by Chad Dechow
The author is an associate professor of dairy cattle genetics at Penn State University.
The Lifetime Net Merit index (NM$) was introduced in 1994 with revisions made in 2000, 2003, 2006 and 2010. I think we can anticipate another revision to NM$ in the near future and there is some discussion of the formula taking a slightly different shape compared to previous versions.
Deriving an optimal economic selection goal is never a trivial task because we must project what economic conditions will be like in the future. Economic conditions in the dairy industry have changed since 2010. Feed costs, heifer values and milk prices have all shifted, and updates to NM$ are needed to help us make more economical selection decisions.
A second factor for updating the NM$ formula is that we have two new fertility traits and we would like to include them in our selection goal. We will discuss those traits later.
There is one more reason that makes the timing good . . . the genetic base is also scheduled to be updated in 2015. While a base change is not justification for NM$ revisions, it does make sense to implement changes at that time because we will be expecting and more mentally prepared for shifts in sire and cow evaluations.
An expanded structure
NM$ only included five traits when it came on the scene in 1994. Those were milk, protein and fat yield, productive life, and somatic cell score. We now have nine categories included in the index and can anticipate more. At some point, adding traits will result in an index that is unwieldy and it will become more difficult to conceptualize what the index is intended to accomplish. That consideration is leading to some discussion about whether a new structure for NM$ is warranted.
We have two new fertility measurements that we can be confident will be added to the index - CCR (cow conception rate) and HCR (heifer conception rate). Adding those would bring the total number of traits to 11. There are currently research efforts underway to develop genomic evaluations for traits such as feed efficiency, specialized reproductive traits and additional health considerations. The amount of data we collect on cows in a routine manner also continues to expand, so I think even more traits will be available to add to NM$ in the future.
Including new traits of economic importance as they are developed is certainly advisable and I think it can be done without making NM$ more difficult to interpret. Rather than listing each and every trait that we include in our selection goal as part of NM$, we can develop broader categories. All of the individual traits we consider then contribute to those broader categories.
Calving ability is an example of this type of approach. Calving ability contributes 5 percent of the weight in NM$ but is not a single trait. Sire calving ease, daughter calving ease, sire stillbirth and daughter stillbirth are the four components of calving ability.
Consider grouping traits
There are several possible broad categories that could be included in a restructured index. One potential category is female fertility. Rather than having three separate female fertility traits, DPR (daughter pregnancy rate), CCR and HCR could be merged into a single female fertility category. Any female fertility traits that were developed in the future could then simply be added to the calculation of that category.
A second logical category would be udder health. We currently consider udder health under the separate banners of udder composite and SCS (somatic cell score). Clinical mastitis evaluations may become available in the future and could be easily added to an udder health category if it was available.
A category dedicated to mobility or foot health is also possible. We currently include feet and legs composite in NM$. There is strong agreement that we need improved foot health and lower rates of lameness. However, it is not clear that selecting to alter foot and leg conformation will lower lameness and reduce foot health troubles. A more general mobility category would allow for the development and addition of new traits if they become available.
A more stable index
There are several advantages to including broad categories in place of specific traits in NM$. The stability of the main index would be greater. The weight applied to a given category may shift some over time, but the general structure of NM$ would undergo fewer changes. It would become easier to incorporate new traits and insights from research trials in a timely fashion without drastic changes to the general formula on a routine basis. It would be easier to communicate to dairy producers what direction the index is intended to move the population.
There are some disadvantages to moving toward broader category classes instead of including specific traits. We have to determine how a category is expressed. For example, a bull with a +1.0 for DPR indicates that we can expect his daughters to have a 1 percent higher pregnancy rate than a bull with a 0 for DPR. How we express the combined value of three fertility traits in NM$ would need to be determined by genetic specialists.
The second disadvantage is that it is not immediately clear how much weight a specific trait is given in the index. We know that calving ability is given a weight of 5 percent in NM$, but how much weight is placed specifically on DSB (daughter stillbirth)? We have to do a little digging to find out that DSB contributes 45 percent of the calving ability category for 2.25 percent of the overall weight in NM$.
One point that I want to make clear is that I am not recommending reducing the number of traits that are included on a bull's proof or reducing the amount of information available to those making selection decisions. Information on each trait will still be available. What we are discussing is simply the face of NM$ and communicating the effect that selecting for higher NM$ will have on a dairy producer's herd.
Expect to see some changes to NM$ in the next year. How the formula changes and how the formula is presented to dairy farmers remains to be determined. The change could be as simple as adding two new traits and applying different weights on existing traits, or we could see an even larger shift toward the development of categories rather than specific traits. What won't change is how we determine the amount of influence a trait has in our selection programs. The influence of any trait will still be driven by its economic importance.