Friday, March 23, 2018

Cattle Raisers Convention 2018: Breed Characteristics, An Overview

Robert Wells, Noble Research Institute

What breeds should you consider?
Complementarity effects

There are two species of cattle:
Bos taurus
British breeds (Angus, Hereford)
Continental breeds (Charolais, Simmental, Limousin, Gelbvieh, etc.)

Bos indicus (Zebu, humped cattle)

Angus (British)
Reputation is carcass and maternal. Also has a reputation for growth.
"They wanted to be everything to everybody," he said. The problem with this is the increased mature size in these growthier Angus cattle.

Red Angus
Reputation for carcass and maternal. Before the 1950s, all Angus were Angus, regardless of coat color. The Red Angus breed has not chased growth as much as black Angus.

Hereford (British)
Reputation for maternal, easy fleshing, and longevity. Hereford don't typically have a lot of maintenance requirements.

Shorthorn (British)
Reputation as maternal and carcass. Shorthorn was previously a dual purpose breed of meat and milk. This is why Shorthorns have been used in a lot of composites such as Santa Gertrudis.

Simmental (Continental)
Reputation for maternal and growth.

Maternal and growth

Reputation for growth and lean tissue. Great for yield grade.

Reputation for growth, but they also do a decent job on quality grade.

American Brahman (Bos indicus, composite of several breeds from India)
Maternal, lean, hardiness, insect, disease and heat tolerance.

Reputation for hardiness and lean beef. Horns are a by-product that can marketed to hang in steak houses.

Reputation for hardiness and roping stock. Once referred to as a goat in a beef cattle hide. Often used for calving ease, but their are probably better options to get calving ease without the discounts for Corriente cattle.


Larger framed than Waygu. Known for marbling and fertility.

There are more breeds out there can you can imagine.

Santa Gertrudis
Mix of Brahman and Shorthorn. Has to fit breed type to be registered.

Maternal heterosis and growth. Longevity, fertility and efficiency. Can be any color.

Carcass, Growth, Maternal and Heat Tolerance.

Gelvieh and Angus hybrid

Limousin and Angus hybrid

Simmental and Brahman hybrid

Black Baldy
Hereford and Angus hybrid. Great longevity and maternal.

F1 Tiger Stripe
Hereford and Brahman hybrid.

Super Baldy
F1 Tiger Stripe with Angus influence.

Commercial Angus

Brangus and Angus cross. Less Brahman influence than Brangus.

Crossbreeding leads to increased hybrid vigor, also known as heterosis.
Crossbreeding can lead to a lack of uniformity. We have now gone towards a straight breeding program. Straightbreeding has lead to increase consumer acceptance and carcass quality, but we have also lost some fertility and stress tolerance.

Maximum heterosis is achieved by an F1 x F1 cross. This has grandparent from 4 unrelated breeds. However, this may decease uniformity, especially in multiple bull herds.

Maternal hybrid vigor increases calving rate (6%), weaning rate (8%), weaning weight (6%), and a negligible 2% increase in birth weight.
Cow lifetime productivity is increased by 25% due to heterosis.

Keep in mind that some crossbred cows are larger than their straightbreed counterparts. May need to adjust stocking rates appropriately.

Original Scenario:
100 cows, Cow Breed A x Bull breed A
525 lb weaned calf
Average weaniing rate 82%
43,050 lbs marketed

Switch to:
Cow Breed A x Bull Breed B
Individual heterosis (+5%)
~551 lb weaning weight F1 calf
45,203 lbs marketed
+2,152 lbs/year = +$5,725.65/year

Switch to:
F1 cow x Terminal bull breed C
+WW total heterosis + 25%
656 lb calf (+131 lbs)
59,040 lbs marketed
+15,990 lbs = +$40,295

"What is that ideal cow? I don't care what color she is," Wells said. The cow needs to fit our environment and our resources.
Early puberty
Never misses a breeding season (1 calf/365 days)
Calves unassisted
Doesn't require a lot of supplemental feed
Easy fleshing
Converts forage to lbs of raised calf

Must be able to manage for the benefits.
Heterosis will not make up for poor animal husbandry/management.
Heterosis will not make up for poor bull selection.

*Note, this post was live blogged and may contain mistakes.

Cattle Raisers Convention 2018: Bull Selection Panel

Tommy Perkins, International Brangus Breeders Association
Kelley Sullivan, Santa Rosa Ranch
Donnell Brown, RA Brown Ranch

What DNA tests do you require when you buy a bull? Parentage? Genetic Defects? Polled? Coat Color?
What trait is most important in bull selection?
Does genomic testing provide value?

Donnell Brown currently markets 4 different breeds (Angus, Red Angus, SimAngus and a 4-breed composite called Hotlander). Brown has been involved with 17 different breeds. They DNA parentage test every animal born on their place. Five to ten percent of animals have the wrong parentage assigned. Cows swap calves. The wrong straw gets pulled out of the tank. A bull comes over from two pastures over and then goes home before we ever knew he was out. Would we prefer to use a bull with one calf crop or a bull with no calves? Most producers prefer the bull with more data. Genomic-enhanced EPDs provide the same amount of information as the first calf crop out of a bull. Donnell said for seedstock producers it is more important to DNA test females, because that gives us more information on her genetic merit than her lifetime worth of progeny data.

"Just because a bull has EPDs doesn't mean he is good." Brown said. The EPDs simply reflect how the bull compares to other bulls.

Brown has never printed actual performance data in a bull catalog. No actual birth weight, no actual or adjusted weaning weight, etc. The EPDs provide much more information.

Truck manufactures report the estimated highway and city miles per gallon. These numbers aren't always exact, but they provide a great estimate to compare different trucks. EPDs are the same for comparing bulls.

Donnell Brown has been using selection indexes for 25 years.

Kelley Sullivan states that Santa Rosa Ranch is now the largest Brangus and Ultrablack breeder in the United States. Ultrablack cattle has allowed Brangus breeders to expand bull selling into new markets. The higher percentage of Angus allows them to sell into Nebraska, Missouri, etc. This
"If you are not successful, we are not successful" Sullivan says. We need to meet our customers need and produce beef for our consumers.

Before you buy a bull, you need to identify herd goals. What are you looking to do?
What are your selection priorities? You need to use the selection tools (indexes, EPDs, genomics). "Unless we know what we have, we can't sell it to you," Sullivan says.
If a bull can't move and a bull can't walk, you can't use him. He won't be able to do what he is supposed to do. Bulls need to be structural sound. You need to look at the bull, or have someone trusted look at him.

You need to find a reputable source of genetics (breeding stock). Santa Rosa Ranch stands behind every bull they sell. Do your homework. Is the seedstock producer doing what they say they are doing.

You need to make a sound investment. They price their bulls at 5 times the current prices of the calf market. Some bulls are priced higher if they have potential to go into a seedstock herd. Don't look for the cheapest bull out there.

Concentrate on factors that have the greatest effect on profitability. Performance is a function of both genetics and management. Don't single trait select.

You're investing in their program and, if they are reputable, they are investing in your program as well.

You must require a Breeding Soundness Exam (BSE) be performed before you take ownership of the bull.

What development ration has been fed? Is he fat? If he is fat, he is going to lose a lot of that condition when he is out breeding cows.

Disposition and docility is sometimes over looked. You don't want the problems associated with bad dispositions.

"One of the goals of our program is moderating mature frame size," Sullivan said. "We need her to breed back and have a calf every year."

Donnell prints only the most valuable information in the bull sale catalog. Brown's number 1 trait is $Profit. Everything that effects your profitability goes into that index. Percentile ranks helps producers better understand EPDs. If you can count from 1 to 100, you can understand percentile ranks. Is this bull average? In other words, 50th percentile. Is the bull in the top 5%? Is the bull in the 95th percentile?

Maternal is so much more than milk. Is the cow going to have a calf year after year?

"I measure as many things as I can measure," Brown said.

"I like selling 18 month old bulls. I like having a man to do a man's job, rather than asking a boy (yearling bull) to do the job."

"A bull you bought last year will effect your herd till 2034. A bull you bought is an investment in your herd," Brown said. If you buy an old junker, clunker pick up, you get the performance of a junky pickup. The same thing happens with regards to the bull you buy.

*Note, this post was live blogged and may contain errors.

Thursday, March 15, 2018

Angus Genetics Inc Releases Foot Score Research EPDs

In January, Angus Genetics, Inc. (AGI) announced the release of research Claw Set and Foot Angle EPDs. The development of a research EPD is the second step towards a production EPD.

This followed research presented in the summer of 2017 which found heritabilities of 0.34 for foot angle and 0.21 for claw set. Estimating heritability (portion of the trait influenced by genetics) is the first step towards a production EPD. This research also found a genetic correlation of 0.22 between the two traits, indicating that both traits need to be reported and analyzed.

Stephen Miller, AGI Director of Genetic Research stated, "“Angus breeders have completed a tremendous amount of data reporting in such a short period of time; this is truly a testament to their commitment toward genetic progress. We are absolutely thrilled to begin the process of rolling this breakthrough out to the membership.”

Kelli Retallick, AGI Director of Genetic Services cautioned, “Though we are getting closer to a production EPD, we encourage members to continue sending in data. Consistency of scoring within a producer’s herd is key, and luckily, we have a variety of resources here at the Association to help.”

Between herd variation, just like any other trait, is handled through the use of contemporary group effects in the EPD analysis. Thus, the main focus is consistency within a herd year after year. The American Angus Association also has partnerships with university judging teams to aid in foot scoring.

Figure 1. Genetic trend for Claw Set EPD in highly accurate Angus sires. Blue line is a linear trend. Red line is a smoothing curve (Loess regression).
 As seen in Figure 1, claw set has basically remained unchanged in Angus cattle since 1985. This may be due to the lower heritability of claw set or less phenotypic selection on claw set. An EPD should help improve the rate of genetic progress for claw set.

Figure 2. Genetic trend for Foot Angle EPD in high accuracy Angus sires. Connealy Counselor, an outlier with a Foot Angle EPD of 1.20 was excluded from this graph. Blue line is a linear trend. Red line is a smoothing curve (Loess regression).
If we compare the 30 years from 1985 to 2015, Foot Angle has also not changed in Angus cattle. However, we see foot angle getting worse from 2003 to 2008, at a rate of 0.013 units per year. However, we see improvement in foot angle from 2009 to 2015 at a rate of -0.016 units per year. This may be due to the ease of phenotypic selection for foot angle or the increased response to selection due to the higher heritability for foot angle.

Recording, Reporting, and Analysis of Subjective Scores

The American Hereford Association uses subjective scores to report Udder and Teat EPDs. They began publishing production EPDs for these traits in 2015. The genetic trend for both of these traits began to improve more rapidly in 2010 likely due to systematic recording and reporting of udder and teat scores in 2009 (Figure 3). These results show how important data collection and reporting are for genetic improvement. Further, this illustrates that subjective scores, when properly analyzed and used, can effectively improve economically important traits.
Figure 3. Genetic trends for Udder (red line) and Teat (blue line) in the American Hereford Association.

Work by Other Breed Associations

The press release pointed out that these were the first foot score EPDs in the U.S. beef industry. Angus made this distinction because the dairy industry has been reporting structure genetic predictions for quite some time. The Australian Angus Association has structural soundness genetic predictions for Front Feet Angle, Front Feet Claw Set, Rear Feet Angle, Rear Leg Hind View and Rear Leg Side View.

Breed associations in the U.S. are also working towards structure EPDs.

Tommy Perkins, International Brangus Breeders Association, explained at the 2017 Texas Beef Cattle Short Course several subjective scoring systems Brangus breeders are using to record and report data. These include a 1 to 5 scale for foot angle and claw set.

Bob Weaber, Kansas State University, provided an update on structural soundness research being conducted at KSU in collaboration with the Red Angus Association of America.


Commercial cattle farmers and ranchers can utilize crossbreeding to complement the strengths and weaknesses of different breeds. Seedstock producers and commercial operations that straightbreed need to look for avenues of genetic improvement. This frequently requires the recording and reporting of data to produce EPDs that increase genetic improvement. At the very least, this requires systematic recording of these traits to increase attention to their impacts and expression.

Take Home Messages

Beef producers, especially seedstock producers, should learn at least two lessons from these developments.

  1. Record and Report data that affect you customers' success
  2. Subjective scores, when analyzed in a genetic evaluation framework, are valuable sources of information

Tuesday, March 13, 2018

Breed composition: it’s like chocolates you can’t tell what’s inside just by looking at them

Written by Tamar Crum, Jared E. Decker, Robert D. Schnabel, and Jeremy F. Taylor

“My mom always said life was like a box of chocolates.  You never know what you’re gonna get.” – Forrest Gump

You may be wondering how in the world does a box of chocolates relate to breed composition of livestock? Or, if you are anything like me, it’s where did I hide that Halloween chocolate, I need some! I think that there are two analogies between a box of chocolates and the breed composition of livestock. 

First, we can pick out the white chocolates and may even be able to separate the milk chocolates from the dark chocolates.  This is similar to our ability to visually evaluate breed characteristics and sort livestock into different breed or subspecies (Bos taurus or Bos indicus influenced) based on breed characteristics.  However, such visual evaluation of breed composition is not terribly accurate.  For example, biting into a piece of dark chocolate and finding a nut when you were expecting caramel.  Crossbreeding is an important tool in the cattle industry, as it enables us to capitalize on breed complementarity and hybrid vigor.  However, crossbreeding complicates our ability to accurately sort animals into breeds based on breed standard traits.  Imagine a box of chocolates that contains a few chocolates that appear to be covered in both white and milk chocolate.  Do we sort these chocolates into the milk chocolate group or the white chocolate group?  Or, perhaps a new ‘hybrid’ group, since neither of these groups really reflects the correct composition. 

Second, a box of chocolates includes a diverse assortment of “fillings”.  The “fillings” cannot typically be determined from just visual evaluation.  The different “fillings” provide another challenge to our being able to sort the chocolates into groups.  Without reading the decoder in the box (isn’t that cheating?) or just taking a bite out of each of them (no judgment on my part if that is your routine!), we cannot accurately sort the chocolates.  The “filling” of the chocolates is directly analogous to the DNA of an animal.  If we keep breeding records on our animals, we can sort the animals based on their pedigree and breed registrations.  For example, if we have offspring from a registered Angus sire and a purebred Simmental dam, we can assume that the progeny will be 50% Angus and 50% Simmental.  But, what about if we take this progeny and breed it to a registered Angus? Will the resulting grandprogeny be 75% Angus and 25% Simmental? Due to the random assortment of DNA (chromosomes) into the sex cells, these proportions can vary. Not only can they differ from the 75/25 mark in an individual, but full-sibs produced from exactly the same mating can also be comprised of varying grandparental breed proportions.  Who knew that sorting a “box of chocolates” could be so complicated?

Understanding the breed composition of animals is a challenge, especially for genetic researchers.  Not all members of a breed are identical. Each breed was formed by an initial sampling of animals that were considered to be “characteristic” of a desired breed type.  Later selection and breed development produced breeds that differed for carcass qualities, maternal ability, or even adaptability. These characteristics make the breeds valuable to the industry.  In addition, each breed may have different mechanisms underlying variation in traits, such as feed efficiency or marbling.  Differences in traits between breeds reward both the producer and the consumer when crossbreeding is used. 

However, in certain genetic analyses we often need to understand the breed composition of animals to appropriately use the data. For example, when markers are used to generate estimates of genetic merit for traits such as feed efficiency, the resulting prediction equations will only be useful within the breeds that are represented in the training data set.  So understanding the breed composition of the animals will guide us in understanding how broadly useful the resulting prediction equations will be. Because of the inaccuracies of breed identification of crossbred animals using visual measures, a method to determine breed composition based on sampling the “filling” will provide a more accurate measure.  We have developed an analytical method to estimate the ancestry/breed composition of crossbred animals based on their DNA data.

You may have heard of or even participated in the 23andMe,, and other genetic tests that are used to predict your ancestry.  You know, you used to dance in your lederhosen until you found out that you were Scottish and so now you wear a kilt! Think of our method as the 23andMe analysis for cows.

So how does the analysis work? In ancestry analysis, the observed data are DNA genotypes for animals which may be full-blood, purebred, or crossbred and the inferred factors are the ancestral or “reference” breeds.  To conduct the analysis, the first and most important step is to determine a set of reference population animals that genetically define the frequencies of genotypes at each tested variant among the members of each respective breed.  As you might expect, this makes it extremely important that the breed definition for the “reference” samples is correct.  In addition to being the most important step, determining the subset of samples that represents the diversity within each of the “reference” breeds is technically difficult. 

The reason for this is that the concept of breed and breed membership is man-made, and has not persisted in nature. The creation of species is a complex and lengthy process taking tens or even hundreds of thousands of years.  On the other hand, the development of livestock breeds is a very recent concept, beginning with domestication of cattle about 10,000 years ago and leading to the formation of herd books approximately 200 years ago.  Compared to the thousands of years cattle have roamed the earth happily mating at random, we should probably only expect that regions of the genome with large  effects on traits that define breed characteristics have been subject to human selection and resulted in breed differences. However, the phenomenon of drift in DNA variant frequencies over the last 200 years has caused enough differences in frequencies among breeds that we do in fact find signal for breed identification. Our software’s output can be represented by a figure similar to Figure 1.

Figure 1: Genetic profiles for animals defined as representing 18 different breeds. Breed identification is shown below each colored block and each animal is represented as a vertical line within the figure.
 The software does not know which animals were chosen to represent each breed but simply clusters them together based upon genetic similarity. We then arrange the output according to the animals that were selected to represent each breed to produce Figure 1. Each block contains a dominant color that is representative of each breed.  There also appears to be small levels of mixture represented by the colors in the top and bottom of each block for almost all the breeds. One interpretation of this is that there is a shortage of statistical power to completely predict breed ancestry.  However, this does not seem to vary much as we increase the number of markers used in the analysis. So, this result could suggest that these samples do not represent purebred animals. But, this is not the case in the recent sense, as the animals sampled to represent each of the breeds were traced by pedigree to ensure that they were purebred.  What appears to be more likely is that this represents breeding events that took place before the foundation animals for each breed were selected. Two simple examples of these events are the polled and coat color variants found in Hereford cattle.  The polled mutation in Herefords is identical to the mutation found in Angus cattle (and other Celtic breeds) and the Hereford coat color variant is only found in white-faced European cattle (e.g., Simmental). This indicates that these variants, and therefore breeds, have common, albeit, common distant ancestries.

The current software version functions to provide estimates of the genome-wide ancestry of individuals.
Future versions may allow ancestry estimates for specific regions of each chromosome.  It provides a method for determining the breed composition of individuals with no pedigree information, and that were perhaps generated in a commercial environment employing various crossbreeding systems.  Figure 2 illustrates how the genomes of crossbred animals can be separated into components originating from their ancestral breeds, with no pedigree information included in the analysis. By establishing the ancestry of these individuals, we can determine cohorts for use in association studies or other downstream analyses such as the genomic prediction of EPDs.

Figure 2: Genetic profiles for 238 crossbred animals. Breed identification is shown by color and each animal is a vertical line within the figure.  The key indicates which color corresponds to which ancestral breed. The animals shown are mostly Angus and Simmental.

The goal of this research is to develop an analytical pipeline that will enable the detection of the breed composition of crossbred animals based on animals defined to be representative of specific breeds. We will then use this information to enhance the analysis of genetic and trait data. Opportunities for the use of this information are only limited by our imagination.  It was once stated on 23andMe’s website that, “Your DNA can tell you a lot about your family, your health, your relatives, your ancestry, your traits, and you.”  ( We hope that this software can help us do just that for cows.

Tamar Crum is a PhD student at the University of Missouri.  This research is part of a study entitled “Inference of Admixture for Cattle with Complex Ancestry”.  This article was written as part of a Walton-Berry Award given to the Decker Genomics Group at the University of Missouri, which paid for four graduate students to attend the Beef Improvement Federation Conference held in Athens, GA in June 2017.

Reprinted with permission from the March 2018 issue of SimTalk.

Monday, March 12, 2018

Mineral Supplementation for Cattle

Eric Bailey
University of Missouri Extension State Beef Nutrition Specialist
Presentation at Southwest Missouri Spring Forage Conference 

Here is the contrarian view. Compared to other drivers of profit,  mineral has an extremely small impact on profitability. Here is a quote to illustrate this view.

"Don't measure with a micrometer and cut with an ax!" -Dr. Tim Steffens.

We don't give a cow a half a teaspoon of mineral, watch her eat it, and go about our day. No, we put out mineral and cows will eat as little or as much as they want.

Bailey's philosophy: Mineral nutrition is an insurance policy. Minerals are not a cure or a key to improving production.

What is the issue? Marketing vs. Science. If we are feeding cows 3 year old hay that is mainly buck brush and sumac, we have much bigger nutritional issues than mineral. In many situations we have energy and protein deficiencies before we have mineral deficiencies. Minerals are high profit margin products for feed companies. They are frequently bombarding cattle farmers and ranchers with testimonials of how well minerals work.

Bailey surveyed articles by extension specialists. He and other specialists recommend using the same mineral program during a drought. 

Injectable trace minerals cover the 4 trace minerals most likely to be deficient in cattle (copper, zinc, selenium, and manganese). The pros of injectable trace minerals is that we ensure nutritional requirements are meet.

Mineral intake does not need to be consistent across time. Minerals are stored in blood, bones, etc., so cattle do not need constant supplementation. If 50 cows eat an entire palette of mineral in a month, simply wait a month before supplying them additional mineral.

Free choice mineral consumption is projected to be 2-8 ounces per animal per day. This means each cow needs one to two 50 lbs bags per year. If they eat more than that, pull out the mineral for a while to maintain rate.

Price per bag ranges from 6.29 to 34.99. Let's compare mineral supplementation costs and annual cow costs. In southern Missiouri, the average producer spends $46.68 per cow per year for minerals. The average producer spends $848 per cow per year. There are bigger problems with cow costs than mineral! Pasture and hay are the biggest cost per cow each year.  

Trace minerals have important roles in immunity but the effect of supplementing above established requirements is debated. 
Keeping salt out year round is a good idea.
Most nutrition issues are related to protein and energy intake.

Cafeteria style mineral supplementation (cow gets to choose which mineral to eat) was disproved 40 years ago. Cows don't crave specific minerals.

We shouldn't compare prices between tubs. We should be looking at what is the cost of meeting nutritional requirements. Often, nutritional requirements are meet with the least expensive mineral.