Genetic tests for a variety of economically-relevant beef cattle traits have become commercially available. Cattle producers collect a hair sample or tissue sample from an ear tag application; samples are sent to a lab where each animal’s DNA is sequenced; and results characterizing an animals individual genetic potential for traits of interest are provided. For an example of the results, see Figure 1 (Igenity, 2016). Independent research has found many of these tests are good measures of the traits they are designed to predict.

While genetic test can provide a remarkable amount of data about potential feedlot performance, economists have only considered a few of these tests and estimated their value to producers. This is important because producers will only adopt this technology if the value of genetic information is greater than the current cost of the test which is about $40 per head. This article briefly summarizes our recent research designed to estimate the value of genetic testing in the U.S. beef industry, specifically focusing on the value of this information to the feedlot sector.

In the first study (Thompson et al., 2014), the value of genetic information is estimated for seven economicallyrelevant beef cattle traits (average daily gain, hot-carcass weight, yield grade, rib-eye area, marbling, tenderness, and days-on-feed) for two scenarios of value. How could genetic information be used? First, genetic information could be used to select which cattle would be selected for placement in the feedlot. This is known as “markerassisted selection.” In other words, feedlot managers would use the information to determine how much more or less animals with superior or inferior genetics are worth compared to their contemporaries.

Figure 1. Example test results for genetic test characterizing average daily gain, Source: Igenity, 2016

Not surprisingly, results indicate that the values to the feedlot of animals with different genetic profiles differ significantly. The value of marker-assisted selection ranged from $3-$22 per head depending on the trait being evaluated (Figure 2). These values represent the additional revenue above all costs except for the cost of the genetic test. Unfortunately, the value generated from genetic information is not enough to pay for the current cost of the genetic tissue test.

Figure 2. The value (additional revenue above all costs except for the cost of genetic testing) of genetic information for selecting feeder cattle for placement in the feedlot for seven economically-relevant beef cattle traits.

Never the less, it is important to note that average daily gain ($22 per head) and marbling ($21 per head) were identified as the most economically-relevant feedlot cattle traits. This makes sense given that animals with higher average daily gain will result in heavier finished weights and/or fewer days-on-feed, both of which increase profitability. In addition, the current structure of the grid heavily rewards more favorable quality grade, or marbling outcomes. It is also important to point out that these values are sub-additive. That is, selecting cattle based on average daily gain and marbling generates a value of $30 per head and not $43 per head.

A second use of genetic information could be to sort cattle that are already owned by a feedlot into management groups that are most likely to perform similarly. We call this “marker-assisted management.” Specifically, this first study focused on the value of using genetic information to choose cattle for the optimal dayson-feed. That is, what is the economic benefit of being able to feed cattle with differing genetics for different numbers of days-on-feed? Again, estimating the value of genetic information as the additional revenue above all costs except for the cost of the genetic test, the value of marker-assisted management was less than $1 per head for each of the traits. This of course means it would not be profitable to use genetic testing to sort cattle by dayson-feed (Figure 3).

Figure 3. The value (additional revenue above all costs except for the cost of genetic testing) of genetic information for sorting feedlot cattle into management groups by optimal days-on-feed for seven economically-relevant beef cattle traits.

In general, these low values were the result of limited differences (a small variation) in optimal days-on-feed for the best and worst performing animals for any given trait. Still, there remains potential for using the information derived from genetic testing to improve other feedlot management decisions, including how animals are fed, how technologies such as implants and beta agonists are used, and how cattle are marketed.

In the second study (Thompson et al., 2016); we use the same data to estimate the value of a marker-assisted management scenario in which genetic information is used to sort and selectively target cattle to different marketing methods: live weight, dressed weight, or grid pricing. For example, animals with higher genetic potential for marbling could be fed longer, allowing them to deposit fat, and then be targeted to grid pricing to capture the premiums associated with more favorable quality grade outcomes. Results indicate that sorting cattle into marketing groups based on genetic information for yield grade and marbling generated up to $13 per head of value defined as the additional revenue above all costs except for the cost of the test. Therefore, extending the definition of marker-assisted management to include marketing decisions increased the value of genetic information. However, this value was still not enough to pay for the cost of testing.

SUMMARY

Today, tissue test for various genetic markers can generate a surprising amount of information including estimates of feedlot performance for individual cattle. So, the economic question we explored was whether the returns of using the information exceeded the costs of the test. One way the information could be used was in determining which animals had the greatest value in the feedlot. This is known as “marker-assisted selection.”

A second way this genetic information could be used would be to sort animals into homogenous groups after they are purchased and come into the feedlot. The objective would be to reduce the performance variability within pens of cattle. This is called “marker-assisted management.”

Our results found that using genetic information to select cattle or to sort feedlot cattle into management groups based on optimal days-on-feed or marketing method is not profitable given the current cost of genetic testing of about $40 per head.

The potential for using these genetic tissue test in the future remains. As genomic technology continues to advance, the potential for declining testing costs and the development of tests for other important feedlot profit drivers, such as disease resistance and feed efficiency, may lead to cost-effective genetic testing.

Until then, the primary value of genetic information in the U.S. beef industry will continue to come from the ability to improve the genetic makeup of cattle entering the feedlot. These improvements will need to take place in the industry’s breeding sector where cow/calf operations are able to impact the genetic makeup of their herds. However, selecting breeding stock for traits that are valuable in the feedlot sector may, or may not, be advantageous in other sectors of the beef industry. Although beyond the scope of this research, the impacts of these feedlot traits on other sectors must also be considered.