In current genetic evaluations, we lump data together, nationally and internationally. It is combined into one data set where we carry out the various analyzes to arrive at genetic indexes for all animals. But is that combining correct? Are there, in fact, any genetics by environment interactions situations that need consideration when combining data? Should genetic evaluations be run separately for grazing herds compared to barn fed and housed herds?
What Does Cow Sense Tell Us?
Cow people know that there are some sire daughter groups and some cow families that perform differently when placed in different environments.
How often have you heard knowledgeable cow persons say – “He sires good useful barn cows but not enough show ring worthy daughters to have a PTAT of 3.21.” Or. “That cow family is great provided you go to the effort of pampering them like babies.”
Some Examples Where Proofs Have Not Always Told the Story
I have seen situations where sires’ daughters do not uniformly perform according to their indexes across all environments.
Quality Ultimate sired strength and stature as well as average milk and good fat percent, but he got the knock for not being tie stall friendly and lacking in daughter mobility in Canada, where he was proven. Yet in Australia breeders have told me that his mobility was not a problem. Why? Well, in Canada in tie stall barns with little to no access to exercise for 60% of the year, Ultimate daughters did not get the exercise they needed and so his proof was accurate, he had a feet and legs limitation. But, in Australia where cattle are outside walking on the ground all year, his daughter’s feet and legs were not a problem. (Read more: Mobility – The Achilles Heel of Every Breeding Program)
Looking beyond Ultimate, each of us can think of other bulls that may not suit all breeders’ needs. I think of Roybrook Starlite whose daughters were high yielders, but they often needed some special care and close monitoring. That is not something most commercial milk producers were prepared to do. Starlite’s maternal line had been a line bred family from a herd that took superb care of their animals.
Love Them or Hate Them
Today breeders either love or hate show bull Goldwyn and the commercial breeder’s dream bull, Oman. (Read more: Why Braedale Goldwyn Wasn’t a Great Sire of Sons)
A bull’s proof is an estimate of his average daughter. In extreme situations or environments, a bull’s proof may not be an accurate prediction of his true worth. How can breeders know if a bull will work, as his proof predicts, on their farm? Very little gets a breeder more upset that having a bull not perform in accordance with his proof.
Goldwyn in large commercially run groups of cows and Oman in the show ring are not good fits for what their proofs said should have ben expected.
Cow Indexes Open To More Environmental Influence
Of course, when it comes to cow indexes there are numerous examples of cows and cow families where the indexes are not accurate in predicting how they will breed on. (Read more: Has Genomics Knocked Out Hot House Herds?)
Now with genomic information included in genetic evaluations, the accuracies of prediction for cow indexes have been doubled and, therefore, may not be quite as variable in accuracy as they were in the past. Discerning breeders know that some cow families work best in certain single environments.
Points To Ponder
When conducting genetic evaluations, assumptions are made. Most of these assumptions have been shown to enhance the resulting genetic indexes. However here are a few assumptions that may contribute to inaccuracies when the indexes are used across all dairy farming situations.
- Including Only Partial Herd Data
Not including all contemporaries in type classification or herd recording data, when conducting BLUP genetic evaluations, violates the BLUP assumption that all animals are handled in a similar manner within a herd. Applying the results from selected data can lead to breeders questioning the daughters they get from a sire or cow family based on their genetic indexes. - Combining International Data Sets
Definition of traits, variances within the data and methods of farm operation are different country to country. Interbull includes data from many production environments from many countries when doing its index calculations. Breeders should carefully interpret the results of combined international indexes when applying them back to their own herd environment. - Multiple Breeding Programs Within A Herd
BLUP genetic evaluations assumes that only one breed program, one feeding program, and one management system exists in a single herd. If that assumption is violated then genetic evaluation results, especially cow indexes, can be less accurate than reported. - Sires Proven on Early Release Semen
Most breeding companies release their high genomic young sires to themselves or selected herds six to nine months before it is made available to all breeders. It is imperative that the genetic evaluation procedures used for evaluating early release sires accurately adjusts for the genetic merit of the sire’s mates and the herds where the daughters are found. - Cows and Technology
With many new technologies coming to market, breeders can expect to see genetic indexes for how cows adapt or perform within a technology. One such area is how cows work in single robotic milking farms. For example, breeders need to understand what is included when a bull’s daughters are called robot ready. Is that simply rear teat placement or does it include other factors as well (i.e. udder depth, milk let down, milking temperament, etc.)? - Genomic Information Not Yet Universal
Even though the global dairy cattle breeding industry is almost into the ninth year of using genomic information, the genomic information and method of including the genomic results in genetic evaluations are not universal country to country. Breeders using genomic indexes from other countries need to do their homework before buying semen or embryos from abroad.
Does This Topic Need Attention?
The short answer is YES. To constructively improve their dairy cattle, breeders need to trust the numbers they use when making breeding decisions. Differences, biases, and inaccuracies in the data must be accounted for when conducting genetic evaluations. As milk products become more of the global diet and as dairy cow populations expand, especially into more tropical conditions, breeders will need to know which cow families and sire daughter groups will work best in which environments.
The Bullvine Bottom Line
The genetic evaluations of tomorrow need to make sure that biases and inaccuracies are not created but rather eliminated when data sets are combined. The saying “Horses For Courses” comes to mind when considering bloodlines that will work better in one environment than another.
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