Selection for performance traits based on adjusted weights or ratios can be  misleading. Environmental effects can increase or decrease the actual performance of an animal, and its ratio is highly dependent on the other animals it competed against in a contemporary group. An excellent calf might be below average in a truly elite group and ratio below 100, while the same animal in another group could be the highest-performing individual. EPDs allow breeders to fairly compare animals from different farms and ranches, or from different years, without bias. By using the pedigree connections that exist within a breed’s database, EPD calculations allow fair comparison of all cattle in that breed. The significant amount of artificial insemination (AI) used by seedstock breeders adds accuracy to EPDs, because many contemporary groups from different breeders have one or more common sires.

Expected Progeny Differences revolutionized cattle breeding. They predict how future progeny of each animal are expected to perform relative to the progeny of other animals listed in the database. EPDs are expressed in units of measure for the trait, plus or minus. Because performance traits are always influenced by environmental effects, EPDs cannot predict actual performance. 

The American Angus Association has a number of EPDs to predict traits ranging from calving ease to growth to carcass merit.

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It’s critical to understand that EPDs cannot be directly compared across breeds, and you might find EPDs on Angus bulls that aren’t produced by the American Angus Association. Those, too, cannot be directly compared. To allow for comparison of EPDs across breeds, the USDA Meat Animal Research Center (MARC) has developed adjustment factors.

The USDA adjustments work from an Angus base.  For example, to compare a Charolais birth weight EPD to that of an Angus, an adjustment factor of +7.1 should be applied to the Charolais EPD. To compare a Hereford yearling weight EPD, an adjustment factor of –26.6 should be applied.

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Dollar Values ($Values) were created to simplify selection and allow for change in several different traits at once relative to a specific breeding objective.  $Values are expressed in dollars per head, and are used to compare how future progeny of a sire are expected to perform, on average, compared to progeny of other sires in the database if the sires were randomly mated to cows and if calves were exposed to the same environment.  

The Association $Values encompass the revenue generated from genetically derived outputs (revenues) and associated costs (expenses) from required inputs. For example, Weaned Calf Value ($W) takes into consideration the revenue of heavier weaning weights as well as the expense of achieving those heavier weights. The $Values are sensitive to the industry-relevant components used in calculating the indexes.

In general, $Values  give cattlemen any easy way to align a value with their breeding objective. For example, if your breeding objective focuses on delivering high value in the feedlot and on the rail, you would be interested in Feedlot Value, Grid Value and Beef Value.

Indexes, over time, are the most effective way to make genetic progress, as they tie genetic merit to economics in a way that helps producers make the most progress in profitability through a systematic approach. 

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When discussing selection tools, people typically think of the expected progeny differences (EPD) first. However, another important value often accompanies the EPD: the accuracy.

Accuracy is a statistical value that represents the amount of information behind an EPD. It ranges from 0 to 1, with zero reflecting the least accuracy and 1 signifying the highest accuracy. This metric is typically located directly below the published EPD, providing insights into the confidence and precision of the genetic predictions. That accuracy number is derived from the same model and data used to estimate the EPD, and it can be used as an indicator of risk for possible changes in the animal’s individual EPD as more information gets added to the evaluation. Using the accuracy values, we can calculate a possible change distribution, which is the potential amount of future change in an EPD prediction. The more accurate the EPD, the smaller the range of possible change. 

Animals that have been genomically tested will typically have a higher accuracy value than untested animals. The added information used in the EPD calculation adds confidence to the prediction and reduces the risk of change.

From a bull buyer’s perspective, the accuracy value and the possible change table can serve as a risk mitigation tool for selection decisions. You must balance the risk and reward of those decisions. For instance, the easiest way to avoid risk is to use proven animals only, but it comes with a potentially lower reward because of slower genetic gain through slower generational turnover. The opposite strategy is to try to maximize the rate of genetic gain by using only young, unproven animals for faster generation turnover; but this strategy comes with bigger risks.

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