NC State Extension Publications

Introduction

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Cattle selection has long-term effects on profitability in all sectors of the industry. In the cow-calf sector, selection often focuses on the sire because of the significant impact that sire selection can have on a herd’s genetic makeup. After four generations, over 90% of the genetics in a herd are the result of sire decisions. This assumes that replacement females are retained in the herd. Therefore, appropriate and accurate sire selection is critical to the genetic improvement of the herd. Since cow selection is also important, the tools discussed in this article apply to the selection of replacement females as well.

Selection Tools

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There are many tools that are utilized for selection, although some are more accurate than others. An animal’s phenotype (observable attributes such as physical appearance, weight, and muscularity) is the result of the animal’s genetics and their environment. Genetic progress requires isolating the genetic component of the phenotype from the environmental component. If selection were based on phenotype alone, the selection would be made unintentionally with environmental and not genetic factors. The environment varies from farm to farm and from year to year, while genetics do not. Genetics are passed from one generation to the next. Genetics purchased on one farm are the same genetics when the animal arrives at a new farm. Although the genetics may vary, the DNA sequence remains the same. Therefore, accurate measurement of an animal’s genetic merit is critical for long-term genetic improvement.

Phenotype = Genotype + Environment + (Genotype x Environment)

Visual appraisal is a common selection method. This involves evaluating the physical appearance of the animal and making breeding decisions based on the desire to improve this appearance. While structural attributes are important to animal longevity, an animal’s physical appearance is a phenotypic measurement that is influenced by the environment. Caution should be used to ensure that breeding stock is not selected based on an environment that cannot be repeated on a different farm.

Performance data (weaning weights, yearling weights, ultrasound data, and shedding scores) are valuable components of a selection program. These metrics provide a benchmark for improvement. Records should be maintained on all traits that affect an operation’s revenue and expenses and that will be used in a selection program. These traits are referred to as economically relevant traits. Performance data are needed to assess improvement over time, since the phenotypic measurements are affected by the environment. An example is when weaning weight increases in a given year with good grass production although the genetics for weaning weight may be the same. Therefore, a superior tool is needed for assessing the true genetic improvement.

Expected progeny differences (EPDs) were introduced into the beef cattle industry in the 1980s. These EPDs provide beef producers with the most accurate selection tool that is available. Expected progeny differences are the most accurate selection tool because it combines not only individual performance data, but also all known pedigree information (for example, sire and dam performance and sibling performance), progeny performance, and genetic correlations between traits. In 2009, the American Angus Association was the first group that began incorporating genomic data (based on the animal’s actual DNA) into their EPD calculations. This resulted in genomic-enhanced EPDs, which further improved the accuracy of the selection tool. An EPD represents an individual’s genetic merit and is a numerical representation of a genotype. Since this tool isolates the genetic from environmental components, selection decisions can now be made based on actual genetic merit without inadvertently selecting for environmental factors that may change. Thus, the genetic merit for over 20 traits can be estimated when making breeding decisions for a herd.

Understanding EPDs

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Expected progeny differences are expressed in the same unit that the trait was measured, which simplifies their interpretation. For example, birth and weaning weights are reported in pounds. The numeric output simplifies the selection of specific traits and provides an estimate of expected differences in offspring performance. Expected progeny differences do not predict actual performance. Instead, they are used as a comparison tool between individuals such as bulls. An example is provided in Table 1.


Table 1. Comparison of progeny weaning weights between two bulls from two different farms.
WW EPD (lb.) Progeny Weaning Weights (lb.)
Farm A Farm B
Bull A +80 525 700
Bull B +62 507 682
Difference 18 18 18

In this example, Bulls A and B are from two different farms with different environments. Based on their weaning weight (WW) EPDs, you would expect on average an 18 lb difference in calves at weaning. On Farm A, calves sired by Bull A weighed 525 lb, while calves sired by Bull B weighed 507 lb. On Farm B, calves sired by Bull A weighed 700 lb, while calves sired by Bull B weighed 682 lb. Regardless of the location, the difference in progeny weight at weaning is an average 18 lb. Actual weights may vary although the differences remain the same. Farm B may have better feed resources that help calves grow more quickly in the pre-weaning time period.

Selection Priorities

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Prioritization of traits varies according to a producer’s goals and the herd needs. For example, producers who sell their calves at weaning will focus on a different set of EPDs compared to the producers who retain ownership through the feedlot. In the same way, producers who are looking for a bull to service their heifers will seek different traits compared to a producer who is looking for a bull for his mature cows. Before evaluating EPDs, it is important to consider goals for the herd and the current status based on production records. Selection priorities can then be determined based on the traits that need the greatest improvement. The greater the number of traits selected at a given time, the less progress can be made in any given trait. Therefore, it is best to identify and prioritize a few key traits that will help accomplish your goals. This approach will minimize the likelihood of feeling overwhelmed by the many traits available for use.

Table 2 provides an example of various EPDs from two Angus bulls that demonstrate how traits are interpreted and prioritized.


Table 2. Comparison of EPDs for various birth and growth traits between two bulls.
CED (%)1 BW (lb)1 WW (lb)1 YW (lb)1
Bull A +5 +2.1 +80 +150
Bull B +10 -0.6 +62 +136
Difference 5 2.7 18 14
Breed Average +7 +1.2 +62 +111

1CED: calving ease direct, BW: birth weight, WW: weaning weight, YW: yearling weight


These two bulls can be compared to one another and to the breed average. The difference in EPDs is calculated by subtracting one value from the other. This difference, as reported in Table 2, represents the expected difference in progeny performance. In this example, Bull A has superior growth EPDs. On average, calves sired by Bull A will be 18 lb heavier at weaning and 14 lb heavier at the yearling time point. In contrast, Bull B has superior calving ease EPDs. On average, calves sired by Bull B will have 5% more unassisted births when born to first-calf heifers based on the calving ease direct (CED) EPD. In addition, calves sired by Bull B will be 2.7 lb lighter at birth.

Reports with percentiles allow producers to quickly visualize where an individual EPD ranks relative to the breed population. Expected progeny differences are only relevant within the breed so that, for example, Angus EPDs cannot be compared directly with Hereford EPDs. The percentile ranking represents where that trait’s value falls relative to the rest of the breed, where lower percentile rankings represents superior EPDs. Table 3 summarizes these rankings for Bull A and B from the previous example. The 50th percentile is the breed average. Bull A is in the top 10% of the Angus breed for WW and the top 5% for YW. However, this bull is in the top 60% and 70% for CED and BW, respectively, which indicates this bull is below the breed average for these two traits. In contrast, Bull B is in the top 25% and 15% for CED and BW, respectively.


Table 3. Comparison of the percentile rankings for various birth and growth traits between two bulls.
CED (%)1 BW (lb.)1 WW (lb.)1 YW (lb.)1
Bull A 60% 70% 10% 5%
Bull B 25% 15% 50% 15%
Breed Average 50% 50% 50% 50%

1CED: calving ease direct, BW: birth weight, WW: weaning weight, YW: yearling weight


In summary, Bull B has superior CED and BW EPDs. Both bulls are equal to or greater than the breed average for WW and YW EPDs. For first-calf heifers, Bull B is the logical option whose progeny will still have good growth potential. If rapid growth rates are desired and mature cows will be bred, Bull A would be the best choice.

Each breed has its own percentile rankings. Many breeds report similar EPDs, although some traits differ between breeds. Table 4 provides websites where this information for various breeds can be found. Be sure to use the correct report and EPD definitions for the cattle breed you are raising or purchasing.


Table 4. Links to percentile rankings and EPD definitions for various breeds common in North Carolina
Links to Breed Resources
Breed Percentile Rankings Trait Definitions
Angus American Angus Association Percentile Breakdown American Angus Association EPD and $Value Definitions
Red Angus Red Angus Association EPD Percentiles Red Angus Association Rancher's Guide to EPDs
Simmental American Simmental Association SimGenetics Purebred Simmental Percentiles Table American Simmental Association Quick Reference to ASA EPD and $ Indexes
Hereford American Hereford Association Breed Avg./Perct. Distribution American Hereford Association Trait Definitions
Charolais American International Charolais Association Genetic Evaluation
Gelbvieh American Gelbvieh Association EPD Info American Gelbvieh Association EPD Definitions

Selection Indexes

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Since beef production is complex, multiple traits may need improvement at the same time. Selection indexes were created to simplify the process, which can be difficult to manage. A selection index applies weights (economic values) to certain economically relevant traits related to a particular breeding objective. Therefore, progress can be made in multiple traits related to the same goal at one time. For example, the Maternal Weaned Calf Value ($M) Index in the Angus breed combines CED, calving ease maternal, WW, milk, heifer pregnancy, docility, mature cow weight, claw set, and foot angle EPDs. This index, which predicts differences in profitability from conception to weaning, is expressed in dollars per head. The index or a similar maternal index is valuable when replacement heifer selection is the goal.

A terminal index focuses on end-product value with growth and carcass traits. For example, the Angus Beef Value ($B) Index combines YW, dry matter intake, marbling, carcass weight, ribeye area, and fat EPDs to predict differences in profitability for post-weaning gain and carcass merit. Some breeds have a dual-purpose index that includes both terminal and maternal traits. One example is the Simmental All-Purpose Index. Indexes simplify the selection process and allow for improvement in multiple EPDs at one time. After you establish your selection goals, you can select the most appropriate index to use for your needs.

Genomic-enhanced EPDs

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Expected progeny differences are more accurate than many other selection tools. However, each of the EPDs has an associated accuracy value that represents the relationship between the true and expected values. The greater the accuracy, the closer the expected progeny difference is to the true progeny difference. The accuracy increases as more data are generated. For example, the bull sires more calves. However, the accuracy for young bulls or heifers is generally low because they do not have progeny records. Fortunately, the inclusion of DNA data through genomics has led to increased accuracy in the younger sires and dams. The impact varies depending on the trait, although it has the potential to improve a young animal’s accuracy equal to that of an individual with 20 progeny. This is known as progeny equivalents.

Genomic data make a greater contribution to the EPDs of younger bulls or heifers, although the impact decreases as more progeny data become available. Therefore, genomic-enhanced EPDs are most valuable when selecting and/or buying younger breeding stock. In addition, genomic data allow for parentage confirmation. An inaccurate pedigree can have a significant impact on EPDs accuracy because the sire and dam genetics are the foundation of EPD calculation. This technology has improved selection programs and the opportunities for genetic progress.

Summary

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The genetic improvement of beef cattle does not happen quickly. New tools now exist to make measurable improvements over time. Most of the genetic change comes through bull selection unless a number of replacement females are purchased from sources off the farm. After goals are established and current production metrics are assessed, producers can then use EPDs to identify genetically superior breeding stock for traits of economic relevance based on selection priorities. Selection can be further simplified through the use of selection indexes that allow for improvement in multiple traits.

Genomic testing can further enhance the accuracy of EPDs, especially in younger bulls and heifers. See Extension publication AG-947, Genomic Testing and Its Uses in Beef Cattle, for more information. Expected progeny differences are the most accurate and valuable selection tool. These EPDs exist for a variety of traits that can satisfy a wide range of breeding objectives. Appropriate goals and accurate selection of breeding stock will result in long-term genetic improvement for your herd and profitability for your enterprise.

Authors

Assistant Professor and Extension Beef Specialist
Animal Science
Extension Specialist, Small Ruminants
Animal Science
Extension Associate
Animal Science

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Publication date: Dec. 14, 2023
AG-954

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