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The ins and outs of net merit and rank

Nate Zwald Published on 29 August 2012

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Selection indexes are great tools and there is certainly no shortage of them available.

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Most countries have at least one, and many have two or more nationally published indexes – as is the case in the U.S. with Net Merit (NM) and TPI.

NM incorporates what USDA-AIPL considers economically important traits into one index.

Indexes are very important selection tools because they prevent setting minimum criteria for particular traits, which limits genetic progress.

However, the weights in the three categories that make up the index (production, health, conformation) are extremely influential in ranking the sires, making certain traits more or less important than you might perceive or value for your operation. Before you base all of your selection decisions on NM, have you considered how the index actually works or what impact certain traits have within the index?

An easy way to think of NM is to group the traits that make up the formula into three main categories with their relative weighting, as in Figure 1 .

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Health traits, for example, receive the most overall emphasis (48 percent) in the NM formula. In 1994, NM started out as primarily a production index with 74 percent of the weight on production traits.

As recently as 2005, the index still had 55 percent of its weight on production. Many still perceive NM to be driven by production traits, but the current formula has a much higher weighting on health than production.

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The NM formula is modified when changes in production costs or milk prices influence profit. For example, an expected change in future commodity prices could influence a change in the NM formula weightings, which could ultimately impact rank.

The most recent modification to the NM$ formula was in 2010 – when the weight on production decreased from 46 percent to the current 35 percent – and the weights on health traits increased significantly.

The current weights reflect an estimate of the future prices of milk, components, cull cows, commodities, replacement raising costs and other health costs, but that is what they are – estimates.

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Like with TPI, when considering the NM index as a selection tool, we can say that while these weights might reflect future expectations for the “average dairy,” the real question needs to be: “Do these weights accurately reflect my expectations and goals for my dairy?”

So what does the rank on the NM list really mean? We know the perception is higher ranking = “better,” but “better” is a very subjective term. Is the 100th bull really that much better than the 200th bull, for instance? Let’s look at an example.

Assume we have three bulls – Bull A and Bull B, which are theoretical, and AltaOTIS, which is an actively marketed bull. AltaOTIS has a NM value of +835, ranking him high on the industry list of sampled bulls.

All three bulls have identical breeding values, except Bull A is one point higher for UDC and FLC and one point lower for body size, and Bull B is one point lower for UDC and FLC and one point higher for body size. What would you expect the NMs of Bull A and Bull B to be based on these differences in the conformation categories?

To answer this question, you need to know the impact of each trait in the NM formula. This information is listed in Table 2 , with

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traits in red having negative weight in the formula.

For example, the weight for SCS is negative because lower SCS values are more profitable.

Once we know the NM for these two bulls, the next question is: Where would each rank on the industry-wide NM list?

NM ranking
The difference in NM between the top 100 and top 200 NM-ranked bulls has become very minute. In fact, when considering the industry-wide top GTPI list of sampled bulls, only 35 NM$ separate the 100th bull ranked for NM from the 200th bull.

Additionally, only 102 NM$ separate the 100th from the 500th-ranked bull for NM. Yes, that means 400 bulls are within 102 NM$ of each other!

This is certainly not something we were used to prior to genomics but, because so many more bulls are being tested now, it is a new reality in the industry. The conclusion is obvious: The importance of rank has little significance, as the difference between bulls is extremely small.

Impact of certain traits on NM – example continued
If you did the calculations, you should have discovered that changing all the conformation traits by one point has a $70 impact on NM. Bull A would have a NM of +905 and Bull B would have a NM of +765.

Bull A would rank fourth in the industry and Bull B would rank 116th. Even when most of the weight is on production and health, as is the case with NM, modifying the conformation traits by one point still has a huge impact.

Based on what you’ve learned by reading about NM and rank, and by going through the provided example, the conclusions should be clear:

1. The current NM formula has the most weight on health traits, not production traits – a common misperception.

2. Even though the weight on conformation traits looks relatively small, changes to those traits can have a significant impact on a bull’s rank.

3. A bull’s NM rank will change disproportionately with small increases or decreases in individual traits because of the number of bulls now being genomic tested.

4. The best “formula” is the genetic plan you develop with your A.I. representative.

It’s easy – just put your weights in the circles for production, health and conformation. PD

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Nate Zwald
Senior Director of Global Strategy & Marketing
Alta Genetics

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