It is not uncommon for a producer to state, “I have been putting high emphasis on genetics within my herd, but the cows just don’t seem to be at the performance level they should be.”

That could be because environmental and management factors play a large role in determining if a cow or heifer is reaching its genetic potential.

Data analysis can help determine if cows are in fact underperforming. This analysis can be conducted by most genetics suppliers through value-added programs that analyze herd performance based on genetic merit.

Such an analysis requires access to herd records (e.g., herd management software backup or DHI test records). Proper sire identification of females is also key to the reliability of the genetic reports (particularly for non-genomic-tested herds).

If the analysis confirms the herd is underperforming, environmental or management factors may need to be further investigated and, if possible, addressed. Remember, too, when assessing the impact of genetics within herds, it is not uncommon to see variability in cows’ performance in comparison to their genetic merit.

Advertisement

Non-genetic factors impact production

An Australian study illustrates how non-genetic factors can impact a cow’s ability to produce milk and components.

This study looked at different levels of feed concentrate and how these levels affected production values based on the level of genetics (high versus low genetic merit). Figure 1 compares genetics (the sires’ Australian breeding value for milk) to the cows’ actual milk yield.

The predicted relationships between milk yield and Australian breeding value for milk

As shown at far left under “Low Concentrate,” increasing genetics only marginally increased milk production. However, as shown at far right under “High Concentrate,” increasing genetic merit has a much greater response in milk production.

Another way to interpret this figure is: If the herd is managed marginally, genetics won’t play as big a factor in herd performance. In better-managed herds, genetics will be more fully expressed, and there will be more differentiation between cows of high versus low genetic merit.

Likewise, Table 1 shows when comparing low versus high genetics for cows fed low concentrate, the difference in combined fat and protein was 27 kilograms per cow per lactation (59.5 pounds per cow per lactation).

Differences between high genetic merit and low genetic merit

Click here or on the image above to view it at full size in a new window.

When looking at high concentrate, the difference is 51 kilograms per cow per lactation (112.4 pounds per cow per lactation). Thus, as feed concentrate increased, the performance gap between the high and low genetic females increased substantially. This illustrates the impact non-genetic factors play on cow performance.

Evaluating reproductive efficiency

When considering the 21-day pregnancy rate performance metric, genetic traits such as Daughter Pregnancy Rate (DPR) generally impact the reproductive efficiency of the herd. However, this is one of many factors that can affect herd fertility.

Other factors that may impact reproduction include cow status (e.g., health, cycling status), nutrition, management (e.g., farm protocols), labor (e.g., protocol implementation), semen (e.g., genetics, bull fertility) and environmental conditions (e.g., heat stress, surface type).

Furthermore, fertility traits such as DPR tend to have a low heritability (4 percent), indicating the much larger role environment has on reproductive performance.

Still, as DPR values increase in a herd, so should herd pregnancy rate. This is demonstrated in Figure 2.

Overall herd preganacy rate by sire DPR quartile

The data used in this figure is based on a group of 278 Holstein herds divided into four groups or quartiles based on the average sire DPR of the cows in the herd (i.e., DPR of the sire ID). The herds, from the Genex database, each contain 500 cows or more.

The figure shows the average herd pregnancy rate for each quartile and the average sire DPR value for the herds in that quartile. Going from quartile 4 (bottom 25 percent) to quartile 1 (Top 25 percent), there is a corresponding increase in herd pregnancy rate that coincides with the increase in sire DPR values.

While increased DPR values generally lead to increased herd pregnancy rates, there is more to analyze. Figure 3 examines the variability in the top and bottom quartiles for herd DPR and how it relates to herd pregnancy rate.

Percent distribution of quartile 1 and 4 DPR herds by actual herd pregnancy rate

The figure shows which pregnancy rate quartile the herds in quartile 1 for sire DPR (shown in blue) and quartile 4 for sire DPR (shown in yellow) ended up in.

As a quick interpretation, 15 percent of the quartile 4 herds (bottom 25 percent for sire DPR) actually performed in the top 25 percent (or top quartile) for herd pregnancy rate.

Likewise, 21 percent of the quartile 1 herds (top 25 percent for sire PTA DPR) ended up performing in the bottom 25 percent (quartile 4) of herds for herd pregnancy rate.

This data shows environmental or herd management factors may have caused some herds to overperform their genetic merit for DPR and others to underperform.

In conclusion, genetics plays an important role in herd performance. As herd management and environmental factors improve, greater differentiation between low- and high-genetic females will be observed.

However, if performance is not meeting the predicted values of the genetic merit of the herd, environmental or herd management factors may need to be investigated and addressed accordingly. Furthermore, improving upon these factors would provide a much greater return on investment for herds with higher genetic selection criteria.  end mark

References omitted but are available upon request. Click here to email an editor.

Joe Binversie