were their top bulls. This is not optimum.
At UNL, they have space to put 90 bulls on feed. At weaning they genomically test every bull calf. With the genomic test, they now have EPDs on every trait. Before they were picking bulls somewhat blind. Now they have data and information behind which bulls go on feed.

"Genomics helps breeds the most that already have very sound databases," Spangler said.

One of the things that breed associations do poorly is collectively bargain for the price of technology. In Ireland they negotiated to genotyped all of the cattle in the country. Because they were able to buy one million SNP chips, the cost per tested animal was less than $20.


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