Canadian Simmental Association - Breed Improvement Archives

The following represent archived articles that were previously printed in the Simmental Country magazine.

The Basics of Multi-Breed Evaluation
The Need for Feed
Percentile Rank (April/May 2005)
Selection Index (March 2005)
Complementary Data (January 2005)
Carcass Data - (The Basics 2004)
The Performance Picture (August 2004)

The Basics of Multi-Breed Evaluation

The Canadian and American Simmental Associations conduct a North American Multi-Breed genetic evaluation on a semi-annual basis. In other words, every 6 months the two countries pool their data together, access the latest information from other contributing populations to the Simmental and Sim-influenced genetic pool, and then conduct an EPD evaluation.

The first step in evaluation is combining the datasets. This means that we combine the Canadian data with the US data in one large computer file. The key step here lies in identifying animals between the populations, such as AI sires that are used across countries. A separate file of these animals is maintained and is updated on a regular basis. This file tells the evaluation that Simmental Bull 1234 in Canada is the same animal as Simmental Bull 4567 in the US.

The next step is editing. Basically this means removing records that are in error. For instance a weaning weight of 1500 pounds would be removed from the data file. Animals with other obvious errors such as those that are born as a male and weaned off as a female would also be removed at this stage. Another primary edit is to remove data that is collected outside of the allowable age ranges. Examples of this would include such things as a weaning weight collected on an animal that is 300 days old, or yearling weights collected on long yearling bulls. This is why sending neat and clean performance records to the CSA is so important, as raw data from many animals has to be excluded at this stage of the evaluation.

The next step is to adjust the data for things such as age of dam, and age of the calf when weighed. This is identical to the process used when calculating adjusted weights, although the formula used is slightly more complex. As well, adjustments are made for the effects of heterosis.

The system then formulates contemporary groups. This is one of the most important steps in genetic evaluation. A contemporary group is comprised of animals of the same sex and similar age that have been raised in the same environment (management group). Evaluations work by making comparisons of animals in contemporary groups. Direct comparisons of phenotype are only made within contemporary groups. Because genetic evaluation uses comparisons, contemporary groups must have at least 2 animals in them and there must be some variation or differences between the animals. Often data will be lost at this stage due to single animal contemporary groupings. There may be no other animals within the herd that are directly comparable to an animal, and the animal cannot be compared to itself so the data for the animal must be removed from the evaluation.

This is part of why proper management groups and associated performance herds are important when submitting data. It allows the evaluation to most properly compare animals, and ensures that performance data from animals raised in the same environment is compared.

So How Does Multi-Breed Fit In?

In order to include animals from other populations outside of the North American Simmental, there must be strong pedigree ties and performance data from reciprocal mating. In other words, there must be enough links between populations that the populations can be accurately compared. This is what the USDA MARC Germplasm Evaluation program has provided for several of the major breeds in use in North America (http://www.marc.usda.gov/).

Prior to each evaluation the most current EPD from the other breed association are used to update the non-Simmental animals in the pedigrees. These EPD from the other breed are then adjusted to a Simmental equivalent using the most recent USDA MARC across breed adjustment factors (http://www.marc.usda.gov/cattle/gpe/AB_EPD2005News.pdf). As well, the accuracy value of the EPD is capped at 0.60, even if the contributing EPD has a much higher accuracy. This allows the progeny data in the Simmental database to have an impact on the resulting EPD from the Simmental evaluation. This approach is similar to those used by other organizations involved in multi-breed evaluation.

Further adjustments are also made to the progeny data to account for the effects of hybrid vigour and maternal effects.

Example:

An Angus sire is mated to Simmental females. The Angus sire has BW and WW EPD of 2.5 (0.99) and 45 (0.99) respectively. Using the 2005 adjustment factors, we would subtract 5.9 pounds from BW and 22.8 pounds from WW. The sire would enter the evaluation with Simmental equivalent EPD of BW -3.4 (0.60) and WW 22.2 (0.60) as its starting point.

If the sire�s calves are in valid contemporary groups, the Angus sire�s EPD may move up or down depending on the performance of his calves.

Putting It All Together

The evaluation works like a big spiderweb. It uses contemporary group information to extract environmental influence and look at the genetic component of differences between animals. Since animals are a combination of genetics interacting with the environment and the environment is effectively removed, it is then possible to compare these genetic differences across herds using pedigree ties.

The end result is a set of EPD that describe relative genetic differences across the North American Simmental population.

Accurate Evaluation and the Seedstock Producer

Since EPD are calculated from the information submitted by producers, it is producers who have the most impact over the accuracy of the evaluation. A producer�s own performance records will impact the EPD in their herd much more than the records of other producers. There are several things producers can do to ensure accurate evaluation:

1. Accurate pedigree information. Accurately identifying sires and dams can have a tremendous impact on EPD, particularly since EPD uses information from the animal and its� relatives to assess genetic merit.

2. Accurate and neat performance data submission ensures that calves are ranking properly and that differences between animals are based on actual differences, rather than typographical errors. It�s not a bad

idea to review performance reports for potential errors as well.

3. Proper grouping of calves is essential to good evaluation. Calves that are raised together should be grouped together. If producers are running herds together, such as a father and son, or siblings performance data should be submitted under one master herd. This does not affect ownership or registration status, but it does ensure that animals are grouped together properly.

4. Reporting data on all animals in a contemporary group is extremely important. Remember that EPD are calculated using differences between animals in a contemporary group. By failing to report all animals, all of the differences cannot be compared and the EPD may be negatively impacted. Not reporting the poor performers means that we can�t compare the better performers in the group to them, thus making the better performers in the group appear to be the poor ones.

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The Need for Feed

In beef production, well over 1/2 of the cost is due to cow herd maintenance. We are not talking about weaned calf production, we are talking about the entire system: breeding a cow, calving her, weaning her progeny (where her job is essentially done), and then finishing and harvesting that progeny. In this industry we often think about feedlot cost of gain, but rarely do we ever really address this overriding cost to beef production.
Breeders know that all cattle are not created equal. This belief that some cattle are better than others is what drove breeds into being in the first place. The same holds true with cow maintenance requirements. Not all cows are created equal. While we can do much with varying our cowherd management to reduce costs/energy inputs, there are still cows that no matter what the production system still require less feed than their herdmates to do the same job. This is largely due to genetic differences in cow maintenance requirement. This is one of the greatest opportunities for breeders to really reduce cost for themselves and their customers.

What makes up cow maintenance requirement?
Size � bigger cows need more energy to maintain themselves. Cow weight is used as an indication of size, with the ideal time to collect this information being at weaning time, but we still need a little bit more information to really assess feed or energy requirement.
Body Composition � this is basically fat cover or body condition score. BCS needs to be collected along with cow weight so that we can account for �fleshing ability� or ease of maintenance. We can all think of cows that raise big calves and still come in fleshy, and we can think of cows that come in as a �rack of bones�. Additionally, I think most of us can appreciate the difference in feed requirement between two 1500 pound cows; one with no fat cover takes a lot more feed to over-winter than one that is 1400 pounds disguised under 100 pounds of fat cover.
Milk � milk gives us an indication, not only of the cow�s need for feed while milking, but also of her relative organ mass. Even when dry, mammary tissue and the organ mass associated with maintaining that tissue requires energy.
The trick to successful production of anything, including beef, is to reduce the cost per unit of production.
Simmental breeders in Canada can participate in a mature size evaluation project through collecting and providing cow weight and body condition score together with their weaning weight data. It is extremely important that both weight and BCS be reported together to account for the differences stated above.

Mature Height
Frame score assessment and mature height evaluation uses data collected on hip height. An easy option to collecting this information is to tack a piece of measuring tape inside the chute and recording the data as animals are processed.

Bending the Growth Curve
The mature height and weight evaluation is useful for breeders that are trying to bend the growth curve of their seedstock. In essence, low birth weight, rapidly growing, early maturing cattle that maintain an acceptable mature size.

Embryo Evaluation
Currently CSA, ASA and Cornell are working on the inclusion of ET data into the genetic evaluation. In order to have records included in the evaluation, calves must meet standard criteria, and more importantly accurate recipient information is a must.
Recipient information must be in the format of:
Recipient Tag � unique within herd identifier
Breed Improvement � continued from page 6
Breed Code � combination of 4, two letter breed codes.
Birth Year � the 4 digit birth year of the recipient dam (not age of the dam)

For example, a correct recipient record might look like the following:
123M / SMSMSMSM / 2002
This is a Simmental recipient dam born in 2002

123M / SIMM / 3 is not an appropriate record
SIMM is not a recognized breed code
3 is not an appropriate age record
This record would be edited out of the genetic evaluation.
Each two letter breed code designates 1/4 of the recipient�s genetic makeup. For example, a SMSMANSM would be a 3/4 SM, 1/4 AN recipient from a Simmental sire and an Angus x Simmental dam.

Percentile Rank
By: Sean McGrath

Percentile Ranks are now available on the CSA search site at http://search.simmental.com and on Simmental registration papers.

Percentile ranks are shown below each EPD and its associated accuracy. Percentile ranks are a quick way to describe where an animal fits in the North American Simmental population. For example an animal with a birthweight EPD rank of 80 is in the top 80 percent of the Simmental population for birth weight genetics. We would expect roughly 20% of Simmental cattle to have heavier birth weight EPD, and 80% to have smaller birth weight EPD. An animal with a BW EPD rank of 25 is in the top � of the breed and so on.

The use of percentile ranks allows for rapid evaluation of the relative genetic merit of an individual without referring to the breed average EPD, or percentile rank tables. This new addition is designed to assist breeders in selecting within the Simmental population.

Example:

EPDS

CE
Acc
%RK

BW
Acc
%RK

WW
Acc
%RK

YW
Acc
%RK

MW
Acc
%RK

Milk
Acc
%RK

MCE
Acc
%RK

CW
Acc
%RK

YG
Acc
%RK

Marb
Acc
%RK

2.3
0.63
65

3.6
0.80
65

48.2
0.72
10

76.8
0.63
15

30.5
0.28
25

6.4
0.27
60

3.8
0.18
20

19.3
0.26
10

-0.36
0.26
1

0.35
0.21
4

By looking at the above example, we can see that this animal is in the top 65% of the breed for calving ease, the top 10% for weaning weight, the top 15% for yearling weight, the top 60% for milk, the top 20% for maternal calving ease. Additionally, the sire is in the top 10% of the breed for carcass weight, top 1% for yield grade and the top 4% for marbling.

The new percentile rank is printed below the EPD and accuracy on animal papers and on the CSA search site. Basically Percentile Rank describes where the animal fits in the current population of Simmental in North America. It is an easy way to assess the genetics of an animal without having to refer to breed averages, rank tables, or other information.

EPD

%ile

CE

50

BW

90

WW

25

YW

15

MCE

75

Milk

30

MWWT

30

The table at the right and the graph below shows an animal with the following percentile ranks.

Basically we see that the animal is right in the middle of the breed for calving ease. If we look at birthweight we see that the animal has a %ile of 90. This means that the animal has a heavier birth weight EPD than 90% of Simmental in North America. Conversely the birth weight is lighter than 10% of the population.

The weaning weight rank is 25. This means that the animal is in the top � of the breed for heavy weaning weight, however there are still roughly 25% of the animals with heavier WW EPD.

Ranks from 50 to 100 represent cattle in the lower � of the breed for a trait. Ranks between 1 and 50 represent cattle that are in the top � of the breed for a trait.

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Selection Index
By: Sean McGrath

Often, breeders and their customers are confused by the number of EPD�s that are available. For programs without a clear selection goal, deciphering which EPD to use, and how much emphasis to put on each EPD is difficult. As well, different customers have different needs and different bulls will likely be required to fit different customers� needs. While EPD�s are a powerful tool, unfortunately the sheer number of EPD�s combined with unclear goals can mean that some bulls are overlooked since they fall short on one EPD value, or may not cross an individual�s mental performance hurdle.

How we sort through this information, in a world of rapidly expanding genetic evaluation technology is a challenge. That is where selection index comes into the picture. Basically, selection indices are a tool that combines the relevant EPD values that apply to a selection goal into one number, based on the relative economic contribution of each trait to the end goal.

While relatively new to most beef cattle breeders, selection indexes are a tool that have been around for many years and is rapidly being developed by the industry.

For example, in a selection index for terminal genetics (where a sire is mated to females to produce feeder/slaughter calves) milk is not a consideration since no females will be retained out of a sire. An index such as this is likely to focus on growth, carcass yield and marbling, with a limited emphasis on calving ease.

A maternal index may focus more on the traits of milk, maternal calving ease, mature size and weaning weight genetics.

Selection index technology is not new to the world of animal breeding, and it is one of the most powerful tools available to us. The use of selection index in other protein industries has allowed for rapid genetic progress that targets production efficiency with market specific products.

One of the largest benefits to selection index technology, besides the fact that it allows selection to focus on one scenario specific value, is the ability of the index to break genetic antagonisms. By this, we mean that the index can account for some of the counterproductive relationships between traits, and also ensure that traits are not overemphasized in selection. Examples of antagonisms that animal breeders try to counteract are the relation between birth weight and growth, and the relationship between carcass yield and marbling. An example of overemphasis on a trait could include excess pressure on milk in production limiting environments. In these cases a selection index may balance effects on fertility against milk production to work out an optimal value.

For producers who are concerned that selection index leads all animals to be the same, not to worry. It is readily apparent that there are a variety of different scenarios that require Simmental genetics. For those who don�t believe this, simply look at the strong markets for various diverse branches of the Simmental gene pool. As well, because selection index combines many traits based on relative importance, strengths in some traits can offset weaknesses in others. For example, in certain situations rapid growth can offset somewhat reduced calving ease, or increased longevity can offset rapid growth rate.

Selection index as an animal breeding tool is one way to simplify and target specific markets/production systems with the right genetics. They will still require the experienced �eye� of the breeder and a professional level of customer support. As well, because they use genetic information and genetic information comes from data reported to the database, it is imperative that accurate and complete data be submitted wherever possible.

This is the basic concept behind selection index. The CSA Breed Improvement Committee is looking down this road and discussing the various tools and needs the breed has in order to develop tools that can make breeding beef cattle easier and help breeders target different markets with the �right� genetics for the situation.

Note: The new on-line registry system is now up and running. Those interested in signing up for the service should contact the CSA office.

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Complementary Data
By Sean McGrath

The CSA encourages data collection and has included the ability to collect data on many new traits in the last several years. This includes things such as mothering ability, calf vigour, udder scores, body condition, cow weight, frame size, and ultrasound data. The focus has been to allow breeders to collect the information that they are interested in, while making data collection optional. The only requirement, should a producer choose to collect a piece of information is the reporting of all animals in a contemporary group. Also important, is that many of the new traits require no expensive equipment or commitment of cash to measure.

This new data exposes a wonderful synergy in data between large and small breeders. In terms of breed improvement, both of these types of breeders are extremely important. Large breeders often have much bigger contemporary groups of calves, thus resulting in more comparisons within each group and adding significantly to genetic evaluation. Additionally, these large breeders contribute a lot of data to the CSA database.

Conversely, small breeders often provide records on traits that take more time to measure. This is the result of having more available labour on a per head basis. The type of data I am referring to includes repeated measurements over the life of a cow, such as udder scores, or mothering ability.

In this way, breeders of all sizes can complement the CSA dataset and result in better research and ultimately better genetic evaluation for all breeders.

There are some challenges for breeders of all sizes when it comes to data collection. We already touched on lack of available labour. More and more this is affecting all sizes of operations. Additionally, not having a critical size may make some procedures such as ultrasound appear cost prohibitive, as it is not possible to spread travel and set up costs over large numbers of cattle.

There are solutions to these problems. For larger herds collecting detailed information on first and second calvers may be a solution. This produces important records on young cows as they are entering production and also helps to systematically identify those that are having a hard time in the herd. For example heifers that are losing weight and condition between their first and second calf. As the dataset develops and we move towards a critical amount of data for evaluation, it also means that the older females in the herd will have a background of information collected when they were young, adding accuracy to their resulting EPD.

For smaller breeders, work together. If you have 20 head and want to ultrasound, get together with a neighbor (any breed will do) and coordinate dates to reduce travel and set up costs, or haul your cattle to his place. Similarly with carcass data, it is possible to pool cattle together and feed them out.

In short, all members matter when it comes to data collection. Your ability to resolve your unique size based challenges is dependent only upon your imagination.

Remember: All data collection for the CSA database is optional, however it is extremely important to report all animals in a contemporary group. EPDs reflect the data in the dataset, and are based on comparisons within contemporary groups. It is important to make as many comparisons as possible (all animals) in order to accurately determine where an animal fits in the Simmental population.

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Carcass Data-The Basics
By: Sean McGrath

Several Simmental breeders have expressed interest in collecting carcass data on their genetics, and some have already assembled some data on their cattle. As customers are looking at retained ownership, and other marketing options whether by design or otherwise, carcass characteristics become important to a customer when they own cattle through to slaughter.

I thought it would be useful to discuss in brief what some of the basic carcass data means.

All cattle are graded based on a few select criteria. Youthful cattle fall into the A grades. This is typically what our feedlot steers and heifers fall into. Older animals fall into the D grade, or E grade in the case of bulls. Off grades of youthful animals are usually put into the B category.

For the purposes of genetic evaluation, what we are interested in is data on young or A class cattle.

Cattle are graded by assessing the entire carcass and then grading the rib-eye between the 12th and 13th rib.

Yield - is a classification of how much meat is in the carcass. A Yield Grade 1 or Y1 has more meat than a Y2 which has more meat than a Y3. Yield grade is assessed by looking at the overall muscling of the animal, and the size of the rib-eye relative to the amount of fat surrounding it. If the circles below represent a rib-eye with the surrounding fat, it is easy to see the difference between a Y1 and a Y2, or Y3.

Quality Grade - is the level of marbling as measured in the ribeye. Marbling is the flecks of fat in the rib-eye. Grading is done after the carcass is chilled as this allows the grader to see the fat, since it turns white when cooled. This is similar to what happens if you leave a frying pan with oil in it to cool on the stove.

Cattle with the highest level of marbling are termed Prime, followed by AAA, and AA, with A having the least amount of marbling. If we look at the rib-eye circles below we can see the difference between a Prime or AAA and an A.

Y1 Y3

Off Grades - are used for Youthful cattle that don�t fit the criteria for an A grade.

B1 - Occasionally you may see a B1 grade assigned to a young animal. This classification is for animals that are devoid of fat (less than 2 mm) around the rib-eye or are devoid of marbling.

AAA A

B2 - grade is used to designate cattle that have distinctly yellow fat cover. This grade is rarely used in Canada, where we finish calves on high concentrate diets.

B3 - grade identifies cattle with extremely deficient muscling characteristics. Typically this grade is not a factor with beef breeds of cattle.

B4 - esignates what is typically known as a dark cutter. These are bad news and typically are heavily discounted. Often dark cutting is caused by reaction to stress prior to slaughter.

Why We Grade - Cattle are graded to separate them into specific markets based on their characteristics. Grading is also often used for a term of payment. This is typically referred to as grid pricing. A typical grid example is shown in the table. Generally cattle within a carcass weight range that exhibit higher yields and more marbling command a higher premium.

	Y2	Y1	Y3
Prime	$$$$	$$$	$$
AAA	$$$	$$	$
AA	$$	$
A	$

Since overall fat level and yield are antagonisitic, the challenge for breeders is to maintain or increase yield and target specific fat deposits (marbling) in their cattle without increasing overall fat levels. This is why breeders are starting to collect and use ultrasound and carcass data in their breeding programs.

We will touch more on carcass data for genetic evaluation in future articles, however there is some great information available on the internet for those who are interested:

Canadian Beef Grading Agency - www.telusplanet.net/public/cbga/

Canadian Beef Export Federation - www.cbef.com

Check out the Grading, Inspection and Product Catalogue menus above.

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The Performance Picture
By: Sean McGrath

Performance reporting has been with us for as long as breeds have been developed. Over time people have naturally tended to report what they could measure. In past times, this may have meant bigger, taller, smaller, blacker, redder, mother and father. As technology has developed to improve our measuring ability the list of traits has grown to include not only pedigree and easily visible traits, but also things such as growth rate, fertility, and ultrasound measurement.

As we obtain more information, we can move from a rough sketch of an animal�s genetic merit to a full blown photograph of where they fit into the Simmental population.

Adding more measures, such as udder scores, hip heights (frame score), mature weight, body condition scoring, and breeding data basically adds more colours to the performance pallet. For example if we want to paint a picture about fertility we need to collect breeding and subsequent calving information. If we wish to view fleshing ability and mature size, we need to add frame score, body condition and weight data to our dataset.

In order to compare this growing list of empirical measurement, EPDs have been developed to provide a picture of what an animal looks like from a genetic perspective, and also to place the animal in context with the entire breed. This is the background of the picture, so to speak.

EPDs provide us with an idea as to the relative performance of an animal�s progeny. In many ways we can refer to the EPD profile of an animal as giving us a picture of how that animal should perform. When we have all the details (complete and accurate reporting) we can draw a pretty good picture of what we expect an animal to do (Figure 1.).

Figure 1. A clear performance picture can tell us a lot about an animal. Complete data on traits of interest produces a clear picture and places the animal in context with it�s surroundings.

Sometimes not all animals are reported. For example, perhaps only calves that are being registered, or heifer calves are reported. Another example, would be not reporting data on all traits of importance. This means that the picture we can produce in terms of a genetic profile is limited, and parts of the picture may be missing (Figure 2.).

Figure 2. The same performance picture with some of the data removed. For example, only reporting on registered calves, or reporting only on selected traits.

While we can generally get a good genetic outline of the animal, as the data becomes more and more limited, the EPD picture that is drawn tells us less useful information about the animal we are interested in (Figure 3.).

Figure 3. An extremely limited performance data profile, including limited reporting of animals and traits.

In cases of extremely limited performance reporting, such as reporting on calves from only one sire used in the herd, or only reporting on those animals we are bringing into production, we also lose the background information on the herd. For example, there are cows in the Simmental database that have their first calf reported when the female is in excess of 5 years old. Does this mean that the female was open for 3 years, or that the calves were not reported for some other reason? The loss of this data affects not only that one female, but also the overall herd outline.

In other words, we do not have a good idea of what the animal looks like or even where the picture was taken. This makes it difficult to accurately identify those genetics that best fit our specific production and marketing goals (Figure 4.).

Figure 4. A performance picture where background herd information has not been reported. It is very difficult to get a good picture of what this sire looks like or where he is standing within the breed.

It is important to remember that producing a performance work of art takes time and patience. Adding traits to genetic evaluation requires time and investment by breeders to collect, analyze and use the data.

Ideally all Simmental breeders will try to paint a performance Picasso for their herd through complete and accurate reporting on all females each and every year, and deciding on what details are important, including breeding, growth and carcass or ultrasound data. By producing a clear picture of what you are producing it is possible to more accurately make selection decisions and also to provide your commercial customers with the right genetics for their situation.

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