Archive for Genetic Evaluation System

Canadian Genomic Evaluations Without Published DGV

Unlike any other country, Direct Genomic Values (DGV) have been published in Canada for genotyped animals as part of its genomic evaluation system.  The intent of doing so was to provide producers and industry personnel a better insight into the “black box” of genomic evaluations when they were first introduced in 2009.  Ten years later, as of the December 2019 release, DGV will no longer be published or included in any outgoing data files associated with Canadian genetic evaluations.  Some breeders have expressed their disagreement with this decision and misunderstanding continues to be propagated.  This article provides further clarification regarding the decision to no longer publish DGV.

What Information Contributes to An Animal’s Genetic Evaluation?

After genomics was first introduced in Canada in 2009, Canadian Dairy Network (CDN) and industry partners launched an extensive education effort to help everyone better understand how the animal’s DNA analysis contributed to its genetic evaluation, resulting in the increased accuracy.  The information in Figure 1 was regularly used as part of this educational campaign.

Every young calf born in Canada and registered in the breed association herd book, whether it’s a heifer or bull, receives a Parent Average for each trait as its first official genetic evaluation, labelled as a PA. This estimate of its genetic potential is simply based on a formula that averages the genetic evaluation of its recorded parents.  In this sense, each animal’s pedigree serves as the first source of information for its genetic evaluation.

As a heifer calf ages and becomes a cow after first calving, her own performance data contributes to her genetic evaluation, labelled as an EBV (Estimated Breeding Value).  Performance data can include production data recorded through milk recording, classification data recorded by Holstein Canada and any other data that contributes to genetic evaluations for the various functional traits (i.e. health traits, fertility, longevity, etc.).  Including a cow’s own performance data to her genetic evaluation adds significant accuracy over and above the accuracy of its Parent Average from pedigree alone.  For cows that eventually have daughters old enough to have their own performance data, this also contributes to their genetic evaluation as a dam and further increases its accuracy.

For young bulls that enter A.I. and end up with many daughters with performance data, they end up reaching progeny proven status with an evaluation that is also labelled as an EBV.  While sires don’t have any of their own performance data included for dairy cattle traits, progeny proofs for sires end up with higher levels of accuracy (i.e.: Reliability) compared to cows, with their own data and with their daughter data, simply because of the volume of daughters that are included.

The significant difference that genomics has offered is the ability to genotype an animal at any stage of its life and have an analysis of its own DNA contribute to the estimate of its genetic potential. Doing so gives an increased accuracy of the resulting genetic evaluation with the greatest benefit occurring for young animals that otherwise would only have a Parent Average based on pedigree data alone.  In Figure 1, adding the contribution from the animal’s DNA is represented in red text and the resulting evaluation labels add the letter “G” to become either a GPA (for young animals) or a GEBV (for cows and progeny proven sires).

What is DGV and Why Stop Publication?

As shown in Figure 1, genotyping an animal means that an analysis of its DNA can contribute to the estimation of its genetic potential, which adds significant accuracy to that evaluation.  After introducing genomic evaluations in 2009, CDN coined the term “Direct Genomic Value”, or DGV, to represent this new source of contribution to genetic evaluations.  The terminology of Direct Genomic Value later became widespread around the world in the area of dairy cattle improvement.  The decision by CDN to publish DGV for each genotyped animal was simply to help everyone understand how genomics works.  The specific DGVs were not meant to be considered as an animal’s genetic evaluation and were never promoted to be used as a tool for selection or mating. 

Direct Genomic Values (DGV) are an intermediate step in the calculation of each animal’s most accurate genetic evaluation and serve as one of various sources of information that contribute to each animal’s estimate of genetic potential.

As an intermediate step in the process of estimating each animal’s most accurate genetic evaluation, it turns out that DGV are also not expressed on the same scale as the official evaluations of GPA.  The most elite animals of the breed have DGV that have a range that is higher than that for official GPA.  For this reason, it seems that various breeders and some A.I. organizations started to pay special attention to DGV and, on occasion, market their animals based on these higher values.

Once the Genetic Evaluation Board (GEB) of CDN, which includes breeders nominated by breed associations and other industry partners, announced its recommendation to the Board of Directors to no longer publish DGV, some of those breeders and A.I. companies that were marketing animals based on DGV made their opposition public and well known. As a consequence, senior staff at CDN and Holstein Canada met with some of the most vocal advocates of keeping DGV to listen to them and hear their perspectives on how DGV was important to their genetic selection and mating decisions.  Following extensive additional research into each of those perspectives presented to CDN and Holstein Canada, there remains no scientific evidence available that demonstrates that DGV provides any more information for good selection and mating decisions compared to using the official value of GPA.  It is based on this scientific evidence that the GEB and the Board of Directors of both CDN and Lactanet Canada have supported the direction to no longer publish Direct Genomic Values effective the December 2019 genetic evaluation release.

Since the initial research regarding the relative accuracy of Direct Genomic Values for selection decisions was openly presented in April 2018, there has much input from and consultation with producers as well as various breed associations, all of which was considered by the GEB when making the recommendation to no longer publish DGV as well as by the CDN and Lactanet Boards of Directors.

What About Transparency and Data Ownership?

The decision to no longer publish DGV does not reflect the position of CDN, or now Lactanet, as it relates to transparency of information and data ownership. The calculation of genetic and genomic evaluations is complex and uses advanced methods and models that involve several steps and sources of data contribution.  In addition to the contributions for domestic animals represented in Figure 1, there is also the use of data from international sources such as Interbull, CDCB in the United States and cow evaluations received from other countries. The genetic evaluation details on a trait by trait basis that are available via the former CDN web site, and the future Lactanet web site, are made available to help everyone understand the main traits presented on each animal’s Genetic Evaluation Summary page.

In terms of data ownership, Lactanet and other industry partners recognize that the raw data collected on dairy farms across the country belongs to the dairy producer.  Milk recording, classification, health recording, breeding data… all what is recorded and paid for by the producer belongs to them.  Even for genotyping, the use of the DNA sample provided by the producer, and the resulting genotype received from the laboratory, is treated seriously by Holstein Canada, CDN and now Lactanet Canada. The role and challenge of the various industry organizations is to take that raw data from the farm and transform it into valuable information for herd management decisions.  For genetic selection and mating decisions, the official genetic evaluation for genotyped animals, either GPA or GEBV, is the most accurate and valuable genetic decision tool, and not the intermediate value of DGV.

Author:                 Brian Van Doormaal, Chief Services Officer, Lactanet Canada

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CDCB changes to evaluation system (December 2019)

Updates to crossbred evaluations

By Ezequiel Nicolazzi (CDCB), George Wiggans (CDCB), Leigh Walton (CDCB) and Paul VanRaden (USDA-ARS-AGIL)

Two important updates will be implemented in the crossbred evaluations in December 2019:

Change in F1’s threshold for the breed of evaluation to be the breed of the ID: Since the introduction of crossbred evaluations in April 2019, Breed Base Representation (BBR) is instrumental in determining the breed of evaluation of all animals. Until now, for F1 animals, the breed code of the animal ID determined the breed of evaluation even if the BBR value is only the second highest value if the 2 highest BBR breeds are in the range of 45-55% and the second breed is less than 10% from the first breed.

Effective with the December 2019 evaluation, the simplified rule will maintain the breed of the ID if its BBR is higher than 40%. In that case an animal with HO ID, will maintain the HO breed of evaluation if its HO BBR is higher than 40%. This change currently impacts less than 500 animals in
the evaluation.

Change in calculation of reliabilities for crossbred animals: The calculations of reliability (REL) and the inbreeding of future progeny (EFI) rely on the relationship between the animal and the predictor population. Since crossbred animals do not have a predictor population for PTA (purebred SNP effects are blended in based on BBR values), their reliability and EFI estimates have previously been obtained using a multi-breed reference population. This strategy results in nearly 30% lower
reliabilities for animals with BBR<90 compared to animals with BBR>90. A further concern was that crossbred animals with stronger links to the reference population (e.g. BBR close to the 90 threshold)
receive similar reliabilities than animals having a mixed-breed genetic makeup (e.g. F1’s, or animals with contributions from more than 2 breeds).

Effective December 2019, following a full review of the methodology and results, the most connected purebred reference population of each crossbred animal (determined by the breed of evaluation used) will be used instead. In addition, a differential weighting of the traditional and genomic
components will be applied, by giving more weight on the traditional component for animals with traditional reliability above 30% (animals with phenotypes). These changes make it even more
important to emphasize that genomic evaluations on crossbred animals are useful for animals being bred to animals of the same breed of evaluation (e.g. going towards “purity”), whereas are not an advisable tool for animals in a rotational crossbreeding program.

As expected, no effect will be observed on purebred animals, whereas reliabilities and PTAs of crossbred animals will be impacted. (Note that reliabilities are used to weight the traditional and genomic components of an evaluation.) The greatest changes will be observed on animals with BBR
close to the 90% threshold, as their reliabilities will be the ones mostly changing (upwards) with this new strategy. Reliabilities will be more closely linked to the BBR distribution, as animals having more purebred composition will receive a reliability and PTA estimates similar (with differences in weighting, obviously) to a purebred animal. Considering that animals with BBR close to the 90% threshold have most of their SNP effects based on that same breed on which relationships are obtained from, this change makes reliability estimates more accurate.

Correction to use of foreign fertility evaluations

By Ezequiel Nicolazzi (CDCB), Leigh Walton (CDCB) and Paul VanRaden (USDA-ARS-AGIL)

When extending the MACE information to include Mastitis into the evaluation in August 2019, an incorrect trait order when comparing reliabilities caused MACE fertility evaluations to be used incorrectly for some bulls. This resulted in more differences between traditional and genomic evaluations than expected, which mainly affected highly-reliable Holstein bulls and animals related to them. Test results on the error repair indicate the divergence between traditional and genomic PTAs for these bulls should be resolved and is expected to result in slightly different genomic PTAs propagating throughout the population, due to better SNP estimates.

We thank Ryan Starkenburg (ABS) for identifying the misalignment and the industry review committees for providing feedback.


10 Years of Genomic Selection: What’s Next?

It was ten years ago, in August 2009, that genomic evaluations were first officially published in Canada.  This started with the Holstein breed but the same technology was later also applied in the Jersey, Ayrshire, Brown Swiss and Guernsey breeds. Let’s take a quick look at how genomics has changed dairy cattle selection, its impact on genetic improvement and contemplate what’s next on the horizon.

Bull Selection and Usage

Almost immediately when genomics was introduced, the A.I. companies around the world were seemingly forced to embrace it.  Given the intense competition between organizations, as soon as any had decided to aggressively use genomic selection, they needed to as well to stay in business. The science showed that genomics was not a “fade” and technology had advanced to a point where DNA could finally be used for genetic selection in dairy cattle.  The biggest advantage that genomics provided to A.I. companies, was the increased accuracy of genetic information available prior to making any bull purchasing decisions. Also, genomics allowed for the use of younger sires and dams as the parents of the next generation of young bulls, without much sacrifice in accuracy.  Together, this translated to an unprecedented annual rate of increase in the average genetic merit of young bulls entering A.I. throughout North America, which now exceeds 120 LPI points and $200 Pro$ per year.  With such a continuous year over year boost in the genetic makeup of genomic young sires offered through A.I. companies, these bulls now represent two-thirds of the total semen market share in Canada.

Increased Genetic Progress

A direct and very significant outcome of having genomic evaluations for the past ten years is the impact on the increased rate of genetic progress.  Figure 1 shows this impact very clearly since the steady rate of annual gain before genomics, which was 46 LPI points and $79 Pro$ per year, suddenly switched after 2009.  During the past five years, the average rate of genetic gain has increased by 2.2 fold, reaching 102 LPI points and $180 Pro$ annually. The dashed lines since 2009 in Figure 1 reflect the expected genetic progress that would have been achieved for both LPI and Pro$ in Canadian Holsteins if genomics had not been introduced.

Of equal, or perhaps even greater, importance than these realized gains for LPI and Pro$ is the impact that genomics has had on genetic progress achieved for individual traits as shown in Figure 2. The first key point to notice is that positive genetic gain is now being realized for all of the major production, conformation and functional traits in addition to Pro$,  LPI and its three components. Before genomics, in addition to losing ground for Daughter Fertility, Persistency, Milking Temperament and the Health & Fertility component of LPI, very little genetic progress was being made for other traits including Fat and Protein Deviations, Milking Speed, Daughter Calving Ability and Metabolic Disease Resistance. For all of the other eleven traits in Figure 2, the average rate of genetic gain realized with genomics has increased two-fold. The truly amazing outcome now known is that genomics provides an unprecedented opportunity to realize selection objectives for lower heritability traits even if they have negative genetic correlations with traits of moderate or higher heritability.

Figure 1: Rate of Genetic Progress Achieved in Canadian Holsteins With Genomics

Rate of genetic progress achieved in canadian Holsteins with genomics

Figure 2: Genetic Gain Achieved in Canadian Holstein During the Past 5 Years Compared to 5 Years Before the Introduction of Genomics

Genetic gain achieved in canadian Holstein during the past 5 years

Genotyping Adoption

Over the past ten years, over 3.2 million genotypes have now been accumulated in the genetic evaluation database at Lactanet.  This includes genotypes from animals all over the world, mainly the United States, since it was agreed at the onset that both countries would share all dairy cattle genotypes.  Figure 3 shows the evolution in the number of genotyped Canadian-born Holstein females since 2008. After an initial gradual growth period a level of plateau was seemingly reached during the years from 2015 to 2017. For various reasons, one of which was a 27% reduction in the cost of heifer genotyping in Canada, the adoption of female genotyping in Holsteins jumped to over 37,000 in 2018 and activity so far this year leads to a projected volume of 53,000 females for 2019. Figure 4 shows the similar information with genotyping adoption rates expressed in terms of the percentage of females registered by Holstein Canada by year of birth. This figure shows that the market penetration for heifer genotyping reached the 12% mark for registered Holsteins born in 2018.

Figure 3: Number of Canadian-Born Holstein Females Genotyped per Year

Number of canadian-born Holstein females genotyped per year

Figure 4: Adoption of Heifer Genotyping by Year of Birth for Registered Holsteins in Canada

Adoption of heifer genotyping by year of birth for registered Holsteins in Canada

A Crystal Ball

The implementation of genomic evaluations and the use of genomic selection have only just started to impact dairy cattle improvement strategies in Canada and globally. Given the experience with genomic selection over the past ten years, looking into a crystal ball towards the future, one can expect to see the following over the next ten years:

  • The introduction of a vast array of new traits of economic and social importance, most of which have not yet even been considered by dairy producers
  • Increased use of sexed semen, in-vitro fertilization and other advanced reproductive technologies, which also promote the increased use of beef semen to breed dairy cows
  • Use of DNA genotypes for improved selection strategies balancing genetic gain with maintenance of genetic diversity, including the use of genome-based mating programs
  • A significant restructuring and consolidation of the A.I. sector, leading to a handful of larger, multi-national breeding companies
  • Significant value-added benefits from DNA genotyping including automated parentage discovery and recording as well as traceability of dairy animals and food products

Needless to say, we are still at the tip of the iceberg when it comes to the impact that genomics and DNA genotypes will ultimately have on the dairy cattle industry.

Source: LactaNet

CDCB Changes in the Fertility Evaluations August 2019

Over the last couple of years, the noticeable seasonal fluctuation in trends in fertility traits has been difficult to understand. In particular, a large percentage of young bulls either increased or decreased, depending on the season of the triannual run (April, August, or December). It is no surprise that when bulls’ evaluations increase, it makes a lot of breeders happy. In contrast, when Predicted Transmitting Abilities decrease, many folks are disappointed. Understandably, producers hate to see bulls they’ve been using decline as it appears that their previous selection of service bulls was not optimum. These perceptions of the changes are unwarranted if it turns out the increases or decreases observed were due to shortcomings in the evaluations, i.e., changes occurred simply because the estimation procedures did not account for season appropriately. A key concern is that users may lose confidence in the usefulness of the results provided.

The good news is that after a complete revision of the fertility evaluations, which included several improvements over the last couple of years, the scientists at AGIL and CDCB have uncovered the reasons that caused seasonal fluctuations. The primary reason was that the seasonal grouping was derived previously from the heifers’ breeding dates instead of cows’ breeding dates. The less-than-exciting news is now that the issue has been discovered and rectified, there will be changes coming one more time, in the August 2019 run.

In order to understand the impact the revisions proposed (new seasonal grouping) would have on the stability of future evaluations, CDCB reran the past 4 evaluations using the revised seasonal groups. The results are shown below for daughter pregnancy rate (DPR) in Holstein. Trends from the same four runs were examined for cow conception rate (CCR) and heifer conception rate (HCR) as well, and also for Jerseys. Comparison of trends in the four official runs (Figure 1) and trends from improved seasonal grouping runs (Figure 2) gave reviewers’ confidence that this lingering problem is now resolved.

Figure 1:

Figure 2:

The results are extremely encouraging because almost all the seasonal variation disappeared when the model changes were applied. The seasonal variability observed in runs previously published (OFFICIAL) was gone in the test runs (TEST) using the revised procedure. These research runs give us confidence that the change introduced in the upcoming August 2019 evaluation will no longer produce the seasonal fluctuation experienced in the last couple of years. The actual changes in Predicted Transmitting Abilities (PTA) for the top 100 NM$ bulls in the previous evaluation are shown in Table 1 for 2 breeds.

     Table 1. Changes in PTAs in fertility traits of Holsteins and Jerseys between the April 2019 and August 2019 runs

Fertility trait Active AI Holstein bulls Genomic Holstein bulls Active AI    Jersey bulls Genomic   Jersey bulls
DPR -0.68 -0.99 -0.50 -0.61
CCR -1.71 -2.36 -1.63 -1.72
HCR -0.13 -0.47 -0.22 -0.33

There were a couple of other minor changes implemented that were obvious improvements that had little impact on the evaluations. For example, cow lactations initiated with an abortion were removed so they no longer biased Early First Calving (EFC). Abortions were previously entering that EFC calculation. Since the incidence of these cases was extremely low, the impact of this new edit is negligible on a population framework but could change EFC on single animals slightly.

In summary, the introduction of the new “stability package” will result in lower values for recent bulls, affecting most fertility traits. The table shows the changes for heifer conception rate (HCR), cow conception rate (CCR), and daughter pregnancy rate (DPR) that will be observed in the August run in comparison to the April 2019 evaluations. These changes will produce fertility evaluations that are considerably more accurate in future evaluations. We want to acknowledge the exceptional efforts of Paul VanRaden and Jana Hutchison for the research investigation to uncover causes of undesirable changes occurring and to Jay Megonigal for rerunning four consecutive test evaluations to confirm that improvements were incoming.


Genetic Evaluation Board (GEB) Executive Summary – February 2019

The Genetic Evaluation Board of CDN met on Wednesday, February 13, 2019 at the Holiday Inn in Guelph, Ontario following an Open Industry Session held the previous day. The following is a summary of the discussions and recommendations from the GEB, which will be considered by the Canadian Dairy Network (CDN) Board of Directors at its next meeting scheduled for March 7, 2019.

  • Brian Anderson from Athlone Farms was re-elected as Chairman of the Genetic Evaluation Board for 2019.
  • The GEB recommended that CDN proceed with the planned implementation of an updated Pro$ formula for the Holstein and Jersey breeds as well as the first introduction of Pro$ for Ayrshires, effective the April 2019 genetic evaluation release. Specific changes associated with the new Pro$ formula include:
    • Updated economic values for revenue based on current milk pricing across Canada.
    • Updated economic values on the expense side of the profit equation, which now include the cost of extra inseminations associated with poor reproduction as well as different daily maintenance costs based on each cow`s estimated relative body size
    • More accumulated cow lifetime profitability data since Pro$ was originally developed in2015.
    • A Pro$ formula for Jerseys based on cow lifetime profitability data specific to that breed.
  • In addition, the GEB recommended that CDN implement automated procedures to develop and introduce an updated Pro$ formula annually for each breed, including an annual update to the genetic base used to express published Pro$ values.
  • In conjunction with the update of the Pro$ formula, the GEB also recommended that CDN update the LPI formula in each breed, effective April 2019, based on the discussions held with the respective breed associations. Although all details of the updated LPI formula will be published separately by CDN, the key changes include:
    • For all breeds, an increased weight on fat such that it is at least equal to or greater than the weight on protein within the Production component, to reflect national changes in milk pricing in recent years
    • Changes to the Durability component in Holsteins by including Hoof Health alongside Feet & Legs as well as Rump
    • For Ayrshire, with the introduction of Pro$, the LPI formula will shift the relative emphasis on the three components to 46% Production, 32% Durability and 22% Health & Fertility, instead of the current 50:31:19, and also adjust the relative weights on the various traits within each of the three components
    • The Jersey LPI formula will increase emphasis on the Health & Fertility component relative to Production and Durability, and incorporate some adjustments within each of the three components including the removal of Dairy Strength from Durability
    • The LPI formula for the other coloured breeds will reflect current breed goals and the desired rate of genetic progress for key traits of importance
  • In terms of future plans for genetic and genomic evaluation services, the GEB discussed and supported the strategy outlined by CDN to develop and introduce evaluations for additional traits including cystic ovaries, metritis and retained placenta, with April 2020 as the target release date, as well as feed efficiency with a target date of August 2020.

    The GEB discussed results from the ongoing work at CDN to develop an improved genetic and genomic evaluation model for calving performance traits, namely calving ease and calf survival. Based on the most recent analyses conducted by CDN, the GEB supported the current direction of implementing a single step genomic evaluation system, with a possible implementation date of December 2019 or April 2020. Results from genomic validation testing and final recommendations associated with the new calving performance system will be presented at the next Open Industry Session in October 2019.

    Given the current direction of industry partners to introduce new DHI service options to allow for the remote collection of on-farm production data electronically, without visiting the farm, the GEB discussed how such data could ultimately be included for genetic evaluation. It is expected that the inclusion of milk weights on each data collection date can easily be incorporated into the current Test Day Model used by CDN for production traits. The use of fat and protein components analysis from in-line sensors may also be possible. When discussing how resulting cow evaluations would be published and labelled, the GEB recommended that CDN examine the possibility of making publicly available all cow evaluations based on their own production data, including such evaluations that may completely be based on unsupervised and/or non-verified data. This topic will be openly discussed with industry partners and presented at Open Industry Sessions in the future.

    Another topic discussed by the GEB that is of broad interest to Canadian producers, breeders and industry partners is the current and future emphasis placed on stature, especially in the Holstein breed. In general, the GEB supports the recent changes implemented by Holstein Canada related to the assessment of stature and how it contributes to Dairy Strength and consequently to overall Final Score for Conformation. While such changes have an immediate impact on classification results, the GEB recognizes that they take several years of classification data before impacting genetic evaluations. For this reason, the GEB recommended that CDN examine the possibility of moving to composite indexes for the calculation and publication of genetic evaluations for Conformation, Mammary System, Feet & Legs, Dairy Strength and Rump. An expected advantage of this approach is the establishment of composite indexes that reflect the desired direction of selection for traits of intermediate optimums such as Stature, Rear Legs Side View, Teat Length and others. To allow for broad industry discussion and input on this topic, CDN will include it on the agenda for the Open Industry Sessions planned for October 2019 and March/April 2020.

    CDN continues to be closely involved in the international effort to address the potential downward bias of progeny proven sires resulting from genomic pre-selection applied by A.I. organizations prior to purchasing genomic young sires. Given the complexity of this issue, any advancement in methods and models to account for this effect is expected to take time.

    Following an industry request, the GEB discussed the current policy implemented by CDCB in the United States associated with the availability to CDN of haplotype results for genotyped animals. As a consequence, the GEB recommended that CDN initiate further discussions with CDCB to find a solution such that CDN is able to provide haplotype results for all genotyped animals.

The next Open Industry Session is scheduled to take place on Wednesday, October 9, 2019 in St. Hyacinthe, Québec with the Genetic Evaluation Board meeting the following day.If there are any questions, concerns or comments regarding the recommendations of the Genetic Evaluation Board, as outlined in this summary, please feel free to contact committee members listed at or by contacting Brian Van Doormaal directly at Canadian Dairy Network


A Portrait of Genomic Young Bulls Marketed in Canada

There is no doubt that the arrival of genomics in Canada ten years ago has had a major impact on the entire dairy industry. It can be argued, however, that no segment of the industry has been more affected than the A.I. sector. In order to survive the competitive environment of that business, both nationally and internationally, A.I. companies needed to embrace and adapt to a new genetic selection scheme based on genomic selection. Canadian Dairy Network (CDN) recently looked at what has changed in terms of young bulls that were actively marketed to Canadian dairy producers in the years before the arrival of genomics (i.e.: 2004 to 2009) compared to those marketed in Canada more recently.

Figure 1 shows that the total number of young Holstein bulls with semen sold in Canada has not significantly changed since 2004, averaging 445.  That said, genomic evaluations make it easier for A.I. companies to market young bulls internationally, which means there are several more players offering genomic young bulls to Canadian producers.  Figure 1 also shows the increasing percentage of those bulls in A.I. that resulted from embryo transfer or manipulation such as embryo splitting, which now surpasses 90%.  This trend generally reflects the parallel increased adoption of new reproductive technologies such as in vitro fertilization (IVF). A reality of the new selection scheme based on genomics is the huge shift towards the use of young animals as parents of potential young bulls for entry into A.I.  This shift results from the significant gains in accuracy of genetic evaluations for young bulls and heifers due to genomics.

While the change towards the youngest parents possible and high selection intensity for A.I. purchases may be criticized by some, Figures 2 and 3 show the positive impact in terms of the average genetic merit of young Holstein bulls marketed in Canada since 2004 for LPI and Pro$, respectively. Prior to genomics, the average increase in LPI for young bulls with semen released between 2004 to 2009 was 84 points per year. For the most recent complete 5-year period from 2012 to 2017, this increased significantly to average 121 LPI points per year. For Pro$, these same averages were $142 and $206 annually, as shown in Figure 3.  This means that genomic young bulls released this year are expected to increase the average lifetime profit of their daughters by more than $200 compared to daughters of young bulls released a year earlier.

The race among A.I. companies to identify, purchase and offer to producers the highest genomic young bulls possible has also led to the adoption of strategies that put greater control in the hands of such companies. Essentially all leading A.I. organizations globally have implemented business plans that include the ownership of elite females, based on genomics, which serve as a primary source for producing the next generation of elite genomic young bulls.  In Canada, the five A.I. companies with the largest market shares all now have their own female multiplier herds and associated breeder prefixes including “Progenesis” for Semex Alliance, “S-S-I” for Select Sires, “Peak” for Alta Genetics, “Denovo” and “ABS” for ABS Global and “Co-op” for Genex/CRI.

The recent CDN analysis also examined the breeder prefix of the young Holstein bulls with semen released in Canada from 2004 to 2017. On average, there were over 220 breeder prefixes represented among those bulls with semen marketed in Canada.  Of these, two-thirds of the breeders provided only one bull during any given year and an average of 40 breeders were able to provide three or more bulls to A.I. that were marketed in Canada. In any given year, there were a handful of breeders that contributed at least 10 bulls that were offered in Canada. Figure 4 shows the trend in the percentage of young bulls marketed in Canada that were sourced from the ten most frequent prefixes within each year of semen release.  This proportion ranged between 19% and 28% for all years from 2004 to 2014 but has increased since then to 47.9% for genomic young bulls marketed in Canada in 2017.  This means that roughly half of all bulls entering A.I. for use by Canadian producers have been sourced from ten breeder prefixes. The main reason for this concentration of bulls sourced from fewer breeder prefixes is the introduction of female breeding programs by major A.I. companies in addition to contractual arrangements between A.I. organizations and specific breeders.


Genomic selection has significantly changed the design and structure of the typical genetic improvement scheme for dairy cattle.  Traditional young sire incentive programs have been replaced by strong demand for young sire semen to a point where it represents nearly 70% of the market share. The increased accuracy of evaluations for young males and heifers has moved sire selection schemes towards genomic testing for screening so that only the most elite are purchased for entry into A.I. In addition, the increased adoption of reproductive technologies such as IVF has significantly reduced the average age of the dams of young bull entries into A.I. The competitiveness of the A.I. sector globally has moved such global companies to strategies whereby they own their own females to have a greater control on sourcing the next generation of elite genomic young bulls.  In the end, this all translates to higher quality young sires offered to Canadian producers, which translates into faster rates of genetic progress for the breed.

Brian Van Doormaal, General Manager, CDN
Lynsay Beavers, Industry Liaison, CDN

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A Closer Look at Direct Genomic Values (DGV)

2019 will mark Canada’s 10th anniversary of the introduction of official genomic evaluations. When they were first introduced by Canadian Dairy Network (CDN) in August 2009 for Holsteins, there was much hesitation and questioning about whether the technology was real and useful or just hype. Today, we know the truth and, as a consequence, breeds with genomic evaluations have rapidly increased the rate of genetic progress for essentially all traits.

Basically, genomic selection added another source of data to the genetic evaluation systems at CDN.  In addition to performance data and pedigree information, DNA became a new source of data for each genotyped animal.  To improve the understanding of how this new source of data was being used to produce published genomic evaluations, CDN decided to make Direct Genomic Values (DGV) public.  In recent months, there has been much discussion about the intent of CDN to no longer publish DGV. The strong interest and passion of Canadian breeders was clearly heard. For this reason, the CDN Board decided to delay the implementation of the GEB recommendation to be effective December 2019. Let’s take a closer look at why CDN will be moving forward with this direction.

What is Genomic Parent Average (GPA)?

For genotyped animals, there are three main sources of information that contribute to its official genomic evaluation.  These include the animal’s Parent Average (PA), any performance data (i.e.: such as lactation, classification, mastitis, fertility, etc. data) recorded on the animal and/or its progeny, and the DGV estimated from the animal’s DNA.  For young bulls and heifers, since no performance data exists, they receive a Genomic Parent Average (GPA), which combines its PA and its DGV into the single official genomic evaluation published by CDN, as shown in Figure 1.

Figure 1: Combining Parent Average (PA) and Direct Genomic Value (DGV) into the Official Genomic Parent Average (GPA)

Scale Differences

Since PA is simply the average of the evaluations for the animal’s sire and dam, the range for PA can never be wider than it is for evaluations of bulls and cows old enough to be parents.  Looking at Conformation as an example, the highest active sire in A.I. currently has a rating of +20, while the highest proven sire is +16 and the highest breeding age female born in Canada is +18.  This means that it is impossible for Canadian-bred animals to have a PA higher than +19. Looking at DGV for Conformation, however, the highest bulls are at +22.  This higher scale for DGV attracts extra attention to these values for marketing purposes. However due to their different scales, DGV cannot be directly compared to GPA values.  Further, since GPA results from a blending of PA and DGV, the most elite animals of the breed will almost always have a DGV higher than GPA.

Animal Rankings

Even though the scales for GPA and DGV are not exactly the same, the rankings for top animals of greatest interest for selection are essentially identical. In fact, regardless of the trait looked at (i.e.: LPI, Pro$, Conformation, etc.), over 90% of the highest genomic bulls would be the same if ranked by GPA versus DGV.  In this sense, DGV does not help identify the most elite animals for selection and mating compared to using GPA alone.

Prediction of Future Genetic Evaluations

In discussion with some breeders, there was the impression that DGV helped to better identify those genomic young bulls that would end up with the highest proofs once their progeny were milk recorded and type classified. This was the basis for the initial analysis conducted by CDN geneticists earlier this year.  The most appropriate way to assess this question is to look at sires that currently have an official progeny proof and see whether their GPA or DGV four years ago, when they were a genomic young sire in A.I., best predicted their current results.  The results of the analysis were clear. While GPA is not a perfect predictor of a young bull’s future progeny proof, using DGV was consistently a poorer predictor.  This can be explained by the fact that DGVs tend to be higher than GPA for elite genomic young bulls so a higher degree of over prediction is expected compared to GPA.

The same question can also be asked for females.  Does DGV for genotyped heifers provide a better prediction than GPA of their future performance as a lactating cow in the herd? CDN conducted a specific analysis to examine this question within several herds.  In the end, there was no practical difference in the correlation between GPA or DGV for heifers with their resulting 305-day lactation yields and classification scores during first lactation.

Looking at the Difference of DGV Versus GPA

Another strategy used by some breeders when assessing high end genomic bulls for semen purchase decisions has been to look at the difference of DGV minus GPA. The belief here has been that preference should be given to select genomic bulls for which the superiority of DGV over GPA is the highest. The CDN analysis looked at this hypothesis by focussing on the Top 100 GPA LPI genomic bulls in 2013, all of which now have an official progeny proof in 2018. The 25 genomic bulls with the highest difference of DGV minus GPA were compared to the 25 bulls with the lowest DGV superiority and results are presented in Figure 2. The 25 bulls with the biggest difference had an average DGV LPI of 3190 and an average GPA LPI of 3027.  As expected, this difference was much less at only 60 LPI points (i.e.: 3075 minus 3015) for the other group of 25 genomic bulls in 2013. Once proven, however, it was the 25 bulls with DGV and GPA being closest together that ended up with the higher average LPI, at 2929 compared to 2827 for the 25 bulls with the biggest difference of DGV minus GPA. This overall result stemmed from the fact that the bulls with the biggest difference had significantly lower Parent Average (PA) for LPI at 2622 points, compared to 2773 for the bulls for which DGV and GPA were quite similar.

Figure 2: Comparison of Average LPI Values for Two Groups of Genomic Bulls Among Top 100 for GPA LPI Based on the Degree of Difference Between DGV and GPA

Breeding for the Next Generation of Extreme Animals

Breeders aiming to produce young bulls for potential entry into A.I. and/or elite females for marketing and embryo sales tend to have navigated to using DGV as an important sire selection tool. The goal from this strategy is to use genomic bulls with the highest DGV for any given trait to increase the chance of producing progeny that also have an extreme DGV in the breed. CDN recently designed and conducted an analysis to assess this strategy compared to using GPA for achieving the same objective.  The conclusion from this study was that DGV was not superior to GPA in terms of identifying extreme genomic sires that will have higher chances of producing extreme progeny. 

Path Forward

Based on all scientific analysis conducted, no evidence has been found to show that DGV provides any information for improved sire selection and/or mating decisions, compared to using the official GPA itself. Based on these results, the Genetic Evaluation Board (GEB) of CDN approved a recommendation to no longer publish DGV in the future.  In terms of implementation of this recommendation, the CDN Board of Directors decided to delay it until December 2019.  In the meantime, CDN will work with the various breed associations and A.I. organizations to prepare and deliver an industry-wide communication plan related to this direction.

Brian Van Doormaal, General Manager, CDN
Lynsay Beavers, Industry Liaison, CDN

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October 2018 Genetic Evaluation Board (GEB) Executive Summary

Canadian Dairy Network (CDN) held an Open Industry Session on Wednesday, October 24, 2018 at the St. Hyacinthe Congress Centre, which was followed, as usual, by a meeting of the Genetic Evaluation Board (GEB) the following day. The following is a summary of the discussions and recommendations resulting from that GEB meeting held the next day, which will be considered by the CDN Board of Directors for approval at its meeting on December 10, 2018.

  • Following a comprehensive presentation related to the publication of Direct Genomic Values (DGV) and a lengthy discussion period during the Open Industry Session, the GEB members continued discussions during its meeting the following day. A summary of those discussions has been circulated by CDN in a separate document and is available upon request. In the end, given the technical nature of the GEB mandate, as an advisory committee to the CDN Board of Directors, the GEB felt there was no science-based reason to change the direction of its original recommendation made last April for CDN to no longer publish DGV for any animals or make them available in any data files. Consideration of non-technical points on this topic and an implementation plan fall within the responsibility of the CDN Board of Directors.
  • The GEB discussed some final details associated with the transition of Somatic Cell Score expression to the Relative Breeding Value (RBV) scale used for all other functional traits, to be effective December 2018. As a consequence the GEB made the following recommendations:
    • That evaluations for the Mastitis Resistance (MR) index be labelled as official when the evaluation for Somatic Cell Score meets the minimum criteria for official status.
    • That CDN develop a Cow Genetic Evaluation Details page on its web site for providing genetic evaluations for traits with official status that do not otherwise appear on the animal’s Genetic Evaluation Summary page.
    • That CDN examine the use of single step methodology for calculating Clinical Mastitis genomic evaluations for possible implementation in the future. This approach is expected to increase the accuracy compared to current genomic evaluations and/or allow CDN to expand the availability of this trait to other breeds.
    • That CDN assess the current range of bull evaluations for Mastitis Resistance in the Ayrshire and Jersey breeds and consider making any required modifications given that these breeds do not have genomic evaluations for Clinical Mastitis, which is the case for Holstein.
  • Also effective December 2018 are official genetic and genomic evaluations for additional hoof health traits in Holsteins, over and above Digital Dermatitis that was introduced in December 2017. On this topic, the GEB made the following recommendations:
    • That Holstein breed evaluations for eight hoof lesions, namely Digital Dermatitis (DD), Interdigital Dermatitis (ID), Heel Horn Erosion (HHE), Sole Ulcer (SU), Toe Ulcer (TU), White Line Lesion (WL), Sole Hemorrhage (SH) and Interdigital Hyperplasia (IH), be added to the “Health” page linked to each sire’s Genetic Evaluation Details page.
    • That the proposed formula for combining evaluations for the eight lesions into a single Hoof Health (HH) index be approved for implementation by CDN.
  • That CDN continue its effort towards the development of a national strategy to have more hoof health data collected from herds across Canada with the aim of increasing the accuracy of genomic evaluations in Holsteins as well as expanding the availability of these traits to other breeds where possible.
  • Given the intent of CDN to introduce updated formula for Pro$ and LPI in April 2019, the GEB reviewed the results of analysis conducted to date and made the following recommendations:
    • Following discussions with Ayrshire Canada, the Pro$ index will be introduced in the Ayrshire breed in addition to the Holstein and Jersey breeds.
    • That that genetic base used for Pro$ be defined such that published values are easily comparable over time and the units of expression reflect the expected difference in daughter profitability in dollar terms.
    • That CDN continue the ongoing research effort to account for different maintenance costs according to a cow’s body size when developing the updated Pro$ formula. To achieve this goal in a sustainable manner for the longer term, the industry should develop a national strategy for collecting body weight data on a routine basis.
    • That the Hoof Health (HH) index to be introduced in December 2018 be added in April 2019 to the Durability component of the Holstein LPI formula, along with Feet & Legs, in an effort to improve both the resistance to hoof lesions as well as mobility.
  • That CDN continue the consultation process with breed associations to assess options of different LPI formula and present recommendations at the next Open Industry Session planned for February 2019.The GEB reviewed the results of work at CDN examining options for improving genetic and genomic evaluations for calving performance traits, namely calving ease and calf survival. Supporting the direction of this ongoing research effort, the GEB recommended the following:
    • That CDN verify that calvings resulting from reproductive technologies such as embryo transfer, where the dam giving birth to the calf is not the same as the genetic dam, be excluded from genetic evaluation calculations for calving performance.
    • Given that both Canada and United States are reviewing their current calving performance evaluation systems, that CDN and CDCB have technical discussions to improve the correlation of bull proofs for calving traits between the two countries.
    • With the increased accuracy from genomics to evaluate Direct Herd Life based on actual daughter survival data, the GEB discussed the value of continuing to also estimate an Indirect Herd Life evaluation based on a prediction formula that combines evaluations for several traits. After considering different options, the GEB recommended that CDN conduct an analysis to examine the impact of removing Indirect Herd Life as a predictor trait of daughter survival that is combined with Direct Herd Life to derive the officially published evaluations for Herd Life. Results of such an analysis will be presented at one or both of the Open Industry Sessions and GEB meetings to be held in 2019.
  • The GEB discussed two topics related to the registration status and/or purity level of Jersey
    animals displayed on the CDN web site, with the following recommendations:

    • That CDN implement an automated check based on pedigree information available for A.I. sires such that only sires whose daughters qualify for herdbook registration by Jersey Canada can be designated as having “Active” status for semen marketed in Canada.
    • In response to correspondence received from Jersey Canada, that CDN examine ways to increase the visibility of purity levels and/or Breed Base Representation (BBR) values calculated by CDCB, especially for genomic young sires and heifers.

The next Open Industry Session will be held on Tuesday, February 12, 2019 at the Holiday Inn in Guelph, Ontario, with the Genetic Evaluation Board meeting the following day.


Workability and calving ease data adds value to business decisions in Australia

Darren and Sharon Parrish use Australian Breeding Values (ABVs) for workability and calving ease to help run a productive and profitable dairy business and make better decisions on their farm at Bodalla, on the New South Wales south coast.

The ABVs help them identify bulls whose progeny are quick and relaxed milkers, while reducing the need for assisted calvings.

While these ABVs are on the check list for any bulls used in the herd, the Parrishs also record the traits within their own herd so they have a measure on how each heifer and cow performs and how their herd is tracking.

Their herd’s Workability and Calving Ease records also go back to DataGene and are essential in building reliability in the proofs of the bulls they have used, a process which underpins ABVs and the genetic evaluation system.

“We’ve been keeping detailed cow records for a long time – it’s something I really like doing because the information we collect gives us feedback on our cows,” Sharon said. “While it does involve a bit of extra work, the information you get back shows you what your cows are doing, the gains we are making and helps us make better decisions.” The Parrishs milk 200 registered Holsteins cows year round under their Darradale prefix.

The Parrishs have recorded workability traits for all 2-yearold heifers in their first lactation for more than 20 years. Workability covers three traits that reflect how easy a cow is to have in the herd: milking speed, temperament and likeability. The Workability ABV is included in each of the three indices – Balanced Performance Index (BPI), Health Weighted Index (HWI) and Type Weighted Index (TWI), with the highest weighting in the HWI.

“We’ve always recorded the workability traits for our heifers but our on farm software program makes it really straight forward,” Sharon said. “Once a heifer’s calving date is recorded in the system, 30 days later Easy Dairy will automatically flag that the heifer needs to be assessed for the workability traits. “We calve 50-60 heifers at a time twice a year, so we will have two batches a year that need to be recorded as they come through the shed.

“Once we have assessed the heifers for their milking speed, temperament and likeability, those records are automatically sent to our herd recording service, Dairy Express. “It might seem like extra work but we are really interested in our cows and we want to know who is slow or nervous as they are not the types of cows we want in the herd.”

Calving ease
The Calving Ease ABV is an indicator of how easily a bull’s progeny will be born – bulls with a calving ease ABV of 100 or more produce easier calvings. The calving ease score has a range of code options from a normal birth, assisted and the level of assistance required up to surgical assistance.

“Every time a calf is born we record the date, its dam, its size, sex, calving ease score and fate,” Sharon said.

“When we select bulls to use over the herd we look at calving ease because we want to minimise calving problems.

“Heifers that have unassisted calvings reach peak production faster and get back in calf sooner than heifers that need assistance. “Heifers which have assisted calving also involve extra labour and often incur veterinary costs.

“It’s expensive to breed and grow out a heifer to the point of calving so we want our heifers to calve unassisted and come into production strongly and then get back in calf and stay in the herd.”

Record keeping
Sharon said having systems in places to record data, meant collecting cow records became second nature and fitted in with other farm activities.

“You can set things up so recording data is quick and easy,” she said. “I don’t see it as extra work, but more of an investment – the more reliable our records are, the more reliable the information is that we get back on our herd.

“Our record keeping was originally on paper but we now use Easy Dairy, although we still keep a paper diary in the dairy which everyone can refer to and use.”

“I’ve also recently downloaded the HerdData app which should make it easier to record data such as matings on our lease block and also calvings out in the paddock because I will able to use my mobile phone. “We do most of the milking – when you are hands on with the herd it is certainly makes recording data easier.”

Better decisions
Sharon said recording Workability and Calving Ease data on farm had a two-fold benefit.

“Recording Workability and Calving Ease traits gives us information on our herd, while contributing data back on the bulls we have used, which improves the reliability of their ABVs. If we want bulls to have meaningful and accurate proofs then we need to supply figures on their daughters’ traits back through the herd tests companies to get accurate bull ABVs.

“The figures also mean we can see the genetic progress we are making in our herd because we have accurate, objective data on the cows in our herd.

“The end result is that we know what we are breeding and can use the data from our herd and the bulls we use to make faster genetic gain.”

The Parrishs recently received genotypes on their heifers as well as estimates of the difference between the low and high genetic merit animals in terms of their contribution to farm profit as a result of being a genetic focus farm for the ImProving Herds Project.


Source: DataGene

Genetic Evaluation Board (GEB) Update

Canadian Dairy Network (CDN) held an Open Industry Session on Wednesday, October 24, 2018 at the St. Hyacinthe Congress Centre, which was followed, as usual, by a meeting of the Genetic Evaluation Board (GEB) the following day. This communication specifically provides an update on the discussions regarding the publication of Direct Genomic Values (DGV) by CDN since it was a key topic discussed at length during the Open Industry Session. A complete executive summary including all actions and recommendations of the GEB will be circulated in the near future. The CDN Board of Directors will consider all such recommendations for approval at its meeting scheduled for Monday, December 10, 2018.

  • The Open Industry Session was well attended with over 80 participants, including many breeders as well as industry personnel. CDN extends a special appreciation to those breeders who took the time to attend this meeting and share their thoughts.
  • In advance of the meeting, CDN and Holstein Canada organized meetings and discussions with key advocates in favour of keeping the publication of Direct Genomic Values (DGV) to gain a better understanding of the various perspectives of Canadian breeders. As a result of these discussions, CDN conducted additional analysis to assess the potential benefits of DGV for breeders to make selection and mating decisions, compared to using the official Genomic Parent Averages (GPA) of young bulls and heifers.
  • In brief, the CDN presentation of analysis results included the following key conclusions:
    • The DGV scale for any trait, including LPI and Pro$, is wider than the scale for GPA, which means they are not directly comparable. It also means that the most elite animals in the breed will have DGV higher than GPA for marketing purposes.
    • The group of highest genomic young bulls available in A.I. are almost identical with similar rankings based on either DGV or GPA. The same is also true for the ranking of heifers in herds of breeders that have been involved for decades in herdbook registration, milk recording, type classification and the use of A.I. sires.
    • In terms of predicting the future progeny proof of genomic young bulls, the scale of GPA is more appropriate and more accurate than DGV.
    • When considering high ranking genomic young bulls, the strategy of giving preference to those bulls with the highest difference of DGV minus GPA is not effective for identifying the most promising sires once they are progeny proven. In fact, such an approach ends up selecting genomic young bulls that have an lower Parent Average.
    • In terms of using a herd’s heifer genomic evaluations to predict future lactation and/or classification performance as a cow, both GPA and DGV have equal levels of accuracy, both being superior to using Parent Average (PA) alone.
    • Another strategy used by some breeders when making sire selection decisions is to identify genomic young bulls with the highest, most extreme, DGV with the goal of producing progeny that also have extreme genomic evaluations. Such extreme young bulls and heifers are necessary for breed improvement and provide important
      opportunities for impacting rates of genetic progress. The CDN analysis conducted to assess the benefits of this approach showed that extreme genomic young bulls based on GPA produced a higher proportion of extreme progeny compared to results based on extreme DGV.
    • Based on the discussions and opinions expressed, there was general recognition among those in attendance that no scientific evidence has been found to indicate that DGV offers any benefit over GPA for making selection and mating decisions. Given this conclusion, it is clearly understood by all industry partners, especially CDN, breed associations and A.I. organizations, that a concerted and collaborative communication effort is required across the country to breeders, producers and industry personnel.
    • Regardless of the technical results from the CDN analysis, those in favour of maintaining the publication of DGV stated that doing so (a) maintains the current transparency of data available publicly; (b) attracts international breeders to the CDN web site, which helps to promote LPI globally; and (c) leaves the choice of whether to use and how to use DGV in the hands of each individual breeder.

After giving due consideration to all of the above and recognizing that the GEB is an advisory committee to the CDN Board of Directors with the mandate of making science-based recommendations, a motion was duly passed to maintain the direction of the previous GEB recommendation to no longer publish Direct Genomic Values (DGV) and to exclude such data from all outgoing files. GEB members consider the timing for any implementation of this action
is the responsibility of the CDN Board of Directors but it should not be any earlier than the stated target date of April 2019.

If there are any questions, concerns or comments regarding the above recommendation of the Genetic Evaluation Board, please feel free to contact CDN Board Chairman, Norm McNaughton (, GEB Chairman, Brian Anderson ( and/or CDN General Manager, Brian Van Doormaal (

Translating Somatic Cell Score Proofs into Daughter Performance

Starting in December 2018, proofs for Somatic Cell Score (SCS) will be expressed as Relative Breeding Values (RBV) in order to improve interpretation and be consistent with all other functional trait expression. On the RBV scale, bull proofs for SCS will be expressed using a value of 100 as breed average and a standard deviation of 5. The most extreme bulls vary from the most undesirable at around 85 to the most desirable at 115.

In general, daughters of bulls with a better than average RBV for SCS will produce milk with a lower Somatic Cell Count (SCC) than daughters of bulls with an RBV for SCS that is average or poorer. In order to help with interpretation of this important trait, Canadian Dairy Network (CDN) has conducted an analysis relating sire RBV for SCS to the average daughter performance for SCC.

Sire RBV and Expected Daughter Performance

Bull proofs for SCS are calculated using the Canadian Test Day Model and each bull receives a separate proof for first, second and third lactation. These three values are combined into a single published proof. The CDN analysis compared each bull’s combined SCS RBV to the average somatic cell count (SCC) of their daughters on test day. Since the average SCC is expected to be different across lactations, the relationship between RBV and average daughter performance was performed separately for first, second and third lactation.

Figure 1 shows the average daughter SCC in each lactation relative to their sire’s overall SCS proof, expressed as an RBV, which is a combination of his genetic potential for each of the three lactations. Although not all bulls have exactly the same relationship between proof and daughter average performance, the three solid lines in Figure 1 show the general relationship within each lactation. This graph clearly demonstrates the trend of higher somatic cell counts associated with each successive lactation.

The actual results in Figure 1 can also be used to establish a table to help translate sire proofs for SCS into the expected average SCC for future daughters. Table 1 provides the difference in average SCC for daughters in first, second or third lactation according to the published SCS RBV of their sire. In addition to being influenced by genetics, actual SCC levels are significantly impacted by herd management. For this reason, expression of expected daughter performance differences in Table 1 are all relative to how daughters of an average sire with an RBV of 100 would perform. In this manner, Table 1 applies to expected performance in all herds regardless of herd management levels. Considering a herd with an average SCC of 140,000 in first lactation cows as an example, future daughters of a bull with an SCS RBV of 105 should have an average first lactation SCC of approximately 113,000 (140,000-27,000).

In general, the higher the sire RBV for SCS, the lower the average daughter SCC across all lactations. Research has shown that SCC generally increases with each lactation. This occurs more drastically in daughters of sires with poor RBVs for SCS. In other words, the more undesirable the sire RBV for SCS, the greater the increase in average daughter SCC from one lactation to the next. For example, daughters of sires with an SCS RBV of 85 have an average increase of nearly 107,400 SCC (223,300-115,900) between first and third lactation, while daughters of sires with an SCS RBV of 115 increase only half that amount with an average of 54,000 SCC (122,600-68,600) between first and third lactation.

Correlations Between SCS and Other Key Traits

Table 2 shows proof correlations between SCS and selected key traits derived using data from >4,000 domestically proven Holstein bulls.

In general, most traits are positively correlated with SCS meaning selection will be favorable toward reducing SCC. In particular, SCS is positively correlated with production yields, Herd Life, Mammary System and both national indexes. Milking Speed is one exception, where the negative correlation indicates that the higher the RBV for Milking Speed, the less desirable (lower) the RBV for SCS. This means that strong selection to improve somatic cell counts would indirectly lead to an increased frequency of slower milking cows in the herd. Not surprisingly, Mastitis Resistance is highly correlated with SCS at 87%.  Since Mastitis Resistance is an index that combines both Somatic Cell Score and Clinical Mastitis, it should be the primary trait considered when making selection and mating decisions to reduce the incidence of mastitis.


SCS on an RBV scale will lead to consistency of expression and interpretation of all functional traits, as well as allow producers to more easily monitor proof changes. With herd average SCC levels as a starting point, RBV for SCS can be related to the expected average daughter performance for SCC. In general, the higher the sire RBV for SCS, the better (lower) the daughter performance for SCC. Also, poor RBV for SCS are associated with more dramatic SCC increases with each consecutive lactation in daughters. As a trait, SCS has favorable correlations with many important traits including moderate correlations with both national indexes, which means that with selection, simultaneous improvements are made for both.  For breeds with Mastitis Resistance available, using this trait is the optimal way to genetically improve your herd for resistance to both clinical and sub-clinical mastitis.

Lynsay Beavers, Industry Liaison Coordinator, CDN
Brian Van Doormaal, General Manager, CDN

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CDN Website Tips & Tricks: The Inbreeding Calculator

Many dairy producers are technologically savvy and seek out tools to help them better manage their herds. On the genetic front, the CDN website is one such tool, highly utilized by those keen on monitoring and querying genetic data. The inbreeding calculator, which provides inbreeding levels and Parent Averages (PA) for potential progeny from various matings, is one of the website’s most frequently used features. When looking to breed any given female, the inbreeding calculator can be accessed one of three ways:

  • From the “Calculators” drop down found in the grey left-hand sidebar of the CDN website.
  • From the “Inbreeding Calculator” link found above an Active List of females. An Active List of females can be generated by performing a Group Query, or you can target females with the same prefix, as covered in the example below.
  • By clicking on the “Inbreeding” tab displayed at the top of any page for the female of interest, which then pre-populates the Inbreeding Calculator with the female’s registration number.

Using the Inbreeding Calculator for Females with Your Prefix

In the first Tips & Tricks article of this series, readers learned how to enter their prefix in the Individual Animal Query to bring up a list of animals they have bred. Using the Selection Refinement Filter, results can be further reduced to only include active females by clicking the “Active Only” option.  

Using the prefix “Ste Odile” – the highest LPI herd in August 2018 as an example – here are the steps to use the inbreeding calculator with a list of females with a common prefix and a male of interest:

  • Select the Individual Animal Query.
  • In the “Search by Name” box, select “Holstein” and “Female” and type “Ste Odile” into the empty field. Submit the query and you will be brought to the resulting Active List of females.
  • To refine the list to only include Active females, select “Query Refinement Filter” and check the box next to “Active Only.” At this point you can also refine the female list by entering evaluation thresholds, as well as sort the list by a trait other than LPI by using the “Sort results by” dropdown at the bottom, if desired. Once you submit the Query Refinement Filter settings, you will be brought back to an updated Active List of females as seen below.

  • From here, choose the red “Inbreeding Calculator” link. By default, “Use the active list” will be selected in the “Select Female(s)” section, as seen below. Under “Select Male(s)”, choose “Individual” and fill in the registration number for a sire of interest. Remember to change the country if the bull in question has a country code other than Canada as part of their registration number. In this case, the #1 proven sire for LPI and Pro$, Mr Mogul Delta-1427-ET, was used. Hit “Continue” to see the Inbreeding Calculator Report.

The top of the report shows the sire information and his genetic evaluations for a select number of traits. Below is a list of all of the potential female mates ranked in order of LPI. Accompanying these potential mates are the inbreeding levels and parent averages for potential progeny for a given female mated to the selected sire, Delta. Select “Download results to Excel” to find and sort traits by parent averages for additional traits beyond those listed in the Inbreeding Calculator Report.

Breeders can use this report to help them select a mate for the animal of interest. The inbreeding percentage (%INB) should be used to eliminate potential mates that lead to a %INB deemed too high by the breeder. While comfort levels for %INB may vary, most A.I. mating programs set a default threshold of 9% to eliminate mating suggestions that lead to a %INB greater than this level. After eliminating potential mates based on %INB, the Parent Averages for the resulting progeny from each potential mate should be considered. Ultimately, the combination of the highest Parent Averages and an acceptable level of inbreeding should lead to the selection of the most desirable mate.

The example illustrated in the screenshot above allows the user to determine which female would be the best mate for the bull Delta. The tool can also be used to easily look at results for various potential sires by clicking the button “Select Top Sire Group”, as an alternative under “Select Male(s)” mentioned in point 4 above, and then selecting from among the bull names listed. A third possible way to use the inbreeding calculator is to enter the registration numbers for a given female and male, and examine the values on an individual mating basis.

In the previous two Tips & Tricks articles the Animal Query, the Group Query and the Selection Refinement Filter were covered.  These tools, in combination with the Inbreeding Calculator described in this article, put genetic information at your fingertips in order to help facilitate the breeding decision process.

Source: CDN

Net Merit $ Index Updated to Include Health Traits

With the August U.S. dairy genetic evaluations, Net Merit $ and the other lifetime profit indices have been revised to factor in disease resistance and to update the economic values used in calculations. Net Merit (NM$), Cheese Merit (CM$), Fluid Merit (FM$) and Grazing Merit (GM$) were revised for the triannual genetic evaluations released August 7 by the Council on Dairy Cattle Breeding (CDCB).

“It is exciting to incorporate these direct measures of disease resistance, so that Net Merit continues to evolve and provide the most relevant information for dairy producers as they work to breed and manage healthy, productive herds,” said João Dürr, CDCB chief executive officer.

In April 2018, evaluations for genetic resistance to six health disorders were launched by CDCB. For Holstein males and females, genetic and genomic evaluations then became available for six common and costly health events – Displaced Abomasum (DA), Hypocalcemia (MFEV), Ketosis (KETO), Mastitis (MAST), Metritis (METR) and Retained Placenta (RETP).

CDCB collaborates with the Animal Genomics and Improvement Laboratory (AGIL) to ensure that cutting-edge research is used to produce quality genetic evaluations. The research of AGIL, a division of the United States Department of Agriculture, was critical to establish appropriate economic values and weightings of the individual traits within the Net Merit index.

“Dairy producers can select for any combination of traits, but total genetic progress will be fastest using an index,” said Dr. Paul VanRaden, Research Geneticist at USDA AGIL. “Because many traits affect profitability, total profit usually increases when more traits are included in the selection index if the evaluations are accurate and correct economic values are used.”

Emphasis of Health Traits in Net Merit 

The six disease resistance traits were incorporated in NM$ through the new sub-index, Health Trait $ (HTH$), at a relative value of 2.3% for NM$, 1.9% for Cheese Merit (CM$), 2.3% for Fluid Merit (FM$) and 2.1% for Grazing Merit (GM$). The new Health Trait $ sub-index is not published separately, similar to the calving trait sub-index (CA$).

Relative emphasis on most other traits reduced slightly due to the addition of HTH$; however, yield trait emphasis increased slightly and somatic cell score (SCS) emphasis decreased greatly because of correlated health costs now assigned directly to HTH$.

“The actual benefits from adding health traits may not appear as large as some expect – because other traits such as productive life, SCS, fertility, livability and calving ease also directly or indirectly account for impacts on animal health,” stated VanRaden.

Additional Evaluation Changes

A handful of other changes were implemented by CDCB for the August evaluations, as part of the mission to apply current research and drive continuous improvement. These changes are described on the CDCB website. Most significantly, the model for female fertility traits was changed to address unexpected variability and heterosis procedures were updated to utilize exact Expected Future Inbreeding (EFI) as possible.

Access to Genetic Evaluations

The CDCB website includes a wealth of dairy genetic summaries, tables and lists, in addition to publicly-available queries on individual animals. The site is updated with lists for all sires, elite cows and heifers for Net Merit, and high-ranking grade cows and heifers, as well as comparative summaries. Further information will be available August 9 at 1 p.m. (EDT) to reflect the status of semen availability for sires in AI (artificial insemination). Additionally, the official CDCB evaluations will be published in various formats by breed associations, artificial insemination and genetic suppliers, dairy herd information (DHI), dairy magazines and other industry sources.

The next triannual evaluation will be December 4, 2018, and the 2019 release dates are April 2, August 13 and December 3. These triannual releases provide the genetic evaluations for individual animals used by dairy producers, genetic suppliers, breed associations and other dairy stakeholders.

CDCB changes to evaluation system (August 2018)

Health traits in Net Merit $

By Paul VanRaden, John Cole, and Kristen Parker Gaddis

The August 2018 NM$ update includes genetic evaluations for six new direct health traits first introduced in April 2018 for Holsteins: displaced abomasum, hypocalcemia (milk fever), ketosis, mastitis, metritis and retained placenta. In Net Merit, the disease resistance traits are grouped into a health sub-index (HTH$) that is not published separately, similar to the calving ability sub-index (CA$).

Economic values of the six new traits were obtained as averages of two recent research studies plus additional yield losses not fully accounted for in published genetic evaluations for yield traits. Some yield losses associated with health conditions are not fully accounted for when 305-day lactation records include adjusted test days coded as sick or abnormal. The added weight of HTH$ on NM$ will lead to nearly the same progress for HTH$ because NM$ has been accounting indirectly for health effects for a long time. Addition of these six new traits to the index is counteracted by removal of indirect health costs previously assigned to other traits such as somatic cell score and yield.

Additional NM$ updates include new economic values for each unit of predicted transmitting ability (PTA) and the relative economic values of traits. Full details of the changes are provided in an updated format that documents the other indexes:


Changes in fertility trait modeling

By Paul VanRaden and Jana Hutchison

Age-parity adjustment factors for daughter pregnancy rate (DPR) and cow conception rate (CCR) are revised for August to improve the stability of genetic trend estimates. During the April evaluation, recent genetic trends in traditional predicted transmitting ability (PTA) for DPR and CCR decreased when new age-parity groups were added by an automated process scheduled every five years. As a result, the fertility PTAs, NM$ and breed association indexes for recent animals declined by 1.7 DPR, 1.4 CCR and $22 NM$ in April.

Since 1995, age-parity effects for production have been estimated separately within five-year periods. Age and parity effects gradually changed across the decades, and more modern cows reached mature yield sooner (Norman et al., 1995). Different age-parity groups within each five-year period helped pass Interbull trend validation and had large effects on estimated genetic trend. These adjustments performed well for production, so were also used for SCS and fertility traits. However, because time groups are based on fresh dates, when the latest fertility group was formed, the least fertile daughters were partitioned into the new group whereas the most fertile daughters remained in the earlier group. To prevent abrupt changes in the future when new time groups are formed, the five-year groups are now redefined to instead gradually slide forward every four months. The April fertility PTAs were recomputed with this revised model, and for young animals the resulting trend returned about 60% of the way toward the December trend rather than maintaining the lower April trend . The age-parity definition change had a downward effect on the trend for older animals. The preliminary results in August indicate the trend for young animals is closer to December results in most breeds for DPR and CCR. As a general indication (since calculations are still ongoing), PTAs for recent birth years that had decreased in April are expected to be closer to the December values in August. In all cases, within-year rankings of animals were affected only a little.

Norman, H.D., Meinert, T.R., Schutz, M.M., and Wright, J.R. Age and seasonal effects on Holstein yield for four regions of the United States over time. J. Dairy Sci. 78(8):1855–1861. 1995.


EFI update and changing of heterosis procedure on genomic evaluations

by Ezequiel Nicolazzi, Gary Fok, Leigh Walton, Jay Megonigal and Paul VanRaden

Expected future inbreeding (EFI) is included in PTAs, but approximate adjustments were used in the all- breed weekly and monthly files after the April release until early May. Exact EFI is now used if both parents were in the pedigree file from the previous full run, and an approximate EFI is used only for new animals whose parents are also new since the last full release. Approximate methods were needed because reprocessing inbreeding for all 78 million animals takes nearly a day and is done only three times per year. Effective with the August 2018 genomic run, calculation of heterosis – previously reprocessed for all animals three times a year – will now be run on a monthly basis.

In light of the growing importance of heterosis and inbreeding values in the all-breed system introduced in April 2018, this critical change to the monthly processing – which required an extensive review – will better account for animals changing pedigree, especially those with changes of breed in their pedigrees (including own breed). Such enhanced procedure will also run during triannual genomic runs, so that all 78 million animals will undergo the procedure two times. The first heterosis run will be used exclusively for the traditional evaluation, and a second run will be used for the genomic evaluation and for reporting of final results. In the rare cases where progeny tested animals change pedigree, they could receive traditional and genomic PTAs with misaligned heterosis. However, the decision was to report PTAs reflecting the most current information available.


Exclusion of IDs from Interbull pedigree

by Jay Megonigal and Ezequiel Nicolazzi

Interbull pedigrees include dismissed IDs and non-standard IDs for some animals. For several years AGIL and CDCB have accepted these IDs as a way to track the past animal IDs. However, recently we discovered that such practice might create a misalignment that can cause old bulls to be submitted to Interbull with incorrect IDs. For August 2018 onwards, bulls with dismissed IDs (labeled as “X”) or that contain “_IMAG_” in their numeric IDs in the Interbull pedigree are now immediately excluded from the CDCB system.


Genomic mating file in HO – full implementation of rules

by Leigh Walton and George Wiggans

With the objective of reducing the dimension of the G-mating inbreeding file, and after discussions with National Association of Animal Breeders (NAAB) and two of its committee chairmen, an editing criteria was applied to females in the genomic mating inbreeding file in August 2017. The new criteria would include genotyped females with a usable genotype if any of the following conditions are met:

  1. The last processing date received from the DRPC is within the past six months and the termination code does not indicate that they are dead.
  2. If the DRPC does not indicate they are dead, they have a progeny born in the last 18 months.
  3. If the DRPC does not indicate they are dead, they were born in the last five years.

These rules were intended to limit the growth of the file by eliminating cows that are not on DHI and are over five years old without progeny in the pedigree table, therefore not of interest for the industry. Applying these restrictions, the file included less than 800,000 animals from the nearly 1.3 million genotyped Holstein females.

After reviewing files distributed in April 2018, CDCB discovered the above criteria was not implemented in full as originally intended. The August 2018 inbreeding file and those in subsequent runs will contain such definition applied in full.


Changes in content of Format 38

No new changes in the formats were introduced, but a number of changes were introduced in the routine programs that generate format 38. All special characters are now routinely excluded from the file; sampling status, average standardized milk (protein) and DYD milk (protein) fields are now blanked. Daughter averages are not shown for traits with less than 10 daughters. As per the industry request, the strategy implemented in April 2018 of publishing daughter/herd information for all traits irrespective of the number of daughters available was reversed. Starting the August 2018, daughter/herd information for all traits, except HCR and GL (as data arrives before milk data), will be blanked for bulls having less than 10 daughters on milk yield.


Change in Jersey elite cow criteria

by Jay Megonigal and Ezequiel Nicolazzi
The elite cow criteria was edited to include the current registry code practices of the American Jersey Cattle Association (AJCA). The association’s current practice is to use numeric registry codes (01 to 06, indicating generation count number) and HR (Herd Register; animals with such status have seven or more unbroken generations of known Jersey ancestors recorded by AJCA). Such criteria was first implemented in March 2017, but never adopted on the elite cow criteria. In collaboration with AJCA, CDCB has modified the JE elite cow criteria to include cows having a numeric registry code greater than 02, or HR. The modification is in effect starting August 2018.


Guernsey phantom group reinstated

by Jana Hutchison, Jay Megonigal and Paul Vanraden.

The exception encountered in April 2018 involving the program that created the unknown parent groups (UPG) for the breeds during the traditional evaluation was edited, in order to allow the creation of the Guernsey UPG irrespectively of their low number of unknown parents in the last 15 years. All genomic breeds will receive their own UPG as was originally intended.

CDN Website Tips & Tricks: The Group Query

Many dairy producers are technologically savvy and seek out tools to help them better manage their herds. On the genetic front, the CDN website is one such tool, highly utilized by those keen on monitoring and querying genetic data. There are two ways to query animals on the CDN website: individually and by group. This article will cover tips and tricks for using the Group Query, while the previous article described the best ways to use the Individual Animal Query.

Group Query

There are two parts to the Group Query: the Quick Search, seen below, and the Advanced Search. Quick Search is used to easily query top male and Canadian-owned females for each breed simply by selecting the breed from the drop down list and then either Male or Female.  If desired, you can also use the list of countries provided to select animals born in any specific country of interest. You can also select specific groups of animals based on their Evaluation Type whereby EBV refers to sires with a domestic progeny proof or cows with Canadian lactation and classification data included, MACE refers to foreign animals with a MACE evaluation provided through Interbull, and PA refers to animals with a Parent Average for production and/or type traits. The search can also be narrowed to include only genotyped animals and/or only animals considered to be active in Canada.

The Advanced Search, on the other hand, includes the same options as the Quick Search but can be used to return more specific query results for top male and female lists for each breed. It can be used to limit the query to only return animals with certain recessive and/or haplotype carrier results, from certain A.I. Controllers (males), from specified parents and/or born within defined date ranges.

Recessives and Haplotypes

Users of the Advanced Search can limit output results by the following recessive or haplotype carrier results:

  • Coat Colour – for Holstein males and females
  • Beta Casein – for Holstein, Jersey, Ayrshire, Brown Swiss and Guernsey bulls with a known Beta Casein test result submitted to CDN
  • Polled – for all breeds and both sexes
  • Brachyspina – for Holstein males and females
  • Haplotypes – Haplotypes affecting fertility including Holstein (HH1, HH2, HH3, HH4, HH5), Jersey (JH1 and JH2), Ayrshire (AH1 and AH2) and Brown Swiss (BH1 and BH2) males, as well as the Haplotype affecting Cholesterol Deficiency (HCD) in Holstein

A.I. Controllers

Using this filter, the query will return results including sires from only selected A.I. companies. There are nearly 20 A.I. companies listed that are members of CDN, which includes both major international companies as well as organizations unique to Canada. One or multiple A.I. companies can be selected, while the default is to display sires from all companies.


When querying females, results can be limited by province, which is usually determined based on the province associated with a DHI herd number. Females that are not part of a herd enrolled on DHI are included in the group identified as “Unknown – Canadian Owned”.

Checking the “Non-Canadian” field will include foreign females in query results but, by default, the CDN queries only include Canadian-owned females.


Both Females and Males of a certain parentage can be targeted in the Advanced Search. For example, perhaps the user would like to see if daughters of a certain sire are on the ground, or  search for sons of a certain dam x sire combination. Both of these example searches can be accomplished by using the parentage section of the Advanced Search. The appropriate fields for this selection are automatically filled in when you select “Group Query” at the top of the page when viewing the Progeny list of any given animal, as shown below using Comestar Lautrust as an example.

Date of Birth

Use this final part of the Advanced Search when targeting males or females born after or within a certain date range. This feature can be used on its own or in conjunction with any of the other search tools.

Putting it all Together

The true power of the Advanced Query tool is revealed when refining a search for either males or females using various combinations of the options described above. Looking to query genomic young sires from a particular A.I. company that are A2A2? Wanting to limit search results to only include red carrier sires free of HCD? Hoping to find out where your polled female out of a given sire ranks in the world? The Advanced Query can do all these things and more! Try it out and discover the hidden power of this popular feature of the CDN website.

Lynsay Beavers, Industry Liaison Coordinator, CDN
Brian Van Doormaal, General Manager, CDN

Download a PDF copy of this article

Source: CDN

New Expression for Somatic Cell Score Evaluations in Canada

Dairy producers are highly aware of the importance of good udder health on milk quality, animal health and the general profitability of the dairy herd. For decades now, milk recording services in Canada have included the analysis of milk samples for somatic cell count and this same data has been used to provide Somatic Cell Score (SCS) genetic evaluations for bulls and cows in all dairy breeds. In October 2017, the Genetic Evaluation Board (GEB) of Canadian Dairy Network (CDN) recommended that the expression of SCS genetic evaluations be changed to be consistent with all other functional traits.  Following approval of this recommendation by the CDN Board of Directors, an implementation plan has been established with an effective date of December 2018. Let’s take a closer look at the background and reasoning of this decision.

Genetic Selection for Improved Udder Health

In the 1990s, an overall Udder Health index was developed by Canadian researchers, which included Somatic Cell Score, Udder Depth and Milking Speed, for breeders and A.I. companies to make genetic selection decisions in this area. In August 2001, due to the increasing interest in genetic selection to improve udder health, these three traits were directly included in the LPI formula. In 2007, the dairy industry implemented a data collection system for health events recorded by producers enrolled on DHI and/or via the DSA program in Quebec. As a consequence, CDN later introduced official genetic evaluations for clinical mastitis as well as a Mastitis Resistance index for Holstein, Ayrshire and Jersey breeds in August 2014. One year later, modifications to the LPI formula for these three breeds included the addition of Mastitis Resistance as the optimized genetic selection index for improved udder health to replace Somatic Cell Score, Udder Depth and Milking Speed. At the same time, Pro$ was introduced as the new profit-based genetic selection index, which has a 40% correlation with Mastitis Resistance.

Availability of the Mastitis Resistance (MR) index provides producers with the opportunity to make genetic improvement to reduce the frequency of both clinical and subclinical mastitis in the herd.  Somatic cell count is a indicator of subclinical mastitis while clinical mastitis has a bigger negative impact on cow and herd profitability.

Proof Expression

In January 2008, the expression of genetic evaluations for all functional traits, with the exception of SCS, was changed to a Relative Breeding Value (RBV) scale with an average of 100 and a standard deviation of 5.  In general, this means that 99% of all bulls within each breed fall between 85 (poorest) and 115 (best), as presented in Figure 1.

  • There are multiple reasons for the adoption of an RBV scale for functional traits but the key advantages include:
  • The RBV scale is almost identical to the scale used over several decades for conformation traits, with the only difference being an average value of 100 for RBVs instead of 0 for type.
  • The use of a consistent scale across all functional traits facilitates the understanding of how each bull ranks within the breed.
  • The evaluations for all traits can be expressed in a common direction with the highest RBVs being most desirable.

Figure 1: Distribution of Bull Proofs as RBVs for Functional Traits

At the time when the RBV scale was introduced for all other functional traits, it was decided to exclude SCS in fear that it would create confusion at a time when producer interest in this trait was growing. Now, after ten years of using the RBV scale for many traits, it has been decided to move SCS to this scale as well. Some of the key reasons for this CDN decision include:

  • The current scale for SCS, with an average of 3.00 and an approximate range from 2.25 to 3.75, is not well understood by producers other than the fact that values below the average are most desired.
  • SCS is currently the only trait for which lower values are preferred so changing to the RBV scale allows the expression to become consistent across all functional traits, both in terms of range and direction of published values.
  • Only three other countries involved in Interbull evaluations express SCS evaluations in the same manner as the current scale used in Canada.  These include Belgium, Slovakia and United States but, in reality, the scale used in the United States has about half the range (PTA) as the current scale in Canada (EBV). Such a scale difference between Canada and United States is not well known and therefore leads to misinterpretation when comparing evaluations from both countries.

Implementation Plan

There are several details associated with the implementation of this change, which explains the significant lead time before implementation in December 2018. The CDN web site will be modified starting the genetic evaluation release in August 2018 by removing Somatic Cell Score as a trait listed in the section of Functional traits on the Genetic Evaluation Summary page for all animals in the Holstein, Ayrshire and Jersey breeds. Focus should be shifted towards the Mastitis Resistance evaluations already available in this section. For bulls in these three breeds, evaluation details for Somatic Cell Score will continue to be available under the “Health” tab. For genetic evaluation data files provided by CDN for both bulls and cows, there will be no specific changes to the file formats and test files with SCS populated with RBV values can be requested from CDN. The Holstein, Ayrshire and Jersey breed associations will implement modifications to their respective web site queries, as well as official pedigrees and other official documents in advance of the December 2018 implementation. Similarly, prior to implementation, computerized mating programs offered by A.I. companies in Canada will require some modification to incorporate the new scale of expression and interpretation for Somatic Cell Score.


Provided by: Canadian Dairy Network

Net merit as a measure of lifetime profit: 2018 revision

The lifetime net merit (NM$) index ranks dairy animals based on their combined genetic merit for economically important traits. Indexes are updated periodically to include new traits and to reflect prices expected in the next few years. The August 2018 update of NM$ includes genetic evaluations for 6 new health traits recorded by producers: clinical mastitis (MAST), ketosis (KETO), retained placenta (REPL), metritis (METR), displaced abomasum (DA), and milk fever (MFEV; hypocalcemia). Cows with genes that keep them healthy are more profitable than cows with health conditions that require extra farm labor, veterinary treatment, and medicine.

Economic values of the 6 new traits were obtained as averages of 2 recent research studies plus additional yield losses not fully accounted for in published genetic evaluations for yield traits. Liang et al. (2017) estimated direct treatment, labor, and discarded milk costs for health disorders from veterinary and producer survey responses, and Donnelly (2017) obtained health treatment costs from 8 cooperating herds in Minnesota. Some yield losses associated with health conditions are not fully accounted for when 305-day lactation records include adjusted test days that are coded as sick or abnormal. Total costs for the 6 traits are added to NM$ in the form of a health trait subindex (HTH$) that is not published separately. This is similar to the calving trait subindex (CA$) that combines 4 traits and is not published or to conformation traits, which are grouped into an udder composite, feet and leg composite, and body weight composite (BWC).

Relative emphasis on most other traits was slightly less because of the addition of HTH$. However, yield trait emphasis increased slightly and somatic cell score (SCS) emphasis decreased greatly because correlated health costs previously assigned indirectly to yield and SCS are now assigned directly to HTH$. Other economic values were updated very little. The 6 health traits are currently evaluated only for Holsteins. The 2018 and 2017 NM$ (VanRaden, 2017) indexes were correlated by 0.994 for recent Holstein bulls.

To read the full report, visit the USDA AIPL website HERE.

Genetic Evaluation Changes Announced by CDBC

Information about the upcoming genetic evaluation changes for April 2018 has been released by the CDBC (Council for Dairy Cattle Breeding). Changes will include evaluations for resistance to six health traits, the all-breed system now being applied to genomic evaluations, and a correction in productive life. 

New health evaluations for Holsteins officially released

by Kristen Gaddis, Jay Megonigal, Leigh Walton, Duane Norman, John Cole, Paul VanRaden

Official genetic and genomic evaluations for resistance to six health events in Holsteins (Hypocalcemia, Displaced abomasum, Ketosis, Mastitis, Metritis, Retained placenta) will be first published in April 2018. These traits are six of the most common and costly health events impacting dairy herds. Preliminary results and test files were shared to the industry in December 2017. Positive predicted transmitting abilities (PTAs) measure resistance to these health disorders. For example, a mastitis PTA of +3 indicates that 3% fewer daughters will get mastitis during each lactation. Data from herds all over the country are included in April. Further research is ongoing to: i) extend health evaluations to other breeds; ii) further improve the evaluation model; iii) include these results in the international exchange of evaluations; iv) increase data consistency and sources. Please note that since this is the very first release of this new evaluation, reliabilities are expected to be lower than in the future, when more and more records will be included in the database. These traits are not yet included in the lifetime net merit (NM$) formula. For further information please refer to the content/uploads/2017/09/CDCB-Health-Traits-FAQs-10_2017.pdf


All-breed system extended to genomic evaluations

By Paul VanRaden, Gary Fok, Mel Tooker, Lillian Bacheller, Jay Megonigal, Leigh Walton 

The all-breed system used for traditional evaluations since 2007 is now also applied for genomic evaluations starting April 2018. This new system allows records from animals of all breeds to be analyzed together and expressed on the same scale. Relatives, regardless of breed composition, will now contribute to every animal’s parent average and its genomic evaluation. Previously, animals with pedigrees including ancestors of a different breed were not correctly accounting for the “out of breed” contribution (a generic unknown parent group was assigned, instead of using the full pedigree). Genomic evaluations are now calculated on an all-breed base and then are converted to within-breed genetic bases for release to the dairy industry. It is important to underline that crossbred animals will still not receive an evaluation. Genomic evaluations for purebreds will be slightly impacted (except for the revised PL calculations, see next topic), whereas a greater impact will be seen in animals with pedigrees containing ancestors from other breeds.


Productive Life (PL) correction

By Paul VanRaden, Gary Fok, Mel Tooker

The multiple-trait Productive Life (PL) processing for incoming Interbull data has been completely revised to prevent the emergency actions taken in April and August 2017. The new system no longer tries to forward the differences between single and multiple-trait PL from one generation to the next. This logic tended to inflate the resulting evaluation, affecting primarily foreign bulls. Since foreign bull evaluations were inflated, SNP effects used to estimate genomic evaluations were affected, extending the inflation to the general population (e.g., including domestic animals). The inflation was more evident in breeds dominated by foreign bulls, such as Ayshire and Brown Swiss, but outlier cases were observed in all breeds. The new multi-trait PL genomic model prevents this from happening. The evaluations obtained with the new system fit better to the Interbull evaluations for foreign bulls, as a result, reducing the inflation of SNP effects. To give an indication of the impact, the 1712 PL evaluation with the new methodology yielded an average (standard deviation) reduction in PL PTA from 6.10(2.46) to 4.21(1.66) for elite cows. Although averages in bulls remain fairly similar (-0.28 vs -0.34 for official and all-breed, respectively), standard deviations are lower (3.87 vs. 3.1) and the correlation between both systems is 96%, indicating some degree of variation for bulls.

Genetic indexes: can one size fit all?

Indexes are important genetic selection tools. They combine all significant genetic traits into one package – and get producers away from setting minimum criteria for specific traits. That allows you to focus on creating a next generation of cows that are the right fit for your environment.

A global industry standard index like TPI has certainly helped dairy producers improve their herds. The one-size-fits all TPI index places 46% of the total weight on production traits, 28% on health and fertility traits and 26% on conformation traits.

However, an index like this assumes all farms face the same challenges within their herd. It assumes everyone has the same farm goals and milk markets. It simply serves as a general overview for a one-size-fits-all genetic plan.

Consider your goals

When you set your own, customized genetic plan, you can divide the weights as you see fit. To decide which production, health or conformation traits to include, consider your farm’s situation and future goals. How are you paid for milk? In a fluid milk market, you’ll likely put more emphasis on pounds of milk as compared to those who ship milk to a cheese plant. Are you expanding or at a stable herd size? If you’re looking to grow from within to expand your herd, you’ll want to put more emphasis on Productive Life and high fertility sires than the producers who are at a static herd size and able to cull voluntarily.

Your farm’s scenario is unique. With different goals, environments and situations, it’s evident there is no such thing as a one-size-fits-all index.

Make progress where it matters

Just 42 TPI points separate the 100th and 200th ranked genomic bulls on Holstein USA’s December 2017 Top 200 TPI list. Does a separation that small mean these bulls offer similar genetic benefits? Of course not!

To illustrate why, let’s compare three different genetic plan scenarios. One focuses on high production, one on high health, the other on high conformation. The tables below show the sires, traits and genetic averages for the top five Alta sires that meet each customized genetic plan. Notice the extreme amount of progress, and also the opportunity cost for using each particular index.

When high production is the goal, your genetic plan may be set with weights of 70% on production, 15% on health, and 15% on conformation. A team of bulls fitting that plan averages 2400 pounds PTAM and 171 pounds of combined fat and protein.


How to Understand Bull Proofs

Let’s face it; sometimes understanding bull proofs can be like reading a document in a foreign language.  With all the letters, numbers and acronyms on a proof sheet, it is enough to confuse even the most passionate dairy breeder. With the Bullvine has developed this cheat sheet to help you understand North American Genetic Evaluations easier.

Selection Indexes

Most genetic selection indexes are set by national organizations or breed associations. Genetic indexes help dairy producers focus on a total approach to genetic improvement, rather than limiting progress by single trait selection. It is important to remember that every farm is unique, with different management environments and situations and goals. With that in mind, it is important to understand what traits are included in each industry standard index. When you know what’s involved, you can more efficiently evaluate if the index indeed matches your farm’s goals.

TPI® = Total Performance Index

The primary selection index recommended by the Holstein Association USA is the Total Performance Index. TPI® is not necessarily aimed at breeding individual cows, but rather to advance the entire genetic pool.  TPI® it consists of the following emphasis:

    • 21% Pounds of protein
    • 17% Pounds of fat
    • 8% Feed efficiency
    • 13% Fertility index
    • -5% Somatic cell score
    • 4% Productive life
    • 3% Cow livability
    • 2% Daughter calving ease
    • 1% Daughter stillbirth
  • TYPE TRAITS = 26%
    • 11% Udder composite
    • 8% PTA type
    • 6% Foot & leg composite
    • -1% Dairy form

LPI = Lifetime Profit Index

The Lifetime Profit Index (LPI) is the primary selection tool used within each dairy breed in Canada. The main goal of LPI in each breed is to define the combination of traits for which genetic progress is desired and the relative importance of each trait for achieving the overall breed improvement goals. The current Holstein LPI formula places the following emphasis on its three major components:

  • 51% Production
  • 34% Durability
  • 15% Health & Fertility

Read more: (Everything You Need To Know About TPI and LPI)

NM$ = Net Merit Dollars

NM$ is a genetic index value calculated by the Council on Dairy Cattle Breeding (CDCB which estimates lifetime profitability of an animal; defined as the difference in expected lifetime profit of an animal, compared with the average genetic merit of cows within the breed born in the year of the genetic base. Like the TPI®, NM$ combines several production, type and health traits with weightings placed on their economic importance and the goals of the index. Trait weightings are updated approximately every five years and are currently:

    • 24% Pounds of fat
    • 18% Pounds of protein
    • -1% Pounds of milk
    • 13% Productive life
    • 7% Cow livability
    • 7% Daughter pregnancy rate
    • -6% Somatic cell score
    • 5% Calving ability
    • 2% Cow conception rate
    • 1% Heifer conception rate
  • TYPE TRAITS = 16%
    • 7% Udder composite
    • 6% Body weight composite
    • 3% Foot & leg composite

CM$ = Cheese Merit Dollars

Lifetime Cheese Merit $ was designed for producers who sell milk in a cheese market. Protein has more value in the cheese market than it does in the standard component pricing market. Milk receives a negative economic weight in the Cheese Merit index. Calculated by the current CM$ index was adjusted in April 2017 and the following trait weights are:

  • PRODUCTION = 50%
    • 22% Pounds of protein
    • 20% Pounds of fat
    • -8% Pounds of milk
  • HEALTH = 37%
    • 12% Productive life
    • -7% Somatic cell score
    • 6% Cow livability
    • 6% Daughter pregnancy rate
    • 4% Calving ability
    • 1% Cow conception rate
    • 1% Heifer conception rate
  • TYPE TRAITS = 13%
    • 6% Udder
    • 5% Body weight composite
    • 2% Foot & leg

Wellness Traits

Recently Zoetis introduced new health and wellness trait indexes with their Clarifide Plus Testing (Read more: The Complete Guide to Understanding Zoetis’ New Wellness Traits – CLARIFIDE® Plus).  The composite indexes that were introduced are:

  • Wellness Trait Index™ (WT$™)
    WT$ focuses exclusively on six wellness traits (mastitis, lameness, metritis, retained placenta, displaced abomasum, and ketosis) and includes an economic value for Polled test results.
  • Wellness Profit Index™ (DWP$™)
    DWP$ is a multi-trait selection index which includes production, fertility, type, longevity and the wellness traits, including Polled test results.

General Proof Terms

  • CDCB: Council on Dairy Cattle Breeding
    CDCB calculates production and health trait information for all breeds in the USA
  • CDN: Canadian Dairy Networks, calculates the genetic evaluations for all the major Dairy Breeds in Canada.
  • NAAB: The National Association of Animal Breeders (NAAB) maintains a database of marketing code numbers assigned to all bulls who enter AI.  The NAAB Uniform Code conveys three useful pieces of information:
    • A one to three digit numeric code indicating where the semen was processed (AI Unit)
    • A two letter alpha code designating the breed of the bull (HO = Holstein)
    • A one to five digit numeric code identifying the bull which produced the semen.
  • MACE: Multiple-trait across country evaluation
    MACE combines information from each country using all known relationships between animals, both within and across populations.
  • PTA: Predicted transmitting ability
    Predicted Transmitting Ability is the predicted difference between a parent animal’s offspring from average, due to the genes transmitted from that parent. Each PTA is given in the units used to measure the trait. The PTA for milk is reported in pounds or kilograms, the PTA for productive life is reported in months.
  • EFI: Effective future inbreeding
    An estimate, based on pedigree, of the level of inbreeding that the progeny of a given animal will contribute in the population if mated at random (Read more: The Truth about Inbreeding)
  • GFI: Genomic future inbreeding
    Similar to EFI, an animal’s GFI value predicts the level of inbreeding he/she will contribute to the population if mated at random. Yet, GFI provides a more accurate prediction. It takes into account genomic test results and the actual genes an animal has.
  • aAa: aAa analysis defines a cow’s structure under six categories. It relies purely on the physical attributes of the animal; no genetic merit is taken into consideration. The analysis aims to strike a balance between enough “roundness” to live and enough “sharpness” to milk high yields.
  • DMS: The Dairy Mating Service (DMS®) program is designed to be an efficient, totally independent system to help dairymen breed higher-producing and longer-living cattle.
    Similar to aAa DMS is a visual analysis of a dairy cow. Each cow is visually analyzed to determine strengths and weaknesses which may be passed on to offspring. When available it also considers each animal’s ancestry to find trends and patterns in the transmission of various genetic traits.

Production Trait Terms

  • PTAM: PTA for milk production in pounds, reflecting the expected milk production of future mature daughters
  • PTAP: PTA for protein production in pounds, comparing the expected production of future mature
  • PTAP%: Indicates the genetic variance of a bull’s PTA for transmitting protein as being positive or negative
  • PTAF: PTA for butterfat in pounds, reflecting the expected butterfat production of future mature daughters.
  • PTAF%: Indicates the genetic variance of a bull’s PTA for transmitting fat as being positive or negative.
  • PRel: the percent reliability of a sire’s production proof
  • Daughter ME Averages: This number tells you what daughters of a bull are actually averaging for a given trait, in this case, what they average for milk production. These values are based on twice a day milking, 305-day lactation, on a Mature Equivalent (ME) basis. If a bull has an official MACE evaluation, the daughter production averages will be based on the bull’s domestic U.S. evaluation.
  • Management Group ME Averages: This number allows you to contrast how daughters of a bull perform compared to herdmates of the same age, so you can evaluate whether they are, on average, superior or inferior to herdmates. Herdmates of the same age as Planet’s daughters are averaging 27,487 pounds of milk; on average, Planet daughters are producing 2,289 pounds of milk more in a 305-day lactation than their herdmates of the same age, on an ME basis.
  • Management Group ME Averages: Herdmates of the same age as Planet’s daughters are averaging 1,011 pounds of fat; on average, Planet daughters are producing 75 pounds of fat more in a 305-day lactation than their herdmates of the same age, on an ME basis.
  • Beta-Casein: Beta-Casein is a major casein protein making up 30% of the total milk protein. Studies have shown health benefits for diseases such as type 1 diabetes, IHD, schizophrenia and autism. (Read more: 12 Things You Need to Know About A2 Milk)
    • A2A2 – Most ideal test result
    • A1A2 – Median result – produces equal amounts of A1 and A2
    • A1A1 – Least ideal test result
  • Kappa-Casein (cheese production)
    There are many forms of Kappa-Casein A, B and E associated with milk protein and quality. Variants are related to the processing of cheese. Studies show yield for cheese production is higher with BB milk versus AA milk.

    • BB – Preferred result for cheese production
    • AB + BE – Intermediate result for cheese production
    • AA + AE – Least favorable result for cheese production

Health & Fertility Trait Terms

  • PL: Productive Life
    Productive life (PL) gives a measure of the amount of time a cow stays in the herd as a “productive” animal and represents how many months of additional (or fewer, if a negative number) lifetime you can expect from a bull’s daughters. Cows receive credit for each month of lactation, and the amount of credit corresponds to the shape of the lactation curve. The most credit is given to the months at the peak of lactation, and credit diminishes as the cow moves to the end of her lactation. First, lactations are given less credit than later lactations, in proportion to the difference in average production. PTAs for PL generally range from -7.0 to +7.0, with higher numbers being preferred. (Read more: Breeding for Longevity: Don’t believe the hype – It’s more than just high type)
  • LIV: Cow livability)
    Measure of a cow’s ability to remain alive while in the milking herd. (Read more: Cow Livability: Breeding for Cows That Stay in the Herd)
  • SCS: Somatic cell score
    The PTA for SCS is used to improve mastitis resistance. Bulls with low PTA for SCS (less than 3.0) are expected to have daughters with lower mastitis than bulls with high PTA for SCS (greater than 3.5). Health management has the biggest effect on SCS, but just like some people inherit a higher chance of getting ear infections, cows can inherit traits which cause higher Next to traits like milk or protein production, SCS has a low heritability.
  • DPR: Daughter pregnancy rate
    Daughter Pregnancy Rate is defined as the percentage of non-pregnant cows that become pregnant during each 21-day period. DPR takes into account how quickly cows come back into heat after calving and conception rate when bred. A DPR of ‘1.0’ implies that daughters from this bull are 1% more likely to become pregnant during that estrus cycle than a bull with an evaluation of zero. DPR PTA values typically range from +3.0 to -3.0, with higher values being preferable.  Each increase of 1% in PTA DPR equals a decrease of 4 days in PTA days open. (Read more: Does Your Breeding Program Save You Labor?)
  • HCR: Heifer conception rate
    A virgin heifer’s ability to conceive – defined as the percentage of inseminated heifers that become pregnant at each service. An HCR of 1.0 implies that daughters of this bull are 1% more likely to become pregnant as a heifer than daughters of a bull with an evaluation of 0.0. Services are only included if the heifer is at least 12 months old and less than 2.2 years.
  • CCR: Cow conception rate
    A lactating cow’s ability to conceive – defined as the percentage of inseminated cows that become pregnant at each service. A bull’s CCR of 1.0 implies that daughters of this bull are 1% more likely to become pregnant during that lactation than daughters of a bull with an evaluation of 0.0. CCR simply looks at the daughter’s ability to conceive when inseminated.
  • SCR: Sire Fertility
    Service Sire Conception Rate (SCR) is the difference of conception rate of sire expressed as a percent comparison. SCR is based on conception rate rather than non-return rate. SCR utilizes multiple services per lactation (up to 7), rather than first service only. A SCR of 1.2 means the bull is 1.2% above average.
  • HRel: the reliability percentage for a sire’s health traits
  • Body Condition Score (BCS)
    BCS is sourced from the Canadian Dairy Network (CDN). BCS reflects the animal’s energy balance status in which research has clearly shown an association with improved female fertility, longevity and disease resistance. BSC evaluations are expressed as relative breeding values with 100 being average. The scale of expression generally varies from 85 for bulls with daughters that generally have very low scores for body condition to 115 or higher for bulls with daughters that have high scores. Bulls rated over 100 are more desired.
  • Mastitis Resistance (MR)
    MR is sourced from the CDN. MR combines both clinical and sub-clinical mastitis into a single genetic selection index. The MR index puts equal weighting on the three areas of clinical mastitis in first lactation cows, clinical mastitis in later lactations and somatic cell score across the first three lactations. MR is expressed as a relative breeding value where 100 is average.
  • Milking Speed and Milking Temperament
    Data points come from the CDN. Milking Speed is evaluated in terms of the percentage of first lactation daughters evaluated as average or fast. Milking Temperament can be defined as milking behavior. Milking Temperament is expressed in terms of the expected percentage of future daughters evaluated as average, calm or very calm during their first lactation. A bull with a score of 100 for both traits indicates average.

Calving Trait Terms

  • SCE: Sire calving ease
    The percentage of bull’s calves born that are considered difficult in first lactation animals. Difficult births include those coded as a score of 3, 4 or 5 on a scale of 1-5, with a 1 classified as “no problem”). The percent difficult births among first-calf Holstein cows is approximately 8 percent. In general, bulls with an SCE of 8% or less are considered “calving ease” bulls that are fine to use on heifers and smaller cows. Bulls with a high SCE percentage should be used with caution on heifers and smaller cows, as they have a higher percent chance of siring larger calves that may pose more of a problem at delivery.
  • DCE: Daughter calving ease
    Like Sire Calving Ease (SCE), Daughter Calving Ease (DCE) is a measurement of the tendency of calves from a particular animal to be born more or less easily. DCE measures the ability of a particular cow (a daughter of a bull) to calve easily; daughters of bull’s with high DCE numbers would be expected to have a more difficult time giving birth than daughters of bulls with lower DCE numbers. DCE is evaluated on the same scale as SCE.
  • SSB: Sire stillbirth
    The percentage of a bull’s offspring that are born dead to first lactation animals.
  • DSB: Daughter stillbirth
    Measures the ability of a particular cow (daughter) to produce live calves. Stillbirth is expressed as percent stillbirths, where stillborn calves are those scored as dead at birth or born alive but died within 48 hours of birth.

Type / Conformation Trait Terms

 In the US 18 linear traits are expressed on a scale of Standard Transmitting Abilities (STAs) deviations, typically between -4.0 and +4.0.   For example, Rear, legs side view – an extreme negative value – a cow will have very posty, straight legs, while a extreme positive value will have sickle, curved rear legs.   In Canada there are 22 descriptive traits appraised using a 9-point linear
scale, with resulting breeding values typically between -20 to +20.  A rule of thumb we use to understand CDN proofs is divide by 5 and you will have their approx US scale for that trait.

  • PTAT: Predicted transmitting for type
    PTA Type is an estimate of the genetic superiority for conformation that a bull will transmit to its offspring. This is directly correlated with the final score of the bull’s daughters, not the linear traits.
  • UDC: Udder composite index
    Udder Composite is an index based on ability for udder improvement. Udder composite includes six linear traits, and the weighting for each trait’s contribution to higher udder scores. The traits and their weightings are:

    • 19% Rear udder height
    • 17% Udder depth
    • -17% Stature
    • 6% Rear udder width
    • 13% Fore udder attachment
    • 7% Udder Cleft
    • 4% Rear teat optimum
    • 4% Teat length optimum
    • 3% Front teat placement
  • FLC: Foot and leg composite index
    FLC is a measure of a bull’s ability for foot and leg improvement. Weights for the four traits in the composite are:

    • 58% foot and leg classification score
    • 18% rear legs rear view
    • -17% stature
    • 8% foot angle
  • Mammary System (Canada)
    • Udder Floor 4%
    • Udder Depth 12%
    • Udder Texture 14%
    • Median Suspensory 14%
    • Fore Attachment 18%
    • Front Teat Placement 5%
    • Rear Attachment Height 12%
    • Rear Attachment Width 10%
    • Rear Teat Placement 7%
    • Teat Length 4%
  • Feet and Legs (Canada)
    • Foot Angle 9%
    • Heel Depth 22%
    • Bone Quality 10%
    • Rear Leg Side View 14%
    • Rear Legs-Rear View 31%
    • Thurl Placement 14%
  • Dairy Strength (Canada)
    • Stature 12%
    • Height At Front End 3%
    • Chest Width 23%
    • Body Depth 17%
    • Angularity 28%
  • Rump (Canada)
    • Rump Angle 23%
    • Pin Width 21%
    • Loin Strength 32%
    • Thurl Placement 24%
  • TRel = the percent reliability for a sire’s conformation/type proof

Genetic Codes

    • PO: observed polled
    • PC: genomic tested as heterozygous polled; means 50% of offspring are expected to be observed as polled
    • PP: genomic tested as homozygous polled; means that 100% of offspring are expected to be observed as polled
    • RC: carries the recessive gene for red coat color
    • DR: carries a dominant gene for red coat color
    These codes, or symbols representing the code, will only show up on a proof sheet if an animal is a carrier or test positive for one of the following. The acronyms denoting that an animal is tested free of a recessive will only show up on its pedigree.

    • BY: Brachyspina
    • TY: Tested free of brachyspina
    • BL: BLADS, or Bovine leukocyte adhesion deficiency
    • TL: Tested free of BLADS
    • CV: CVM or Complex vertebral malformation
    • TV: Tested free of CVM
    • DP: DUMPS, or Deficiency of the uridine monophosphate synthase
    • TD: Tested free of DUMPS
    • MF: Mulefoot
    • TM: Tested free of mulefoot
    • HH1, HH2, HH3, HH4, HH5: Holstein haplotypes that negatively affect fertility
    • HCD: Holstein haplotype for cholesterol deficiency

The Bullvine Bottom Line

The letters, numbers, and acronyms on a proof sheet can be complicated.  We hope that this cheat sheet will help you better understand them the next time you go to make your mating decisions. It is important to remember not to try and correct everything with each mating, but instead pick the 2 to 3 traits that your animals need to be corrected most. 

For complete top genetic evaluation lists from around the world go to Sire Proof Central




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High Ranking Genomic Young Bulls – June 2017

Bulls with no daughters in their genomic proof for production or type.  No requirement for semen status.

Registration NumberNameRequesterNAAB codeBirth DateGFIProFatFeed
Yield % Rel.SCSPL Fert.
HO840003140986372PEAK DARLA HTLN U889-ETAlta201705048.67683193742.556.72.02.992.582.841.30715.36.22947
HO840003140986351PEAK DARLA HTLN U882-ETAlta201705037.87684209742.697.51.92.702.121.98-0.18714.75.92882
HO840003141657524BLUMENFELD FRAZZLED 5712-ETSelect201704108.06281178742.648.62.72.552.502.190.32714.45.42879
HO840003142181099PEAK LAVISH ROBSN 20485-ETAlta201704147.859112233742.798.03.71.651.631.120.57723.64.32866
HO840003137908317BROWN STAR 3550-ETGenex201704097.26795203742.687.23.81.721.022.451.45703.85.42865
HO840003123606838MR 63049-ETNGenVis201704068.85779169772.608.83.82.432.441.300.36744.94.92863
HO840003142181082PEAK ALEXAL BRBN 20468-ETAlta201704058.17575186752.797.33.02.571.791.940.63734.44.32858
HO840003141992416UNITED PRIDE 1405-ETGenex201703196.85898205742.598.
HO840003142181491PEAK EXPO ROBSN 80427-ETAlta201704117.464104234742.848.93.81.351.211.29-0.67713.75.12849
HO840003142181520PEAK JOSETTE HTLN 80456-ETAlta201704288.06281180742.737.31.62.752.872.310.89713.83.82839
HO840003142181106PEAK LAVISH ROBSN 20492-ETAlta201704238.56992213742.748.13.21.661.331.300.22723.64.02838
HO840003141494407ABS SPECTRE 7821-ETABS201704208.070113229752.887.
HO840003140766081KINGEMERLING GRNT DEARON-ETHO201704018.86486179742.897.72.32.652.621.660.47723.93.92835
HO840003140986357PEAK LAVISH HTLN U895-ETAlta201705078.978124254742.914.
HO840003142181521PEAK EXPO HTLN 80457-ETAlta201704298.467103222742.816.
HO840003141135032MIDAS-TOUCH HELIX DINGLE-ETAcceler201704138.860112211742.847.
HO840003143160100PEAK ALEXAL LYLAS T746-ETAlta201703248.46089192752.696.
HO840003136176263LARS-ACRES SUPER NERD-ETSelect201704207.85780175742.698.
HO840003142181108PEAK AZALEA ROBSN 20494-ETAlta201704238.26786205742.788.72.91.621.661.31-0.02713.64.92816
HO840003138766589DOUBLE A 3550-ETGenex201703267.76999225742.947.82.91.701.331.45-1.09713.64.22814
HO840003142934691OCD HELIX 43176-ETSelect201704258.351104196742.577.
HO840003142181523PEAK DANCER HTLN 80459-ETAlta201704308.951106188742.685.
HO840003142934662OCD LEGENDARY 43147-ETSelect201704198.74981158742.779.
HO840003138766569AARDEMA 3530Select201703188.17092205742.718.52.31.621.230.960.03713.53.42803
HO840003142181366PEAK LUXURY ROBSN 60802-ETAlta201704307.762116227742.857.22.51.820.971.911.07714.74.02803
HO840003138766572AARDEMA 3533Select201703197.85685186742.708.94.21.781.341.14-0.52723.54.62802
HO840003134545080PLAIN-KNOLL 10606Select201704178.36299208742.767.
HO840003141428969OCD BOURBON 41590-ETSelect201704258.45675171742.807.64.32.321.961.560.37734.04.42798
HO840003132117338PINE-TREE 9882 MODES 886-ETABS201704077.770101233752.977.72.61.781.570.66-0.68744.14.32797
HO840003142181325PEAK MEG ROBSN 60761-ETAlta201704088.35291197742.829.05.01.331.460.850.21714.13.92796
HOUSA00064BLT3850LFD JEDI TEANA 1150-ETHO201702088.36868167742.897.73.32.311.961.720.90723.94.92794
HO840003141495129SIEMERS S-HERO DICER-ROZ-ETSemex201702068.65795179742.727.42.32.362.381.761.35706.26.82793
HO840003142181351PEAK ZRONICA SALRC 60787-ETAlta201704238.369102215742.538.50.51.711.271.510.01704.94.62793
HO840003132117332PINE-TREE 9882 MODES 880-ETABS201703308.062105222752.917.
HO840003141494402WILRA ABS SPECTRE 7816-ETABS201704178.458102213752.718.21.71.921.671.52-0.25723.63.12791
HOUSA000074396068DAR-BURN BOURBON 936-ETAlta201704018.062101216742.837.63.71.521.700.080.14714.65.62791
HO840003137794587HIGHER RANSOM 11607GenVis201704257.967105241743.
HO840003140616286SANDY-VALLEY EFFECT-ETSelect201704278.66481184742.849.
HOUSA000144130674PINE-TREE 9882 DO MYSTIC-ETHO201703188.16073153752.857.33.02.702.581.541.48744.64.22787
HO840003140986599WESTCOAST HARMONY-ALEXAL 702Semex201702089.16996206742.826.91.02.411.941.490.58714.14.22786
HO840003143721680SSI-DUCKETT 8317Select201704278.37283185742.804.72.22.582.610.901.14724.86.42786
HO840003138922928LEANINGHOUSE JEDI 23219-ETHO201704218.26473156742.776.93.02.321.872.101.13733.85.02785
HO840003141559525DE-SU GRANITE 14131-ETSemex201704018.34890182752.917.92.82.532.612.02-0.78723.44.32784
HO840003132923828PENN-ENGLAND GIFIAN1306A-ETSelect201704088.65879154742.737.
HO840003132117325PINE-TREE 9839 APPR 873-ETSemex201703228.87486212752.917.11.92.301.531.42-0.07724.74.82778
HO840003137908319BROWN STAR 3552-ETGenex201704138.17684208742.946.22.51.911.651.730.50705.36.02778
HO840003143160060MR RAGEN JACEY 1199GeneSeek201704078.06577188752.667.62.71.982.151.170.11736.36.42778
HO840003141560227NO-FLA HYFLOW 46133-ETGenex201702127.67558165752.818.83.41.541.421.530.96724.64.52777
HO840003141495240SIEMERS GRANITE HANDSOME-ETSemex201704208.45980173742.868.42.42.362.111.710.46723.44.42776
HO840003141559577DE-SU LEGENDARY 14183-ETSelect201704308.44684155742.788.
HO840003135583841DYKSTRA 30807-ETGenex201704097.86598218742.786.82.91.561.451.090.08725.25.02774
HO840003140503780N-SPRINGHOPE FRAZLD 2893-ETSelect201703038.45799202742.627.92.01.891.740.82-0.28724.03.92772
HO840003142181529PEAK HEIDI ROBSN 80465-ETAlta201705038.653109211752.886.
HO840003129437023WET GRANITE 181-ETSemex201703307.95983173752.857.32.52.602.321.46-0.04724.25.62771
HO840003131058506HOLLERMANN RAGEN 175-ETGenex201703097.87092193752.678.41.61.371.571.150.34725.65.32771
HO840003139851226KINGS-RANSOM G 10527-ETSemex201704068.35670160742.846.51.53.383.152.381.15733.94.72771
HO840003132117331PINE-TREE 9839 GAGE 879-ETABS201703308.165106237752.908.11.61.801.521.49-1.08725.65.32769
HO840003142181103PEAK COOKIE HTLN 20489-ETAlta201704208.76674195742.755.82.22.432.081.74-0.59703.14.42768
HO840003142934577OCD SUPERHE RAEDEN 43062-ETSelect201703318.86081191742.888.
HO840003143160074PEAK FASTLANE HELIX T715-ETAlta201703159.369104225742.965.81.81.911.411.72-0.17713.23.82768
HO840003141562808MELARRY FRAZZLED FATS-ETSelect201704057.97191214742.628.31.31.361.301.280.13735.05.02767
HO840003143105036BACON HILL MYSTIC 3522Select201705048.46876169742.896.03.12.321.771.961.30724.95.22767
HOUSA000144135482FUSTEAD KING BOB-ETHO201704038.34075140742.587.82.82.822.762.021.54733.53.72766
HO840003139904998WESSELCREST 499-ETGenex201703088.85783166752.715.
HO840003141428881OCD BURLEY 41502-ETABS201704097.957100189742.936.
HO840003138817808WELCOME TRIAXLE 3480-ETSelect201704018.75694193742.817.
HO840003140503775N-SPRINGHOPE FRAZLD 2888-ETSelect201702248.36596196742.746.
HO840003141559530DE-SU SPECTRE 14136-ETABS201704058.55996194742.958.
HO840003142934551OCD BURLEY 43036-ETABS201703258.95892196742.696.
HO840003139851225KINGS-RANSOM G 10526-ETSemex201704188.95791180743.
HO840003132117347PINE-TREE 6543 MODES 895-ETABS201704257.56085203752.797.
HO840003137794590FLY-HIGHER 11610GenVis201704198.06795210742.809.
HO840003141559555DE-SU LEGENDARY 14161Select201704208.15473159742.718.92.42.702.411.540.47715.86.12758
HO840003138887946GREEN-BANKS BOURBON 7075-ETZoetis201704198.16794203742.807.02.21.671.551.320.41725.35.42757
HO840003138817809WELCOME PEACEFUL 3481-ETSelect201704017.87096218732.737.01.71.901.600.610.18716.35.62756
HO840003139490563SSI-DUCKETT 8292Select201704158.56065140752.695.
HO840003139490547SSI-DUCKETT 8276Select201704107.96272167742.777.43.51.881.961.310.44724.86.22754
HO840003138766610DOUBLE A 3571-ETGenex201704017.44777160742.558.44.41.641.411.64-0.45714.35.42751
HO840003142490296T-SPRUCE 738Select201704128.65778165742.588.23.01.601.511.470.77734.44.22750
HO840003139490553SSI-DUCKETT 8282Select201704128.05347124742.538.45.31.551.881.390.54724.15.22749
HO840003142934610OCD GRANITE 43095-ETSemex201704068.84291167752.867.92.72.862.431.740.58734.13.92749
HO840003134545082PLAIN-KNOLL 10608Select201704248.26873171742.766.71.82.351.812.240.89735.84.22748
HO840003132117336PINE-TREE 6800 BOURB 884-ETABS201704078.66271153742.695.82.02.512.781.691.46725.16.72747
HO840003138766509DOUBLE A 3470-ETGenex201702177.75390180742.588.32.71.571.301.850.23724.64.82747
HO840003139669731HAAK-HAVEN FLYWHEEL AXEL-ETAlta201703158.15680173752.918.52.62.412.101.820.14724.85.92747
HO840003140616263SANDY-VALLEY APP CANTON-ETSemex201704078.35984169742.716.
HO840003140986600WESTCOAST HARMONY-ALEXAL 705Semex201702098.97291205742.786.
HO840003141494330ABS VERONA 7744-ETABS201703127.75789184742.678.92.21.641.681.210.67704.65.62747
HO840003140503778N-SPRINGHOPE FRAZLD 2891-ETSelect201702278.06899222742.826.
HO840003143721693SSI-DUCKETT 8330Select201704308.75688179742.816.41.52.542.342.301.12724.25.22746
HO840003137163910REGANCREST K 12153HO201703038.86695202752.846.
HO840003140371443FARIA BROTHERS GRANITE 181453Semex201703318.565104208742.816.71.01.841.471.450.99713.14.62745
HO840003140371493FARIA BROTHERS GRANITE 181378Semex201704078.55290186752.787.
HO840003141494348ABS VERONA 7762-ETABS201703187.96182177742.758.52.71.601.491.650.79705.54.82745
HO840003141274936LOEHR - 716Cogent201703188.75365136752.577.
HO840003143105018WELCOME TERRY 3504-ETAlta201704108.34679161752.716.73.62.692.161.950.66745.15.52744
HO840003140986694PEAK SURREAL ROBSN T775-ETAlta201703317.95968161742.738.64.21.481.521.110.76714.64.92742
HO840003143241583GENESEE SUPERHERO 22-ETHO201705049.350105198742.876.31.72.542.491.560.41714.85.52741
HO840003141428929OCD BOURBON 41550-ETSelect201704198.161106230742.906.82.91.341.131.01-1.07733.75.02740
HO840003142181097PEAK ALEXAL BRBN 20483-ETAlta201704137.97392209752.816.21.61.890.931.99-0.09735.14.82740
HO840003132117340PINE-TREE 9882 CHARL 888-ETZoetis201704147.869100222752.867.
HO840003141559574DE-SU LEGENDARY 14180-ETSelect201704298.55381161742.757.
HO840003141559578DE-SU SPECTRE 14184-ETABS201705018.25695200742.876.
HO840003142181332PEAK WILDC TSHOT 60768-ETAlta201704138.55796199742.748.01.61.751.521.340.03722.54.12737
HO840003142710468MAPLEHURST 4323-ETGenex201703247.76382197742.726.32.71.781.481.830.37705.05.12737
HO840003140239383MATCREST GATEDANCER 446-ETGenex201703218.36988199742.877.
HO840003140284991ZIMMERVIEW GRANITE 822-ETSemex201704077.85578176752.988.63.61.861.611.58-0.15732.94.22736
HO840003141494425ABS SPECTRE 7839-ETABS201705038.371100219743.
HO840003138766607AARDEMA 3568Select201704018.75578168742.858.
HO840003138766644AARDEMA 3605Select201704179.16989216742.906.02.31.781.910.56-0.34725.24.72733
HO840003141494420ABS SUPERHERO 7834-ETABS201704308.25189181742.699.
HO840003141559533DE-SU LOPEZ 14139-ETSelect201704098.175102231742.904.91.31.691.211.420.02704.24.42733
HO840003141806488MCVD HELIX 6808-ETZoetis201703159.17991217742.975.91.71.761.191.410.16724.86.52733
HO840003143721676SSI-DUCKETT 8313Select201704268.15474163742.806.25.01.901.810.960.11734.46.32733
HO840003141559538DE-SU GRANITE 14144-ETABS201703298.65988187752.856.92.71.751.371.431.16711.93.82731
HO840003143097101CLAYTOP 602-ETGenex201704118.36290182752.737.
HO840003136176259LARS-ACRES SUPER NATURAL-ETSelect201704178.65191191742.756.
HO840003137794589FLY-HIGHER 11609GenVis201704187.96588198742.837.
HO840003138766559DOUBLE A 3520-ETGenex201703158.76475171742.688.11.71.731.901.241.01724.15.42730
HO840003142181331PEAK MABEL ROBSN 60767-ETAlta201704128.16577192742.996.33.31.761.891.040.06713.34.32730
HO840003142490304T-SPRUCE 746Select201704278.76878183742.638.01.11.771.751.530.32715.95.62730
HO840003123606842ST GEN 63053-ETNGenVis201704269.23775145762.6710.13.81.761.981.850.43743.64.12728
HO840003141428854OCD BLOWTORCH 41475-ETGenex201704056.96382205742.667.12.51.531.491.21-0.60714.56.32728
HOUSA000144143076GIL-GAR GRANITE ZACK-ETSemex201704175.94683146732.807.12.82.472.052.021.30702.73.42728
HO840003138766586AARDEMA 3547Select201703258.86198204742.677.70.41.651.721.74-0.25714.53.92727
HO840003142934637OCD BLOWTORCH 43122-ETGenex201704128.262103207742.715.81.71.721.301.600.62724.75.82726
HO840003134545085PLAIN-KNOLL 10611Select201704289.26379181742.785.52.02.491.722.190.49724.64.52725
HO840003137909052JOOK BANDARES 17682-ETHO201704188.35979176742.688.52.01.621.392.110.91724.15.52725
HO840003141428838OCD GRANITE TABORA 41459-ETSemex201704028.45383170742.837.
HO840003141657512BLUMENFELD SURGEON 5700-ETGenex201703287.46381166742.796.
HO840003138919653HENDEL GRANITE 626-ETSemex201704018.94974143752.757.72.72.452.391.551.23723.55.52724
HO840003140616266SANDY-VALLEY EVINRUDE-ETSelect201704168.95893202742.777.13.01.741.141.24-0.12734.84.92724
HO840003141399112SYNERGY 6377-ETSelect201703288.66593199742.896.31.61.911.941.210.12724.94.42724
HO840003132920280FAIRMONT 5251-ETGenex201704158.65679172762.707.
HO840003140239386MATCREST 449Select201703288.46199186742.855.
HO840003141559554DE-SU GAGE 14160ABS201704208.05663150752.709.82.71.891.482.130.47724.34.32723
HO840003142181088PEAK ALEXAL BRBN 20474-ETAlta201704087.96568161752.776.51.62.602.052.110.67734.75.62722
HO840003143721706SSI-DUCKETT 8343Select201705037.95791207732.5410.53.10.810.680.24-2.01715.15.72722
HOUSA000144150481GIL-GAR GRANITE ZILCH-ETSemex201704197.75781150742.837.01.92.422.001.641.15713.23.52722
HO840003135301291RONELEE DACARA G 327-ETSemex201704018.44883172752.936.
HO840003140616291SANDY-VALLEY EMPRO-ETSemex201704308.66274171742.657.92.31.901.381.340.65714.54.02721
HO840003142181478PEAK MYSTERY ROBSN 80414-ETAlta201704077.75988192742.777.92.91.561.270.840.20724.34.32721
HO840003142181530PEAK MYSTERY HTLN 80466-ETAlta201705038.963117245742.955.
HO840003143097100CLAYTOP 601-ETGenex201704018.75164147742.667.
HO840003142934638OCD BURLEY 43123-ETABS201704138.45187171742.647.83.11.601.341.640.64724.84.92720
HO840003134545079PLAIN-KNOLL 10605Select201704168.760106209742.796.40.82.331.831.480.67726.75.72719
HO840003141559520DE-SU GRANITE 14126-ETSemex201703308.94276142752.837.43.62.632.252.011.06723.75.12719
HO840003142181479PEAK JOSETTE ROBSN 80415-ETAlta201704087.64971165742.748.33.51.911.921.361.35714.14.22719
HO840003140239398MATCREST HELIX 461-ETHO201705028.65993195742.836.
HO840003141559569DE-SU GRANITE 14175-ETSemex201704288.25796182752.996.
HO840003138766621AARDEMA 3582Select201704108.16586191742.907.02.21.911.551.340.59714.95.12716
HO840003142181089PEAK ALEXAL BRBN 20475-ETAlta201704098.46871166752.815.71.42.721.832.230.64734.35.82716
HO840003142181110PEAK AZALEA ROBSN 20496-ETAlta201704237.84983190742.729.
HO840003134545084PLAIN-KNOLL 10610Select201704258.45558134742.876.33.72.642.091.941.58723.93.22715
HO840003140284990ZIMMERVIEW MODESTY 821-ETSelect201704067.871103242753.
HO840003132923826PENN-ENGLAND TARMAC 1304ASelect201704068.05954159742.768.33.31.791.781.92-0.25714.04.12712
HO840003141428956OCD BOURBON 41577-ETSelect201704238.14581166742.617.93.61.661.841.20-0.11724.45.72712
HO840003142181370PEAK LUXURY ROBSN 60806-ETAlta201705057.96598206742.856.71.41.811.181.690.73714.94.52712
HO840003138766561DOUBLE A 3522-ETGenex201703167.65593192742.818.12.61.601.172.03-0.17725.36.02711
HO840003138922922LEANINGHOUSE GRANT 23213-ETHO201704199.24772159742.908.04.31.801.851.680.17723.04.92711
HO840003141494201ABS BOURBON 7615-ETABS201704017.87475179742.856.52.41.851.101.060.81724.25.22711
HO840003142934677OCD 43162Select201704227.76981187742.916.42.21.971.571.450.67706.14.72711
HO840003132117334PINE-TREE 9839 GAGE 882-ETABS201703318.85372177752.958.63.41.931.751.98-0.39724.94.32710
HO840003141559553DE-SU HELIX 14159ABS201704198.357117213742.895.
HO840003142181120PEAK MEG BTRCH 20506-ETAlta201705098.55463136742.837.
HO840003142181321PEAK LOYAL SHERO 60757-ETAlta201704068.67087203752.836.30.12.452.131.330.74725.65.42710
HO840003142934550OCD BLOWTORCH 43035-ETGenex201703247.76298216742.955.62.61.811.381.450.02724.95.92710
HO840003143160053SSI-TOG U842Select201704108.75862147732.747.
HO840003132923830PENN-ENGLAND GIFIAN1308A-ETSelect201704098.46484172742.736.
HO840003141559519DE-SU GRANITE 14125-ETSemex201703298.94969154752.907.63.52.342.111.710.26723.04.92709
HO840003143552998AR-JOY CU MOD AG-ETHO201704178.15489198742.927.91.62.441.931.74-0.18724.55.52709
HO840003142181090PEAK GINA ROBSN 20476-ETAlta201704098.04567141752.797.83.12.452.431.721.36723.33.92708
HO840003142490303T-SPRUCE 745Select201704208.16873179742.796.
HO840003143105022WELCOME LEMERY 3508-ETGenex201704207.96188209752.836.10.92.422.011.95-0.42725.04.82708
HO840003141494393ABS VERONA 7807-ETABS201704148.26575174742.798.63.11.481.480.500.11716.26.02707
HO840003140371568FARIA BROTHERS GRANITE 181306Semex201704038.360102200743.
HO840003142041145TTM BANDERAS BUCKLE-ETSelect201702098.55877155742.777.22.02.411.841.571.77734.65.02706
HO840003138817817WELCOME TRIPOLEE 3489-ETSelect201703288.74080154752.808.
HO840003141494392ABS SPECTRE 7806-ETABS201704138.057113224742.797.51.41.491.171.050.05734.95.22705
HO840003141495186SIEMERS FERDNAND BEROZE-ETSemex201704117.16457156752.956.93.32.321.911.790.10725.05.32705
HO840003140650409LADYS-MANOR LEGEND 888Select201704048.33985157742.799.14.11.721.801.390.41725.24.82704
HO840003141428947OCD BOURBON 41568-ETSelect201704218.36274166742.756.
HO840003137661315SEAGULL-BAY 1315Cogent201701158.47879216752.806.01.51.441.171.20-0.60724.75.42703
HO840003140640922ARMSON CHANNING TATUMGenex201702268.06094196732.786.50.62.442.041.460.16715.06.42703
HO840003141806562MCVD FLAGSHIP 6882-ETZoetis201704168.96660173742.777.
HO840003137794598FLY-HIGHER 11618-ETGenVis201705058.04370142742.779.
HO840003139904994WESSELCREST 495-ETGenex201703018.55474152752.776.50.92.682.382.571.50723.24.42702
HO840003141428930OCD LEGENDARY 41551-ETSelect201704197.94158115742.6410.34.61.821.701.520.34715.04.32702
HO840003142181508PEAK HAMLET BNDRS 80444-ETAlta201704208.94278161752.808.12.02.462.652.290.68724.64.22702
HO840003142934603OCD ZAMBONI 43088-ETSelect201704058.45066153742.775.73.52.692.041.420.50722.93.02702
HO840003133300841COYNE-FARMS EUCLID MARK-ETGenex201702098.15780174742.828.21.91.621.721.51-0.07702.73.52701
HO840003138206083LEANINGHOUSE BURBN 22886-ETHO201704028.35663154742.846.84.51.931.601.760.89725.66.42701
HO840003141428882OCD BURLEY 41503-ETABS201704098.15584173742.707.12.21.961.761.34-0.26724.65.32701
HO840003141559558DE-SU ROCKETFIRE 14164Select201704218.46969187752.826.
HO840003141559579DE-SU SPECTRE 14185-ETABS201705017.96487200742.796.51.02.441.781.55-0.53725.86.02701
HO840003143160075PEAK SURREAL TSHOT T714-ETAlta201703159.05175158742.738.22.71.801.911.480.60713.35.42701
HO840003135301292RONELEE FELECITY G 328-ETSemex201704038.14373136742.787.51.92.762.892.341.57724.65.22700
HO840003138766634DOUBLE A 3595-ETGenex201704138.35390189752.778.
HO840003132117348PINE-TREE 9882 BURLE 896-ETABS201704278.162109212752.875.92.01.810.940.590.98733.94.02699
HO840003135583828DYKSTRA 30794-ETGenex201703318.35265156752.768.43.71.691.811.410.13734.74.92699
HO840003142181510PEAK MABEL ROBSN 80446-ETAlta201704228.35893202742.896.02.81.581.301.220.65712.94.02699
HO840003134199328NO-FLA FERDINAND KC 82947-ETSelect201611058.16984187752.815.
HO840003138766560AARDEMA 3521Select201703168.86573184742.788.31.61.661.321.66-0.30733.84.02698
HO840003138766618DOUBLE A 3579-ETGenex201704088.35362149752.528.32.41.932.251.34-0.02725.46.72697
HO840003140038508MORNINGVIEW BOURBON 324-ETABS201705018.75690179752.776.31.12.582.261.780.52736.46.92697
HO840003137794586FLY-HIGHER 11606GenVis201704199.16680177742.825.00.32.602.181.991.11733.63.82696
HO840003142181077PEAK HONOR LYLAS 20463-ETAlta201703298.36687184742.755.
HO840003142181078PEAK COOKIE ROBSN 20464-ETAlta201703307.86485200742.855.42.31.871.471.530.57714.55.02696
HO840003142181505PEAK CLOUD9 HTLN 80441-ETAlta201704198.56776187742.756.32.01.951.700.62-0.42704.25.02696
HO840003137593973RICHMOND-FD BT JUKEBOXGenex201704257.05684185742.727.23.11.340.961.75-0.43723.55.42695
HO840003140239381MATCREST GRANITE 444-ETSemex201704018.85780159752.866.
HO840003140616242SANDY-VALLEY MR LOYALTY-ETHO201704028.456118227742.956.21.01.981.551.34-0.14715.15.02695
HO840003140986364PEAK AUBURN HTLN U884-ETAlta201705038.24796192742.805.
HO840003142181496PEAK CLOUD9 HTLN 80432-ETAlta201704138.37077185742.836.02.81.881.180.880.15705.05.82695
HOUSA000074396069DAR-BURN BOURBON 937-ETAlta201703297.66386195742.878.04.10.910.550.42-0.80714.04.62695
HO840003132170248DEER-BROOK AMULET 168Alta201704277.75973179752.917.10.92.682.691.69-0.25724.75.42694
HO840003133104829ARIWAMI BOURBN BLAST 600-ETSelect201704177.86956148742.805.02.92.421.852.011.20726.06.82694
HO840003141428889OCD FLYWHEEL RAE 41510-ETAlta201704098.24891177752.798.
HO840003141560336NO-FLA PAYTON 46242-ETAlta201702248.65889182752.726.70.82.362.131.711.34716.96.22693
HO840003130915957IDEAL 12386Select201704138.46288191742.806.20.71.982.511.33-0.11715.85.72692
HO840003139660073AMMON FARMS RAMBO BRUISERSelect201704058.23764116752.687.
HO840003139864675HYDE-PARK DAMIEN 57Genex201703238.44175156742.657.
HO840003139068525NO-FLA ROWDY ORTIZ 90561-ETGenex201703148.76782198752.847.32.61.541.000.58-0.74734.34.82691
HO840003139490556SSI-DUCKETT 8285Select201704148.26275167742.626.22.21.871.421.560.98725.15.82691
HO840003140038502MORNINGVIEW 318-ETSelect201704238.96574169742.665.40.22.532.471.551.14714.55.22691
HO840003140616241SANDY-VALLEY EGNOS-ETSemex201704018.35776165742.767.42.61.681.461.08-0.05702.33.12691
HO840003140891392WAKE-UP RAGEN 3969-ETGenex201704087.66277176752.707.32.41.311.301.45-0.19734.44.42691
HO840003141428897OCD SUPERHERO 41518-ETSelect201704128.26478190742.816.
HO840003141428900OCD BLOWTORCH 41521-ETGenex201704118.25968166752.616.42.51.491.671.880.96734.15.02691
HO840003141559537DE-SU GRANITE 14143-ETSemex201704108.44096161752.757.
HO840003138817820WELCOME PROCTER 3492ABS201704018.43579130742.568.44.11.461.591.761.42713.14.72690
HO840003135301290RONELEE FELICITY G 326-ETSemex201703307.95588171742.856.
HO840003141559521DE-SU GRANITE 14127-ETSemex201703309.14878142752.926.12.32.532.671.971.03723.44.72689
HO840003132923825PENN-ENGLAND GIFIAN1303A-ETSelect201704058.47296204742.986.00.91.701.061.650.85714.23.62688
HO840003141495137SIEMERS MODESTY ROOZE-ETSemex201703318.16480181742.886.
HO840003142181512PEAK EXPO HTLN 80448-ETAlta201704247.97390213742.905.
HO840003142934663OCD SUPERSTAR 43148-ETSelect201704198.15662136742.647.52.52.301.781.501.38724.25.22688
HO840003143721674SSI-DUCKETT 8311Select201704268.46386171742.764.81.72.301.621.511.57725.15.22688
HO840003135301293RONELEE DACARA G 329-ETSemex201704039.14688175752.776.
HO840003140616283SANDY-VALLEY 3297Select201704278.65474162742.668.32.71.661.401.640.88715.55.02687
HO840003141559527DE-SU GRANITE 14133-ETSemex201704028.45985182752.966.82.71.921.601.100.34724.05.32687
HO840003132117337PINE-TREE 9882 CHARL 885-ETZoetis201704058.15786179752.747.12.31.801.580.980.55725.14.92686
HO840003138817822WELCOME TREPIDO 3494-ETSelect201704068.25791192742.737.02.71.750.941.21-0.04725.64.82685
HO840003141559564DE-SU LEGENDARY 14170Select201704228.45387175742.797.23.11.741.501.150.89715.66.02685
HO840003143721696SSI-DUCKETT 8333Select201704307.95169157742.656.24.31.631.670.940.17734.15.52685
HO840003143105027WELCOME KRISTOE 3513Select201704258.15051117742.568.22.72.392.371.421.22734.94.72684
HO840003138766562DOUBLE A 3523-ETGenex201703167.36177162742.896.53.11.501.232.040.81703.85.92683
HO840003139220568MSU 1682-ETGenex201703318.06573180752.755.
HO840003140650403LADYS-MANOR KROY 882-ETSelect201703017.76695205742.955.91.11.991.561.410.91724.95.12683
HO840003142181326PEAK LOYAL SHERO 60762-ETAlta201704088.55258134752.728.43.12.361.811.641.34725.05.72683
HO840003142181119PEAK COOKIE JEDI 20505-ETAlta201705088.17278197752.955.61.81.971.171.720.00723.85.62682
HO840003137794597FLY-HIGHER 11617-ETGenVis201705037.64976155742.598.83.21.391.091.461.08704.15.52681
HO840003141559572DE-SU HARMONY 14178-ETSemex201704297.97483210742.796.62.01.320.820.94-0.15695.85.12681
HO840003142181083PEAK HONOR HELIX 20469-ETAlta201704068.76599208742.805.11.51.471.381.24-0.06704.94.92681
HO840003142181102PEAK AZALEA ROBSN 20488-ETAlta201704187.75386185742.886.33.31.621.401.160.88712.74.12681
HO840003133191132MIKENNY GRANITE 1299-ETSemex201703307.86077166753.
HO840003136176250LARS-ACRES HELIX TEETIME-ETSelect201704048.77395222752.856.10.61.781.430.850.07716.45.32680
HO840003138922921LEANINGHOUSE LGDRY 23212-ETHO201704188.44886162742.958.33.41.721.411.661.18704.74.72680
HO840003141560299NO-FLA XAVIER 46205-ETAlta201702198.257104210752.647.81.21.431.021.200.43706.35.82680
HO840003138369905EILDON-TWEED GATE BELEIN-ETGenex201704197.94887199742.687.22.51.921.371.52-1.09724.75.02678
HO840003130915956IDEAL 12385Select201704178.46369165742.967.
HO840003135301294RONELEE DACARA G 330-ETSemex201704058.33986165742.797.
HO840003138499046PEAK BUENA DILL 20416-ETAlta201702148.05772169742.836.
HO840003138766636DOUBLE A 3597-ETGenex201704157.66663160752.817.61.41.882.241.210.00724.65.72677
HO840003143721694SSI-DUCKETT 8331Select201704308.85284170742.945.41.72.612.502.060.74724.75.32677
HO840003138817821WELCOME TREPID 3493-ETSelect201704038.55584180742.726.51.32.372.071.54-0.14725.66.22676
HO840003140284992ZIMMERVIEW GRANITE 823-ETSemex201704097.55480175752.878.12.11.711.641.520.26733.34.82676
HOUSA00064BLT3847LFD JEDI LILY 1147-ETHO201701129.04969156752.848.04.21.691.501.450.27724.55.72676
HO840003137984307JENNY-LOU IRONMAN 8597-ETSelect201704088.74662156752.798.93.61.672.301.46-0.53735.16.12675
HO840003140616277SANDY-VALLEY KRAGEN-ETSemex201704228.95279139752.766.80.62.662.382.072.02733.45.42675
HO840003142181104PEAK AZALEA ROBSN 20490-ETAlta201704208.24960137742.839.14.41.331.391.360.67712.83.42675
HO840003142934619OCD ZAMBONI 43104-ETSelect201704078.25983182742.825.22.12.381.860.850.23724.64.92674
HO840003136555708UNITED PRIDE 1400-ETGenex201703118.24957141742.727.
HO840003141495202SIEMERS CHARLES ROO-ETSemex201704148.16170149752.884.
HO840003142181528PEAK DANCER HTLN 80464-ETAlta201705028.34278153742.785.41.32.833.062.451.01703.64.92673
HO840003143159990PEAK SURREAL ROBSN U816-ETAlta201703318.24767156742.818.13.61.631.671.510.71712.24.52673
HO840003135583839DYKSTRA 30805-ETGenex201704088.25252136752.589.33.41.361.721.160.54734.14.72672
HO840003141399099SYNERGY 6364-ETZoetis201703208.57094213742.805.90.31.931.631.020.67726.36.62672
HO840003141428858OCD BLOWTORCH 41479-ETGenex201704067.55993209742.866.52.71.451.101.39-0.15715.66.22672
HO840003141559552DE-SU LEGENDARY 14158Select201704208.45173147742.908.
HO840003142181350PEAK LAVISH GDNCR 60786-ETAlta201704218.25885194742.835.
HO840003142934699OCD 43184Select201704278.15368165742.729.43.51.690.861.08-0.17714.64.22672
HO840003143721663SSI-DUCKETT 8300Select201704198.06080168742.695.62.21.961.631.120.44724.66.72672
HO840003138766615DOUBLE A 3576-ETGenex201704068.55750142752.757.53.61.751.412.19-0.03733.55.42670
HO840003141494408ABS SPOCK 7822-ETABS201704218.151110209742.776.81.61.401.001.49-0.13693.74.92670
HO840003136661584HILMAR-D LEGEND BOOMER-ETSelect201703269.05251127742.718.
HO840003137908321BROWN STAR 3554-ETGenex201704167.75674166742.727.71.81.631.382.000.17693.43.72669
HO840003141494388WILRA ABS SPECTRE 7802-ETABS201704107.85073159742.749.12.01.791.791.37-0.30723.44.52668
HO840003143159979SSI-TOG U868Select201704238.27977198742.817.1-
HO840003143160062PEAK MILLY ROBSN U827-ETAlta201704038.36892208752.835.71.31.410.871.520.34734.13.52668
HO840003135583843DYKSTRA 30809-ETGenex201704117.86686191742.975.81.61.891.881.220.24726.25.42667
HO840003141428901OCD HURLEY 41522Select201704138.24687185742.627.23.31.371.171.07-0.53734.14.22667
HO840003141806510MCVD HELIX 6830-ETZoetis201703158.66567170742.956.
HO840003142934608OCD SUMO 43093-TW-ETSelect201704068.85677177743.
HO840003136176260LARS-ACRES SUPR NINTENDO-ETSelect201704197.75485182742.847.32.51.811.671.050.76715.45.92666
HO840003139490347SSI-DUCKTT 8076Select201701158.17379199742.928.42.11.390.860.50-0.35706.25.72666
HO840003142181495PEAK HEIDI ROBSN 80431-ETAlta201704137.76577198742.927.72.51.590.741.22-0.93723.63.92666
HO840003137593971RICHMOND-FD BURLEY AL-ETABS201704228.850102187742.667.01.21.451.581.100.42713.84.42665
HO840003138817823WELCOME LIBRATION 3495-ETABS201704067.76897205742.717.31.60.980.470.920.52715.75.52665
HO840003140986297PEAK ALEXAL HTLN T842-ETAlta201704238.74993186742.784.70.82.732.222.380.80714.75.22665
HO840003140986369PEAK FUCHSIA ROBSN U890-ETAlta201705057.25087185742.827.61.71.961.901.20-0.22724.04.22665
HO840003141992419UNITED PRIDE 1408-ETGenex201703308.33870134752.668.
HO840003142181357PEAK HATTIE HTLN 60793-ETAlta201704268.56872155742.953.
HO840003142490306T-SPRUCE 748Select201704298.17596225743.

GTPI is  a servicemark of Holstein Association USA Inc.

High Ranking Genomic Females – June 2017

Top 200 females receiving their first genomic evaluation in the current month

Registration NumberNameBirth DateGFISire's NamePTAPPTAP%PTAFPTAF%MilkFeed Eff.Yeild Rel.SCSPLFert. IndexPTATUDCFLCBSCType Rel.DCEDSBGTPI
HO840003132352740MS 78906-ET201704268.4S-S-I MONTROSS JEDI-ET690.01790.002168178752.639.63.32.571.972.120.8734.05.82929
HO840003142041169MS DG-TM MODESTY BREEZE-ET201704118.2BACON-HILL PETY MODESTY-ET67-0.01920.032242203742.919.
HO840003134691934SANDY-VALLEY EDEN-ET201704048.4BACON-HILL PETY MODESTY-ET620.08970.171351221753.
HO840003142478597AL-LEW JEDI AVATAR 1459-ET201703078.7S-S-I MONTROSS JEDI-ET660.01770.002069167742.957.
HO840003134691925SANDY-VALLEY EMOTION-ET201704027.8BACON-HILL PETY MODESTY-ET620.041070.161696228742.888.12.12.582.002.01-0.9723.84.12869
HO840003141493633DE-SU MANTON 7047-ET201704168.6BACON-HILL MANTON 2873-ET580.04770.071540173752.799.
HO840003141691493T-SPRUCE FRAZZLED 10694-ET201702188.0MELARRY JOSUPER FRAZZLED-ET840.04980.032440235742.767.21.71.881.391.580.1735.45.92863
HO840003132352676201704118.3WA-DEL YODER BANDARES-ET580.01710.011795160752.708.73.22.972.751.730.4744.04.32861
HO840003141806565MCVD FLAGSHIP 6885-ET201704178.7S-S-I 1STCLASS FLAGSHIP-ET590.05870.121443189742.908.13.82.542.232.040.4733.86.12859
HO840003141493619DE-SU MODESTY 7033201704118.7BACON-HILL PETY MODESTY-ET460.05890.181112166752.678.
HO840003141428853OCD FRAZZLED NAPPY 41474-ET201704058.2MELARRY JOSUPER FRAZZLED-ET540.03810.091490171742.569.
HO840003141605469EILDON-TWEED BRB WILA 2B-ET201704098.1WA-DEL ABS BOURBON-ET700.06900.091798205752.766.81.62.902.372.110.6744.66.02857
HO840003139672498PINE-TREE 9882 MODE 7502-ET201704178.1BACON-HILL PETY MODESTY-ET650.03930.091854199752.857.92.82.502.321.080.4743.94.12854
HO840003141493620DE-SU MANTON 7034-ET201704117.9BACON-HILL MANTON 2873-ET720.0169-0.062271182752.939.44.31.821.781.41-0.1713.45.02854
HO840003139672500PINE-TREE 6543 MODE 7504-ET201704187.7BACON-HILL PETY MODESTY-ET750.03900.022229220753.
HO840003143104749WELCOME-TEL MANTN HALINA-ET201703217.7BACON-HILL MANTON 2873-ET640.06750.071541182752.878.24.12.382.011.760.5733.05.22852
HO840003141562812MELARRY 2948201704138.4MELARRY JOSUPER FRAZZLED-ET760.051220.172048264742.688.
HO840003132352655MS 78821-ET201704068.3SEAGULL-BAY SUPERSIRE-ET710.061160.181785254772.818.
HO840003141493671DE-SU SPECTRE 7085-ET201705027.9DE-SU 13050 SPECTRE-ET700.041120.132032232742.897.
HO840003140618350201705019.0WA-DEL YODER BANDARES-ET650.04870.061863191752.859.13.41.991.861.000.5744.24.32834
HO840003141494410ABS HELIX 7824-ET201704248.4AOT SILVER HELIX-ET640.08880.131442204752.958.
HO840003138922872LEANINGHOUSE MDSTY 23163-ET201703158.0BACON-HILL PETY MODESTY-ET420.05700.13908150742.768.83.62.873.452.000.0732.44.32831
HO840003141235937MATCREST BOURBON 1639-ET201703218.0WA-DEL ABS BOURBON-ET810.0273-0.092592202742.807.12.81.961.791.22-0.4724.05.42831
HO840003141428894OCD BURLEY MENNA 41515-ET201704117.9PINE-TREE BURLEY-ET580.051040.181488204742.647.83.11.971.441.730.5715.35.42828
HO840003136617240OUR-FAVORITE INVIGORATE-ET201704138.0BACON-HILL PETY MODESTY-ET620880.042074188742.967.62.62.652.452.03-0.2733.85.52827
HO840003143159819BGP FLAGSHIP DIAMOND-ET201703148.6S-S-I 1STCLASS FLAGSHIP-ET550.03950.121597171752.808.
HONLD000879381767DROUNER K L CLASSY-ET201704018.3ENDCO SUPERHERO-ET560.04960.161448184722.698.
HO840003132352783201705068.0BACON-HILL PETY MODESTY-ET580.05970.161471203742.867.
HO840003141725897SIMPLE-DREAMS 1325 F2692-ET201704058.5S-S-I 1STCLASS FLAGSHIP-ET490.06800.131144173742.699.
HO840003141495141SIEMERS MODSTY ROZ 27305-ET201704028.1BACON-HILL PETY MODESTY-ET650.01850.022094195752.917.52.52.672.291.67-0.6734.64.12819
HO840003138887934GREEN-BANKS FLAGSHP 7063-ET201704067.9S-S-I 1STCLASS FLAGSHIP-ET700.03950.072062204752.936.
HO840003141428865OCD MODESTY RAEDEN 41486-ET201704068.1BACON-HILL PETY MODESTY-ET550.07900.161218217742.898.23.91.992.201.01-1.9733.25.22813
HO840003134691936SANDY-VALLEY AP MARIPOSA-ET201704078.4ENDCO APPRENTICE-ET520.05780.121224168742.598.72.42.642.082.570.5714.04.42808
HO840003141495108SIEMERS JDI BROOKE 27272-ET201703278.1S-S-I MONTROSS JEDI-ET790.09790.051734213752.788.12.81.431.410.780.6724.65.22808
HO840003141493644DE-SU GRANITE 7058-ET201704258.3PROGENESIS GRANITE590.06990.171386206752.838.11.52.812.261.490.2734.55.12807
HO840003141494403ABS SPOCK 7817-ET201704188.1ROSYLANE-LLC SPOCK-ET650.08990.161447227742.798.52.01.461.631.48-0.5703.14.82807
HO840003139799998201703027.3BACON-HILL PETY MODESTY-ET670.02960.072030225742.917.
HO840003141495133SIEMERS BANDRS ROZ 27297-ET201702068.4WA-DEL YODER BANDARES-ET570.071010.201258203752.787.
HO840003140618346201704289.0S-S-I 1STCLASS FLAGSHIP-ET510.07770.141051157752.697.
HOGBR162206600415TYNEVALLEY JEDI BAMBI-ET201703158.7S-S-I MONTROSS JEDI-ET670.01820.012103177762.797.
HO840003134691955SANDY-VALLEY ESPYN-ET201704308.1ENDCO APPRENTICE-ET620.05840.081644189742.648.
HO840003141657530BLUMENFELD FRAZZLED 5718-ET201704128.3MELARRY JOSUPER FRAZZLED-ET600.0357-0.031714147742.668.
HO840003132352715201704168.2FARNEAR TANGO SABRE 1973-ET500.04780.121227153752.548.53.22.662.521.401.3745.56.82801
HO840003137909038JOOK BANDARES 17668-ET201704108.8WA-DEL YODER BANDARES-ET600.05640.031545157742.609.33.81.831.741.500.8723.74.32801
HO840003139017361201703168.2PLAIN-KNOLL KING ROYAL-ET610.05910.111620183742.677.01.62.871.861.951.2723.94.22800
HO840003139017365201704028.1S-S-I MONTROSS JEDI-ET810.0378-0.042412197742.917.
HO840003132352756ST GEN 78922-ET201705018.7AOT SILVER HELIX-ET720.071050.141733223742.895.80.52.692.181.821.0715.35.52799
HOUSA000144130496PINE-TREE 9882 D O MISTY-ET201703198.3WA-DEL YODER BANDARES-ET410.06650.13786125752.639.24.82.622.711.591.6744.84.82799
HO840003133120660S-S-I BG 9494 15395-ET201703298.8AOT SILVER HELIX-ET730.041060.112024223742.985.22.12.471.451.540.7714.94.42797
HO840003137909040JOOK JEDI 17670-ET201704138.6S-S-I MONTROSS JEDI-ET810.0460-0.092261179742.749.02.41.841.591.240.9724.86.32797
HO840003134691930SANDY-VALLEY JUBILEE-ET201704108.2WA-DEL YODER BANDARES-ET590.05830.101521176752.838.42.52.432.421.450.9724.74.92795
HO840003142934602OCD SALOON RAEDEN 43087-ET201704058.5SANDY-VALLEY SALOON-ET600.05810.091490171772.746.71.83.322.701.761.4755.65.92794
HO840003141495113SIEMERS MODSTY ROZ 27277-ET201703287.9BACON-HILL PETY MODESTY-ET630.03950.101842212752.838.
HO840003137349559CO-OP 8500-ET201704017.6SYRYCZUK SILVR BLOWTORCH-ET640.03780.021868171722.836.42.62.462.452.011.1694.26.32792
HO840003141657519BLUMENFELD FRAZZLED 5707-ET201704078.2MELARRY JOSUPER FRAZZLED-ET65-0.01900.022275184742.667.61.22.482.091.890.5716.25.62791
HO840003142934609OCD FLAGSHIP RAE 43094-ET201704068.7S-S-I 1STCLASS FLAGSHIP-ET430.07800.18791152752.677.
HO840003134691952SANDY-VALLEY FRAZZLE EZA-ET201704267.8MELARRY JOSUPER FRAZZLED-ET650.011050.112018218742.788.01.81.571.541.20-0.3724.63.52790
HO840003135373356ALL-ROUND FLAGSHIP HARDY-ET201705018.6S-S-I 1STCLASS FLAGSHIP-ET450.06720.14915153742.679.
HO840003138922873LEANINGHOUSE MDSTY 23164-ET201702288.6BACON-HILL PETY MODESTY-ET500.04800.121274182742.927.92.22.702.972.16-0.9732.23.32788
HO840003141428939OCD GATEDANC DANNY 41560-ET201704208.6TRIPLECROWN GATEDANCER-ET540.08940.201077188742.766.61.92.972.591.601.0715.05.32784
HO840003141428990OCD VERONA DETROIT 41611-ET201705017.9PINE-TREE VERONA-ET600.06790.101393183732.737.71.92.642.321.820.4704.64.42784
HO840003141805355JE-KO MODESTY GIFT201703268.1BACON-HILL PETY MODESTY-ET550.04960.151487202743.
HO840003142934648OCD BANDARE LAVAGE 43133-ET201704168.9WA-DEL YODER BANDARES-ET550.08930.201053182752.666.81.82.552.321.871.6745.04.62784
HO840003138887832GREEN-BANKS ALLTIME 6961-ET201612238.2S-S-I HEADWAY ALLTIME-ET570.06640.061293159742.617.53.71.901.991.980.6733.54.12782
HO840003141495095SIEMERS IRONMN ROZ 27259-ET201703246.9S-S-I DAMARIS IRONMAN-ET560.07970.191262201742.737.82.12.302.011.070.2704.04.92782
HO840003132352734ST GEN 78900-ET201704258.9S-S-I 1STCLASS FLAGSHIP-ET540.07800.121196172742.788.62.82.342.252.060.8715.35.32780
HO840003140766074EMERLING BURLEY DEANN-ET201703297.8PINE-TREE BURLEY-ET690.051020.121845221732.756.91.71.921.241.490.2704.85.72778
HO840003132920143FAIRMONT BLOWTORCH ROXY201702218.0SYRYCZUK SILVR BLOWTORCH-ET500.03840.121370161722.467.
HO840003138735837201704258.0DE-SU 13050 SPECTRE-ET620.041130.181665232742.777.81.91.701.120.74-0.5723.04.32777
HO840003142437637CO-OP FERDINAND 5753-ET201703248.4DE-SU FERDINAND 12489-ET710.03800.012058191742.876.84.31.601.011.580.4715.85.42777
HO840003138735828201704128.4ROSYLANE-LLC SPOCK-ET590.05970.161424202742.658.62.41.591.481.140.3705.04.72776
HO840003141255282UNITED-PRIDE BORBN 10615-ET201702148.1WA-DEL ABS BOURBON-ET640.0268-0.011921168742.667.74.61.311.091.140.2712.34.32776
HO840003143184944N-SPRINGHOPE FLGSHP 2931-ET201704248.8S-S-I 1STCLASS FLAGSHIP-ET620.031020.121836200742.817.30.92.631.941.690.7735.04.32776
HOUSA000144160200STONE-HAUS FLGSHP M5 VI-ET201704188.8S-S-I 1STCLASS FLAGSHIP-ET590.05910.121525184742.757.51.22.492.232.291.0725.54.92776
HO840003138922912LEANINGHOUSE MDSTY 23203-ET201704147.5BACON-HILL PETY MODESTY-ET630.02940.081944217743.
HO840003139198656QUIET-BROOK-D HTIME LIME201704228.4COOKIECUTTER HANG-TIME-ET640.05800.071684193742.796.51.52.822.441.72-0.2723.95.62775
HO840003131264374201702178.2S-S-I MONTROSS JEDI-ET720.05870.061919208742.837.93.21.581.061.130.2736.06.12774
HO840003138206078LEANINGHOUSE JEDI 22881201703298.6S-S-I MONTROSS JEDI-ET78-0.0190-0.042684205753.
HO840003141255232CO-OP UPD WRENCH 10565-ET201701247.8BLUMENFELD SPRING WRENCH-ET740.0666-0.031931193722.846.92.81.952.300.96-0.3704.85.52774
HO840003141493621DE-SU GRANITE 7035-ET201704119.0PROGENESIS GRANITE540.03820.091558155742.826.63.22.322.271.781.5723.23.62772
HO840003141495111SIEMERS MODSTY ROZ 27275-ET201703287.8BACON-HILL PETY MODESTY-ET630.01900.062000197742.766.72.61.911.651.68-0.4724.14.92772
HO840003138206107LEANINGHOUSE MODESTY 22910201704248.0BACON-HILL PETY MODESTY-ET620.061090.191525232743.
HO840003141428512OCD FLAGSHIP MISSY 41133-ET201701248.7S-S-I 1STCLASS FLAGSHIP-ET550.07810.131226171752.785.
HO840003142041163TTM BANDERAS ELECTRIC-ET201703288.8WA-DEL YODER BANDARES-ET690.05680.001838169742.807.72.81.861.601.751.2723.43.42771
HO840003141495094SIEMERS FERDND ROZ 27258-ET201703247.9DE-SU FERDINAND 12489-ET730.03820.022066213752.847.32.01.971.701.23-0.8724.75.52769
HO840003141691294SONRAY-ACRES JEDI SLEIGHBEL201702218.1S-S-I MONTROSS JEDI-ET610.09810.131200193742.818.52.81.801.731.620.3734.25.02768
HO840003134691917SANDY-VALLEY MD LIESL-ET201704046.8BACON-HILL PETY MODESTY-ET6201030.102004207742.767.
HO840003140617404UECKER CHARLEY JO SASH-ET201704018.1DG CHARLEY640.04930.101793210752.797.
HO840003132352652ST GEN 78818-ET201704058.0S-S-I 1STCLASS FLAGSHIP-ET580.06740.081400167742.688.
HO840003142038180PLAIN-KNOLL LEGNDRY 1546-ET201704079.1WELCOME LEGENDARY 2870-ET650.03840.061864179742.818.41.72.401.702.001.2726.15.12766
HO840003142186142ZIM-BLUE-BAY MODESTY 21331201703288.3BACON-HILL PETY MODESTY-ET470.03700.081246154742.768.63.32.382.371.94-0.1722.63.72765
HO840003141493631DE-SU GRANITE 7045-ET201704159.1PROGENESIS GRANITE530.051000.191277195742.817.
HO840003143013316SIMPLE-DREAMS R545 F2702-ET201704168.6S-S-I 1STCLASS FLAGSHIP-ET520.06720.111176169742.718.43.32.302.062.03-0.1724.85.32764
HO840003134691933SANDY-VALLEY LIGHTS OUT-ET201704048.7PROGENESIS OUTLAST580.07830.131314181742.537.
HO840003136306871LFD JEDI SAMIAH 362-ET201702218.6S-S-I MONTROSS JEDI-ET560.05870.141370185742.878.
HO840003141495206SIEMERS ABL NATION 27370-ET201704158.2LEANINGHOUSE KING ABEL-ET640.07920.131452202742.905.91.32.802.371.240.7713.94.22763
HO840003142181065PEAK NRVANA FSHIP 20451-ET201703108.1S-S-I 1STCLASS FLAGSHIP-ET610.07960.151436203742.757.
HO840003141428867OCD BLOWTORC LOVEY 41488-ET201704078.2SYRYCZUK SILVR BLOWTORCH-ET670.03840.041909206742.926.92.81.911.511.57-0.8713.35.02761
HO840003134691954SANDY-VALLEY ESSENTIAL-ET201704308.5ENDCO APPRENTICE-ET470.01720.071422148742.579.52.91.951.901.930.2712.53.42760
HO840003141135016MIDAS-TOUCH BOURBON JESS-ET201704028.1WA-DEL ABS BOURBON-ET670.05770.041762170742.725.
HO840003141495231SIEMERS JEDI OAKRA 27395-ET201704198.0S-S-I MONTROSS JEDI-ET690.0359-0.051948151752.728.
HO840003143104761WELCOME KERMIT TAREEN-ET201703228.8PEAK ALTAKERMIT-ET510.03710.061480147752.577.52.72.722.221.600.8743.94.12757
HO840003127498486TERRA-LINDA JEDI 274201704208.7S-S-I MONTROSS JEDI-ET640.03790.041796183752.878.52.61.911.581.860.3734.06.22756
HO840003141495119SIEMERS GRANIT HANKERINA-ET201703298.0PROGENESIS GRANITE560.02760.051674156743.
HO840003140985799201704068.3S-S-I 1STCLASS FLAGSHIP-ET47-0.01680.031615125752.708.
HO840003141494395ABS SPECTRE 7809-ET201704147.5DE-SU 13050 SPECTRE-ET650.061080.171624226742.817.62.01.341.201.220.1715.35.32755
HO840003142580174RUANN FLAG METRONY-72952-ET201704197.9S-S-I 1STCLASS FLAGSHIP-ET580.01800.051796169742.817.42.12.532.032.150.5734.05.22755
HO840003143769255CRYSTAL-STAR FLSH 984-ET201703278.9S-S-I 1STCLASS FLAGSHIP-ET460.03630.061208131742.548.53.22.712.202.321.0724.95.12755
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HO840003142301723201704139.0WELCOME LEGENDARY 2870-ET510.03750.081448152742.818.

GTPI is  a servicemark of Holstein Association USA Inc.

Can You Trust Genomic Evaluations? 7 Facts Exposed

Successful dairy cattle breeding is about using the facts available including the degree of trust that can be placed in the numbers. The facts used by breeders can vary all the way from in-herd observations, to show results, to including actual performance and genetic evaluation indexes. This article will deal with the genetic evaluation indexes that are based to a great extent on an animal’s DNA analysis. Often just referred to as ‘genomics.’ In this article, The Bullvine will cover details, from recently released studies and articles. We will look at how genomic evaluations are adding trustworthy information to the toolkit that breeders can use to advance their herds genetically.

1) Accuracy

Before there were genomic indexes, there were parent average genetic indexes (PA’s) for heifers that did not have their performance (production and type) records of for bulls that did not have daughters with a performance recorded. The prediction accuracy for PA’s was low, standing at 20-33%. Breeders knew that there would be a wide variation from the PA numbers, once performance data was added in.

In 2008, based on the study of the DNA profiles of daughters proven sires, genomic (genetic) indexes were published by genetic evaluation centers that used both pedigree performance information and an animal’s DNA profile. Immediately the accuracy of the genomic indexes doubled (60-65%) those for PA’s. Of course, this was lower than the accuracies for extensively daughter proven sires, but a significant step forward.

Alta Genetics has recently published an excellent article on the accuracy of genomic index predictions – “How genomic proofs hold up.” The study compares genomic indexes at the time of release as young sires and what their indexes are in April 2017.

The study reports:

  • Young sires released in 2010 2014 decreased by 171 vs. 52 in TPI and by 151 vs. 74 in NM$.
  • For the 1078 US A.I. Holstein bulls released in 2013, their April 2017 indexes decreased on average by 99 TPI and 103 NM$. The degrees of change for TPI were: 4% of bull lost more than 300 TPI points; 9% remain, in 2017, within 20 TPI points of their 2013 indexes; and 19% increased in TPI from their 2013 to 2017 indexes. For NM$: 2% on the bulls changes by more than 300 in NM$; 9% were within 20 NM$ in 2017 of their 2013 indexes, and 9% increased in their NM$ index.

Definitely, there was an increase in accuracy of prediction of genomic indexes from 2010 to 2017.

Take Home Message: With each passing year, breeders can place more and more trust in the accuracy of genomics indexes. As more animals have their DNA profile established and as more SNIP research is conducted breeders can expect to see further increases in accuracy of genomic indexes. Also, there will, in the future, be the publication for additional genomic indexes for specific fats and proteins, for lifetime performance and for health and fertility traits.

2) Improvement Rates

CDN has recently reported on a study “Analysis of Genetic Gains Realized Since Genomics.” This study compares two five-year time periods: (a) animals born (2004-2009) immediately prior to the existence of genomic evaluations; and (b) animals born (2011-2016) after genomic evaluations were available to breeders.


The rates vary by trait with the range in compared indexes being from a small improvement rate to over 500%. Note that in Holsteins the rate of genetic gain in protein %, lactation persistency (LP), daughter fertility (DF) and milking temperament (MTP) went from negative to positive. In Jerseys LP, MSP and daughter calving ability (DCA) went from negative to positive, yet metabolic disease resistance (MDR) went slightly negative. Similar rates of improved genetic gains were achieved by both Ayrshire and Brown Swiss breeds.

Take Home Message: Congratulations to the breeders for trusting and using the genomic index information to make faster rates of genetic improvement. A word of thanks goes out to the genetic evaluation centers all over the world for doing the research on and implementation of genomic indexes. The very significant increased rates of genetic gain may not be duplicated in the future for all traits as breeders are now selecting for many new economically important traits not previously evaluated and published.

3) Terminology

It is a known fact that the term ‘genomics’ has not always been interpreted correctly by everyone.

Over forty years ago, when genetic indexes were first published, frequently breeders thought of them as only being for production traits when they were available for both production and type traits. Today many people refer to genomic indexes as only being for production traits when they are available for production, type, fertility, health, other functional traits and total merit indexes (TPI, NM$, …).

Take Home Message: Interpret genomic indexes to be genetic indexes that include both pedigree and DNA profile information. Breeders can find genomically evaluated sires for all traits at all A.I. studs. Breeders can use one or all the genomic indexes as part of their herd’s breeding plan.

4) Inbreeding

Alta Genetics recently published an article, “Inbreeding: Manage it to Maximize Profit,” on sire options to limit the effects of inbreeding.

The article covers:

  • When selection is practiced in a population, it results in a concentration of good genes and thus inbreeding. So, inbreeding is a natural outcome of selecting the best and eliminating the rest.
  • Every 1% increase in inbreeding results in $22 – $24 less profit over a cow’s lifetime.
  • There is not a magic level of inbreeding to be avoided. The current average level of inbreeding in North American Holsteins is 7-8%.
  • A Midwest US study shows that superior inbred high genetic merit cows are more profitable than inferior genetic merit non-inbred cows.

The average inbreeding level of the top 25 NM$ (April ’17) daughter proven Holstein sires is 7.9% for genomic future inbreeding index (GFI). For the top 25 NM$ genomically evaluated sires the average GFI is 8.2%. Having genomic bulls with a higher level of inbreeding than proven sires is as expected when selection pressure is high, when generations are turned rapidly and when there is extensive focus placed on a single total merit indexes (NM$ or TPI or Pro$ or LPI or …).

Take Home Message: A.I. sire mating programs are designed to take into consideration the level of inbreeding of future progeny when a sire x dam is recommended. If a Holstein sire has a GFI of 9% or higher a breeder should require that that bull should have positive proof values for all of DPR, HCR, CCR, LIV, PL, SCC, immunity and calf wellness. Breeders should use and trust that inbreeding is being handled by sire mating programs.

5) Functional Traits

At the same time, as genomic evaluations became available, breeders started paying attention to a host of functional traits. These traits have economic significance and include milk quality, fertility, heifer, and cow health (immunity, wellness, disease resistance, livability, …), birthing, productive life and mobility. In the future, these functional traits will be expanded as on-farm data, and DNA profiling on animals are recorded and farm data is sent to data analysis centers. Noteworthy is the fact that animal wellness and welfare will be front and center for consumers of dairy products.

Take Home Message: Breeders can trust in the published genetic evaluations for functional traits as animal DNA profiles play a significant role in increasing the prediction accuracies from 15-25% to 60-70%. Functional trait improvement will require that breeders pay attention to both genetic and farm management.

6) Feed Efficiency

Feed accounts for 50-60% input costs for heifers and cows on dairy farms. Any gains that can be made by selecting genetically superior animals for their ability to convert feedstuffs to milk and meat have the potential for breeders to make more profit.

Research and data analysis are underway or nearing completion in many countries including US, Netherlands, and Canada on using DNA data combined with nutrition trial data to produce genomic indexes for feed efficiency. Other trials are underway to electronically capture on-farm data on feed intake, dry matter intake (DMI). It is a well-established fact that level of production is highly correlated to DMI.

CDAB has just published that “AGIL/USDA has demonstrated the feasibility of publishing national genomic evaluations for residual feed intake (RFI) based on the data generated by the 5-year national feed intake project funded by USDA National Institute of Food and Agriculture (NIFA), involving several research groups”. “The next step for CACB is to develop a proposal on how to collect data for use in genetic analysis for feed efficiency.”

Take Home Message: There will be genomic indexes for feed efficiency likely with 2-3 years. Once again breeders will have a tool they can trust into breed animals that return more profit.

7) Breeder Acceptance

A.I.’s are reporting that 60 to 90% of their semen sales are from genomically evaluated bulls. That fact on its own says that breeders purchasing larger volumes of semen are putting their trust in genomic evaluations. However, breeders wanting daughter proven sire proofs need to be given that option provided they are prepared to pay extra for their semen.

Take home message: Breeders check books tell the whole story – Genomic Evaluations are trusted.

The Bullvine Bottom Line

In less than a decade the use of DNA data in genetic evaluations has gone from unknown and not understood to a trusted source of very useful information. Having genomic indexes has given breeders the opportunity to advance their breeding programs, their herds, and their on-farm profits.  Trust in information is important to dairy cattle breeders and they have and will continue, in the future, to place their trust in genomic indexes.



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Does Filtering Really Help Achieve Your Breeding Goals?

It can be argued that sire selection is the single most important element of a successful breeding program. Of course, it goes without saying that you must first have established the breeding objectives for your herd. This is where the two national genetic selection indexes, LPI and Pro$, have a critical role to play.  Canadian Dairy Network (CDN) and each breed association provides lists of top animals… proven sires, genomic young bulls, cows and heifers, ranked based on their LPI and Pro$.  These indexes have been developed and implemented to guide Canadian producers in terms of setting their breeding goals and then realizing them.

Optimum Sire Selection Strategy

The ideal strategy for producers to achieve their breeding objectives is first to rank sires based on your preferred selection index. Once the highest sires for that index are identified, then the second step is to determine how to best incorporate them in your herd by avoiding matings that result in too much inbreeding and/or a higher risk of carrying an undesirable genetic recessive such as the gene associated with Cholesterol Deficiency.

In Canada, producers are encouraged to determine whether LPI or Pro$ best meets their overall needs.  Recall that Pro$ was introduced in August 2015 as a profit-based index that ranks sires, and cows, according to the net profit that their daughters are expected to realize during the first six years of their life. Compared to Pro$, producers using LPI as their primary selection index can expect more genetic progress for conformation traits but slower gains for production yields and both indexes have a similar expected response for most functional traits.

Filtering on Trait Minimums

Some producers have adopted the strategy of applying minimum values on one or more traits for filtering through sires to identify those to use in the herd. Such a strategy can have a very significant impact on the resulting sire selection, which is often not considered.

Table 1 serves as an example of the impact of this type of filtering by trait on the resulting genetic profile of the selected sires, which is based on the top genomic young bulls actively marketed in Canada following the April 2017 release.  Assuming that a total of ten sires are needed, scenario A simply provides the average evaluation for the Top 10 genomic bulls based purely on either Pro$ or LPI. As expected, these two groups have very high averages for all traits with Pro$ being stronger for production yields and slighter lower for conformation traits.

For the four other scenarios, from B to E, the averages in Table 1 are based on the ten highest sires for LPI among those that pass the various filtering criteria. With scenario B, a minimum Conformation evaluation of at least +12 was imposed. While this approach increases the average Conformation rating by 1.6 points it has a significant negative impact on the overall level of selected bulls for all other traits presented, except Fat yield. To counteract this impact on production, scenario C adds a second filter to include only those bulls that are at least +12 Conformation and +1500 Milk.  This approach helps to some extent in terms of reducing the negative impact on milk yield but this strategy still translates to an important sacrifice for Daughter Fertility, Herd Life and Protein yield. In an effort to address this issue for Daughter Fertility, scenario D adds a third filter by removing any bull that is not at least breed average (i.e.: 100) for that trait. Lastly, scenario E is included in Table 1 to demonstrate that this third filter on Daughter Fertility would have to be increased to include only those bulls at 105 or higher in order to not lose any opportunity for genetic improvement compared to using either LPI or Pro$ as the sole selection criteria. Under this scenario, however, there is no real impact on the average level for Conformation but the resulting group of selected sires would translate into a significant sacrifice of 207 kg Milk, 5.7 kg Fat and 15.2 kg Protein compared to using the Top 10 sires by LPI.

Table 1 is also very revealing in terms of the impact of sire selection filtering on the genetic level for the overall indexes of LPI and Pro$. For LPI, scenarios B to E would be interpreted by most breeders as having a minor impact with a decrease of about 30 to 40 LPI points for scenarios B, C and D and 79 LPI points for scenario E.  Given that Pro$ is a profit-based index expressed in true dollar terms, the impact of the filtering examples in Table 1 can be more accurately quantified.  For scenarios B, C and D, which all have an impact of reducing the average Pro$ value of roughly 100, this would translate to an expected lost opportunity of an extra $100 lifetime profit for every daughter born in the herd during the year.  For a herd with 50 heifer calves born annually, this equates to lost profit of $5,000 per year compared to using a sire selection strategy based solely on LPI. Under scenario E, which has a larger negative impact on production yields, the lost profit per year would be almost doubled. If Pro$ was the selection index of choice, for which the top 10 sires average about $3000 instead of $2925 for the top 10 LPI sires, the lost profits under each scenario would be about $75 more per daughter per year.

In summary, the temptation to apply minimum values for filtering through the long lists of sires being actively marketed in Canada is understandable but should be avoided.  Such sire selection strategies actually hinder the speed at which you achieve your breeding objectives. LPI and Pro$ are two different selection indexes designed to meet the varying interests of Canadian producers. Select which index best suits your breeding goals and then stick with it to select the sires to use in your herd while managing the inbreeding level and likelihood of genetic recessives for each mating.

Brian Van Doormaal, General Manager, CDN
Lynsay Beavers, Industry Liaison Coordinator, CDN

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CDCB Announces Leadership Changes

The CDCB Board of Directors is pleased to announce newly-elected directors and advisory members.

These directors are designated by sector for a three-year term during the CDCB Annual Meeting:

  • Gordie Cook, from Holstein Association USA Inc., representing the Purebred Dairy Cattle Association.
  • Bill Verboort, from AgriTech Analytics, representing the Dairy Records Processing Centers.
  • Pat Baier, from AgSource Cooperative Services, representing the Dairy Records Providers.
  • Charles Sattler, from Select Sires, Inc., representing the National Association of Animal Breeders.The CDCB Board and staff express their gratitude to Kent Buttars for his dedication and contribution as a CDCB Board Member for the past three years.The CDCB Board of Directors appointed Juan Tricarico (Innovation Center for U.S. Dairy) and Don Bennink (North Florida Holsteins) as the Non-Voting Advisory Members of the CDCB Board for the year of 2017.Data AccessThe CDCB is in the process of reviewing the existing business rules for data access. The main proposed changes are:
    • Reset all user accounts on the industry queries website, moving from company accounts to individualaccounts.
    • Access to collaborator’s data should be granted by data providers through bilateral agreements.
    • All users would need to commit to online end-user agreements in order to access either collaborator’sdata or CDCB products.
    • User permissions to use the CDCB online queries will be defined in two dimensions: type of results andanimal control.
    • Preference will be given to individual searches using queries and group files using ftp.

4201 Northview Dr. | One Town Center | Suite 302 | Bowie, MD 20716 |

Health Traits Genetic Evaluations

Research and development of genetic and genomic evaluations for health conditions (hypocalcemia, displaced abomasum, ketosis, mastitis, metritis, and retained placenta) has been successfully completed by CDCB’s geneticist Kristen Gaddis with the support of the AGIL/USDA researchers. A revision of the data-exchange Format 6 has been discussed with dairy records processing centers to ensure a smooth ingestion of health records into the cooperator database. The National Dairy Herd Information Association (NDHIA) is leading the process to obtain farmer authorization for routine transfers of health event data to the CDCB. This project has the highest priority for the CDCB members, and the goal is to release preliminary evaluations in December 2017.

Feed Efficiency

AGIL/USDA has demonstrated the feasibility of publishing national genomic evaluations for residual feed intake (RFI) based on the data generated by the 5-year national feed intake project funded by USDA National Institute of Food and Agriculture (NIFA), involving several research groups. Additional RFI data on new generations is needed to maintain and improve reliability of the predictions and therefore the CDCB is developing a proposal of a “Sponsored Program for Feed Efficiency Data Collection”.

Gestation Length Evaluations

Following a favorable recommendation from the CDCB’s working group Genetic Evaluation Methods (GEM), the CDCB Board approved the implementation of gestation length evaluations for service sires as an isolated trait (not included in the profitability indices) at the CDCB August 2017 official evaluations.

Public Relations and Promotion

After careful evaluation of the applications received, CDCB has engaged Look East from Gladstone, MO, to conduct CDCB’s public relations and promotion activities. The contact person is Amy te Plate-Church, who has about 20 years of dairy industry experience.

Genomic Nominators Workshop

The first-ever CDCB Genomic Nominators Workshop was held at the Maritime Conference Center, Linthicum Heights, MD, on May 17. About 25 personnel attended, representing artificial insemination companies, breed associations, genomic laboratories and NDHIA. The event objectives were to review the genomic nomination process, exchange experiences among genomic nominators and present the quality certification evaluation procedures to be adopted in 2017.

2017 CDCB Industry Meeting

Save the date!
October 3, 2017, 8:30 AM – 1:30 PM CDT.
Alliant Energy Center on the World Dairy Expo grounds.


Canadian Base Change Summary

Each year, the genetic base used to express genetic evaluations in Canada is updated in conjunction with the first official release. The definition of each genetic base used is therefore as follows:


Breed(s) Traits Genetic Base Definition Used
All Production Cows born during a 3-year period centred seven years ago (2009, 2010 or 2011) that have test day records in the Canadian Test Day Model genetic evaluation analysis.
Holstein Conformation Proven bulls born in the most recent complete 10-year period (2002 to 2011).
Coloured Conformation Proven bulls born in the most recent complete 15-year period (1997 to 2011). For Canadienne and Milking Shorthorn breeds, the base period starts with proven bulls born in 1984 and for the Guernsey breed it starts with proven bulls born in 1994.

The table below indicates the amount of base change realized in 2017 compared to 2016 for each trait and breed. For LPI, the following base adjustments reflect the change to the new scale with half the variance compared to previous years.

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Important changes to Holstein UK genetic evaluations for type traits in April 2017

As of April 2017, Holstein UK genetic evaluations for type traits will no longer be calculated by CDN in Canada. This service will now be provided by AHDB Dairy and their contract partners SRUC/EGENES in Edinburgh.

This move has provided an opportunity to review the type evaluation process and a number of important changes are being implemented in April 2017, which are set out below;

1) Type traits will be expressed on a reduced scale, which will result in less extreme values for young genomic bulls in particular. Type scores for the majority of bulls will now lie within 3 standard deviations (or 3 points) from the population mean.
For reference, the table below gives some statistics related to all available Holstein sires;

TM rank Current New
Top TM 4.76 3.73
Top 10 3.79 3.23
Top 25 3.49 3.06
Top 50 3.56 2.84
Top 100 3.37 2.68

2) An enhanced international and genomic evaluation for locomotion will result in more accurate PTA being calculated for this trait. This improvement will result in some bulls having a substantially different PTA result in April 2017, as compared with their previous published value. This is in accordance with an increase in the reliability of their PTA.

3) International daughter information will continue to be included in the calculation of type results for daughter proven sires, even when they reach the standard of ten effective UK daughters. This will allow for a smoother transition of results for those bulls which initially only have international daughters and then gradually acquire UK daughter information.
If you have any queries about these changes please contact;

Darren Todd Direct: 01923 695275
Mobile: 0770 3647139

Marco Winters Direct: 01978 760797
Mobile: 07980 545469

Proposed changes to evaluation system (April 2017)

Cow livability and revised body weight composite in net merit

By Paul VanRaden and Tom Lawlor 

Cow livability (LIV) was introduced as a new trait in August 2016 and is now included in lifetime net merit dollars (NM$). Cows that die are assumed to generate $1,200 less income than those sold for beef. Relative emphasis on LIV in December 2016 NM$ is 7%, but is counteracted by decreasing the relative emphasis on productive life (PL) from 19% to 13%. This revision does not change the expected genetic progress for PL but will cause more progress for LIV and healthier cows. 

Body size composite (BSC) was updated by Holstein USA in August 2016 to better predict actual body weights, and that change is now also used in NM$. The previous formula for BSC is replaced by the new formula for body weight composite (BWC):

BSC = .5 * stature + .25 * strength + .15 * body depth + .10 * rump width

BWC = .23 * stature + .72 * strength + .08 * body depth + .17 * rump width – .47 * dairy form

Major differences are that BWC is estimated from much more recent data, each unit of BWC is associated with larger differences in body weight than those of BSC, and BWC uses dairy form to account for presence or absence of fat in addition to skeletal size. Composites for other breeds were updated with this same formula except that Jerseys and Brown Swiss are not scored for body depth, so the .08 for body depth was added to the .72 for strength in those breeds. The standard deviation of predicted body weight has increased, and this causes more negative emphasis in NM$ (-6% on BWC vs. -5% previously on BSC). Genetic correlations of BWC with other traits also differ from those previously used for BSC:

Body depth 
Rump width 
Dairy form 

Therefore, use of BWC instead of BSC in NM$ reduces the selection against stature, body depth, rump width, and dairy form. 

Economic values for other traits were updated with 2 additional years of price data, resulting in small reductions in milk price, a shift in value of fat relative to protein, and less emphasis on somatic cell score. For recent bulls, the 2017 and 2014 NM$ indexes were correlated by 0.99. Further details are provided HERE

Revision of heterosis adjustments

By Paul VanRaden, Gary Fok, and Mel Tooker

Heterosis adjustments had been computed incorrectly for 14 of the 58 Montbeliarde bulls and 5 of the 34 Simmental bulls with US daughter records. Most Montbeliarde and Simmental bulls have pedigrees containing ancestors of more than 1 breed and their pedigree breed composition was stored in a table for crossbreds, but some have purebred pedigrees and were not in the table. For those bulls, the default heterosis value of 0 for purebreds had been used and was correct for the animal’s own heterosis, but should have been 100% for the expected heterosis of progeny because the bull’s breed differs from its breed of evaluation. Their predicted transmitting abilities (PTAs) will increase by 9 pounds protein, 20 pounds fat, and 2.7 daughter pregnancy rate (DPR) for example when their expected heterosis adjustment is corrected. None of the top 10 Montbeliarde or Simmental bulls were affected. This problem was detected while designing new programs to convert PTAs from the all-breed to within-breed scales.

Heterosis adjustments were also incorrect for traditional PTAs of crossbred cows. Those adjustments had been programmed separately and used the cow’s own heterosis instead of the expected progeny heterosis as intended, which is usually only half as large, and therefore PTAs of crossbred cows received too much adjustment. Cows with maximum of 100% heterosis (F1 crossbreds) will have their traditional PTAs decreased by 4.5 pounds protein, 10 pounds fat, and 1.4 DPR, with proportionally smaller decreases for cows with less heterosis. Differences from this adjustment are fairly small because the expected future inbreeding (EFI) differences between crossbreds and purebreds account for most of the total heterosis effect, and the EFI adjustments were applied correctly. Genotyped cows will be much less affected by this heterosis adjustment because the marker effects receive more emphasis than the traditional PTA, and because genotypes for crossbred cows that do not pass the breed check edits are not evaluated.

Correction of SCS parent averages for non-genotyped heifers

By Ezequiel Nicolazzi, Gary Fok, and Paul VanRaden

A coding mistake introduced in the August 2016 evaluation caused females to receive a better SCS (traditional) evaluation than they should have and, as a consequence, also their other (traditional) evaluations that use SCS information such as multi-trait productive life and net merit were impacted. Some nongenotyped heifers had received net merit values that seemed to be incorrect. Upon investigation, the cause was determined to be a bug in one of the computer programs that handles cow unknown parent group contributions to SCS traditional evaluations. This bug was introduced just before the August 2016 evaluation. Please note that due to the nature of the group of animals involved, this issue affected mainly heifer parent averages that were not public, and therefore released only to Dairy Records Processing Centers. This, and the fact that genomic evaluations were not affected, is probably the reason why the bug went unnoticed for so long. We have now fixed the bug and tested the program in order to avoid this event from propagating further. We thank Bill Verboort for reporting this problem after the December triannual run, and we are sorry for the inconvenience.

Some non-

Revision of rear udder width for Brown Swiss

By Ezequiel Nicolazzi and Jan Wright

Interbull evaluations for rear udder width (RUW) will now be used for Brown Swiss, which is the only breed with RUW evaluations from Interbull. In April 2017, RUW for Brown Swiss will be published according to the following criteria:
1) if a bull has a traditional or Interbull evaluation, then the evaluation with the highest reliability – usually Interbull – will be considered as the official value for RUW.
2) if a bull does not have either of the above evaluations (please remember there is no direct genomic evaluation on this trait), then the official value of RUH will be used as the official value for RUW.
Other breeds are not affected by this change.

Breed Canadian and Benefit from International Exposure

There are many advantages to genotyping heifers as part of an overall herd management program including improved decisions for selection and mating. An added benefit lies in the potential to create animals of interest genetically for both domestic and foreign markets. When marketing animals domestically, GLPI or Pro$ are the indexes of choice for the vast majority of buyers. Breeders from our largest genetic export market, the United States, will likely be interested in an animal’s GTPI or genomic Net Merit (NM$) value. Extra fees beyond the initial cost of genotyping are charged when these foreign indexes are requested for any Canadian animal. In this article, we help Canadian breeders estimate a genotyped animal’s GTPI or genomic NM$ based on their GLPI or Pro$.

National Indexes

Canadian Dairy Network (CDN) calculates both national selection indexes, LPI and Pro$. These indexes are designed for Canadian breeders and producers to maximize profitability depending on their breeding goals. The U.S. also has two national selection indexes, TPI and NM$. TPI is calculated by Holstein USA, while NM$ is calculated by CDCB (Council for Dairy Cattle Breeding). Holstein Canada acts on behalf of Canadian breeders interested in receiving a U.S. genomic evaluation and facilitates the payment of the required fees. For Holstein females, the additional fee for obtaining U.S. genomic evaluations is currently $20 CAD.

Screening Based on GLPI

In Canada, official genomic evaluations including GLPI and Pro$ are released on a weekly basis for all newly genotyped females. These evaluations are available on the CDN website at noon EST on Tuesdays. In addition, genomic reports are available after signing in to your Holstein Canada online account. For males, the same process is used but the resulting genomic evaluations delivered to the bull owner are unofficial and therefore not presented on the CDN or breed association web sites.

To assist breeders in deciding whether or not to pay for receiving a U.S. genomic evaluation, CDN has related GLPI values for Holsteins in Canada to their GTPI values in the U.S. Figure 1 shows the relationship between GLPI and GTPI values for over 30,000 genotyped Canadian heifers. The correlation between these overall indexes is relatively high at 94% so knowing the GLPI of an animal in Canada provides an excellent indicator of how high its GTPI may be in the U.S. For example, if an animal has a GLPI of 3000, then following that line up in the graph will show that it crosses the solid dark line very close to 2400 on the GTPI scale, which means they are essentially equivalent on average. The actual data points show, however, that among all animals at 3000 GLPI, the range in their GTPI is broader from roughly 2200 to 2600. In terms of confidence intervals, 90% of the animals will have a GTPI that is within ±145 points from the predicted level indicated by the dark solid line, regardless of their GLPI in Canada. For the example above, this means that 90% of all animals that have a GLPI of 3000 will have a GTPI value between 2255 and 2545 (2400±145). 

Another way of analyzing the same data is presented in Table 1, which shows the probability that an animal’s GTPI surpasses specific levels depending on its GLPI value. For example, a heifer or young bull with a GLPI that rounds to 3200 has a 3% chance of reaching a GTPI of 2700 or higher and an 23% chance of surpassing 2600 GTPI. Considering low GTPI levels, there is a 93% chance that an animal with 3200 GLPI reaches at least 2400 GTPI and it is essentially certain that they will pass the 2300 GTPI mark. 

Similar to the analysis above done for GTPI, the association between Pro$ and genomic NM$ was examined. Figure 2 shows the plot of these values for genotyped Canadian Holstein heifers, which are also highly correlated at 93%. Table 2 shows the probability that an animal’s’ genomic NM$ surpasses specific levels depending on its genomic Pro$ value.

The strong association between GLPI and GTPI, as well as between genomic Pro$ and genomic NM$, means that knowing the GLPI or Pro$ of an animal in Canada provides a great indicator of the level of its U.S. index values.  As Canadian breeders you can focus your selection and mating decisions on either GLPI or Pro$ and then identify those heifers for ordering genomic evaluations from the United States to increase the international exposure of your top genetics.

Lynsay Beavers, Industry Liaison Coordinator, CDN
Brian Van Doormaal, General Manager, CDN
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Holstein Association USA Adds New Traits to Official Holstein Pedigrees™

Holstein Association USA is pleased to announce that three new traits have been added to Official Holstein Pedigrees. Feed Efficiency, Fertility Index, and Sire Calving Ease are now displayed on all versions of the pedigrees for the subject animal, sire and dam.

Three new traits have been added to the Official Holstein Pedigree. You will now find Feed Efficiency (FE), Fertility Index (FI), and Sire Calving Ease (SCE) listed. Here is an example of a Pedigree with the new traits highlighted in a red box.

“Feed Efficiency and Fertility Index are two newer traits which are both included in the TPI® formula, and we wanted to make them widely available for anyone to see for any Registered Holstein®,” said Lindsey Worden, Executive Director, Holstein Genetic Services. “Sire Calving Ease is another trait which many breeders requested to have added to pedigrees, so we are happy to be able to make all of that information publicly available and easily accessible.”

Official Holstein Pedigrees may be ordered online at, or printed pedigrees may be ordered by calling Customer Service at 800.952.5200. Holstein COMPLETE™ members receive free internet pedigrees, up to the number of cows they have enrolled in the program.

For more information, contact Ashley Mohn, communications coordinator, at 800.952.5200, ext. 4128, or via e-mail at

Holstein Association USA, Inc.,, provides products and services to dairy producers to enhance genetics and improve profitability–ranging from registry processing to identification programs to consulting services.

The Association, headquartered in Brattleboro, Vt., maintains the records for Registered Holsteins® and represents approximately 30,000 members throughout the United States.

Zoetis and Holstein Association USA Release Top-Ranking Bull Lists With Genomic Predictions for Wellness Traits

Zoetis and Holstein Association USA announce the release of new lists identifying top-ranking bulls for wellness traits available through CLARIFIDE® Plus from Zoetis. CLARIFIDE Plus is the first commercially available, U.S.-based genomic test that offers dairy producers the ability to directly predict disease risks in Holstein cattle. The bull lists will include official industry rankings for the Dairy Wellness Profit Index™ (DWP$™) and Wellness Trait Index™ (WT$™). The two economic selection indexes provide a path for dairy producers to rank and select for comprehensive genetic improvements. With advanced genomic predictions for wellness traits, CLARIFIDE Plus provides direct indication of the genetic risk for six of the most common and costly animal health diseases: mastitis, lameness, metritis, retained placenta, displaced abomasum and ketosis.

“We felt it was important to develop these top-ranking bull lists as another tool to help producers use the technology more effectively, and we have received consistent feedback from Zoetis and Holstein Association USA customers asking for this resource,” said Cheryl Marti, associate director, U.S. Marketing, Dairy Genetics and Reproduction, Zoetis. “We’ve been very pleased to see such enthusiasm and recognition for the benefits of CLARIFIDE Plus to help progress the dairy industry and overall herd health and profitability.”

With the published lists, producers can view top market choices for bulls available through participating artificial insemination (AI) organizations. These lists make it easier for Holstein producers to identify bulls that meet overall profitability goals including production, reproduction, longevity, health and now wellness traits.

New Top-Ranking Bull Lists Available
The four new bull lists available through the Holstein Association USA website include:
• Top DWP$™ bull list for daughter-proven bulls
• Top DWP$ bull list for genomic young bulls
• Top 50 WT$™ bull list for daughter-proven bulls
• Top 50 WT$ bull list for genomic young bulls

Bull information for the top-ranking lists is compiled from propriety wellness traits from Zoetis, combined with traits available from the Council on Dairy Cattle Breeding (CDCB) genetic evaluation. The information is being made available through consenting AI organizations.

“With more than 30,000 members making up our association, we work to keep their operations as healthy and profitable as possible,” said Lindsey Worden, executive director, Holstein Genetic Services, Holstein Association USA. “Working with Zoetis to integrate CLARIFIDE Plus wellness traits into accessible lists for our members is one great example of such efforts.”

CLARIFIDE® Plus gives producers the most comprehensive package of trait predictions for Holstein cattle. Visit for more information.

About Holstein Association USA
Holstein Association USA, Inc., provides products and services to dairy producers to enhance genetics and improve profitability of Holstein cattle, ranging from registry processing and identification programs to consulting services. Headquartered in Brattleboro, Vermont, Holstein Association USA maintains the records for Registered Holstein® and represents approximately 30,000 members throughout the United States. For more information, visit

About Zoetis
Zoetis (zô-EH-tis) is the leading animal health company, dedicated to supporting its customers and their businesses. Building on more than 60 years of experience in animal health, Zoetis discovers, develops, manufactures and markets veterinary vaccines and medicines, complemented by diagnostic products and genetic tests and supported by a range of services. Zoetis serves veterinarians, livestock producers and people who raise and care for farm and companion animals with sales of its products in more than 100 countries. In 2015, the company generated annual revenue of $4.8 billion with approximately 9,000 employees. For more information, visit

Communication on rear udder width PTAs in breeds other than Holstein

cdcb_logo-58691It came to our attention that some bulls PTAs for rear udder width (RUW) in breeds other than Holstein had larger than normal changes.

The reason for these results is new genetic correlation estimates were implemented in December. In the August run, using genetic parameters obtained in 2003, rear udder height (RUH) had the highest correlation (0.85) with RUW and was therefore used to fill missing values for RUW. The new genetic correlation estimates available, showed a decrease to 0.67 in genetic correlation of RUH with RUW. Since now dairy form had the highest correlation (0.75) with RUW, it was used as the substitute trait instead of RUH. Holsteins continue to use RUH as the substitute trait because the correlation with RUW is very high (0.92). Genomic PTAs have not been computed for RUW because RUW is not exchanged in multi-trait across country evaluation (MACE), except for Brown Swiss. Instead, genomic PTAs for RUW are computed from the most correlated trait, which is now dairy form in breeds other than Holstein.

Here are some examples for some bulls:


As you can see above, Dairy form and RUH do not change substantially. On the contrary, consequence of the change in correlations, RUW does change for single bulls – although population-wise mean and standard deviation of RUW has only minor variation. Even if actual numbers in the above example seem different, both solutions are correct. The update in genetic parameters is required to better reflect the data currently used for genetic and genomic evaluations. Using Dairy Form rather than RUH makes RUW estimation more accurate, as new correlations between Dairy Form and RUW are higher. It is highly important to underline that this change is not affecting only a specific bull or group of bulls. This modification affects all the population similarly, for all the bulls on all breeds other than Holstein. Also note that this procedure to fill missing traits has been used for about 20 years.

We acknowledge there is room for improvement for these traits. RUW PTAs from MACE could be used for Brown Swiss (the only breed with MACE evaluation for RUW), or missing PTAs for foreign bulls could be filled before rather than after the genomic evaluation, or Interbull could include RUW in MACE for the other breeds. However, all these solutions require research and development and cannot be applied in a very short time. Note also that in the December run, Interbull added 10 more MACE conformation traits for Brown Swiss that are not scored in the United States and are not evaluated in other breeds.

Huge Milk Data Release to Contribute to Cattle Breeding in Scottland

National Milk Records has shared 9 billion rows of data gathered via routine milk recording with AHDB Dairy, which heralds the starting point for developing exciting new breeding traits, according to the levy board.

“Identifying and breeding cows that can produce the same amount of milk but from less feed is vitally important to maintain the sustainability of the GB dairy industry,” says NMR Managing Director Andy Warne, who made the historic handover.

Mr Warne explains how milk samples will help achieve this: “Each milk sample we test generates 1,060 data points that can tell us more about the health of the cow. We’ve used the data already as part of our Energy Balance service and it’s this information that will help us breed more efficient cows in the future.”

The new feed efficiency traits could be available as soon as next year and will be another tool to help producers improve their profitability. “We anticipate we’ll be able to provide genetic information for all the Holstein bulls used across the industry because of the volume of data,” says Marco Winters from AHDB Dairy.

Working with the EGENES department at Scotland’s Rural College, NMR and AHDB aim to develop new breeding traits linked to feed efficiency. Once available, the new traits will also be combined with genomic testing.


Source: The Cattle Site

Selection for Increased Resistance to Metabolic Diseases

Every dairy producer has faced metabolic disease in their herd. Metabolic diseases are heavily influenced by management; particularly by nutrition through the transition period. As with all diseases, however, a genetic component also exists which means that certain animals are genetically more or less susceptible to metabolic disorders. Starting December 2016, Canadian Dairy Network (CDN) will publish genetic evaluations for Metabolic Disease Resistance (MDR) in the Holstein, Ayrshire and Jersey breeds. With this new tool, producers will be able to select for increased resistance to these costly diseases. Read on to learn more about the development and interpretation of the Metabolic Disease Resistance index and the traits behind it. 

Clinical Ketosis, Subclinical Ketosis and Displaced Abomasum

The impact of ketosis tends to be under predicted on most farms. Clinical ketosis is observed in a visibly ill animal, while subclinical ketosis often remains undetected unless a herd monitoring program is in place. Either form of ketosis leads to excess concentrations of ketones circulating in the bloodstream in early lactation as a result of negative energy balance. Ketosis can lead to other metabolic diseases, impairs immune function and can also lead to reduced reproductive performance, reduced milk production, and an overall increased risk of being culled. In general, higher parity cows experience higher volumes of total lactation milk loss after a ketotic episode.

Cows with ketosis are also more likely to experience a displaced abomasum with the majority of cases occurring soon after calving. An accumulation of gas in the abomasum, often caused by inadequate feeding and management, can cause this stomach to move up in the abdomen, generally to the left side of the body. Surgical intervention is often required and cows that have had a displaced abomasum have shown to produce over 300 kg less milk during the lactation. 

Where Does the Data Come From?

A national system for collecting health events has been in place since 2007. Since that time, approximately 40% of all herds enrolled on milk recording have been voluntarily recording the incidence of eight key diseases and reporting this data to their milk recording agency. This accumulation of data has led to the calculation of genetic evaluations for Mastitis Resistance since August 2014. Effective December 2016, this source of data collection will also be used to produce genetic evaluations for Clinical Ketosis (CK) and Displaced Abomasum (DA).  In addition, DHI laboratory analysis of milk samples for levels of BHB (i.e.: milk beta-hydroxybutyrate) serves for calculating genetic evaluations for Subclinical Ketosis (SCK). The overall index for Metabolic Disease Resistance combines evaluations for these traits into a single value for genetic selection to reduce incidence rates in Canadian dairy herds.

Metabolic Disease Resistance – The Details

Metabolic Disease Resistance (MDR) combines evaluations for six traits in total, including Subclinical Ketosis, Clinical Ketosis and Displaced Abomasum, each of which is evaluated separately for cows in first lactation compared to later lactations.  To improve the accuracy of these evaluations, the genetic evaluation system also includes two indicator traits, specifically the ratio of fat to protein production in early lactation and the Body Condition Score in first lactation. In general, the relative weight on each trait in MDR is 50% for Subclinical Ketosis and 25% for both Clinical Ketosis and Displaced Abomasum. MDR has an estimated heritability of 7% and evaluations are expressed as Relative Breeding Values (RBV) with a scale that averages 100 and generally ranges from 115 for the best animals to 85 for the worst. For sires, the official status for MDR will be the same as for Subclinical Ketosis in first lactation since this trait will generally have the most daughter information included.

Due to the amount of data currently available for these diseases, CDN will publish MDR evaluations only for the Holstein, Ayrshire and Jersey breeds. In addition, genomic evaluations for MDR will only be available for the Holstein breed due to the limited number of reference sires available for Ayrshire and Jersey. 

Metabolic Disease Resistance – The Impact

Table 1 shows the relative weight that each of the three metabolic diseases have in the index for Metabolic Disease Resistance (MDR) as well as the overall percentage of healthy cows in the Holstein breed for each metabolic disease. As expected, the incidence of each disease generally increases as cows get older.

As seen in Figure 1, comparing the percentage healthy daughters for sires that are highly or poorly ranked for MDR clearly shows value in genetic evaluation and selection programs based on this index to improve the resistance to all three metabolic diseases. For Holsteins, a 10-point difference between sires for MDR translates to an expected increase of healthy daughters by 5.5% for subclinical ketosis, 2% for clinical ketosis and 2% for displaced abomasum.

Metabolic disease can play a significant role in affecting the profitability of dairy farms. Combining good management practises, especially for cows during the transition period and early lactation, and the Metabolic Disease Resistance (MDR) index for genetic improvement is the ideal approach to minimizing the impact of these diseases in your herd. Given the 20% correlation that MDR has with both Pro$ and LPI some genetic progress has been achieved for these traits but producers now have the opportunity to make direct selection and mating decisions.

Lynsay Beavers, Industry Liaison Coordinator, CDN
Brian Van Doormaal, General Manager, CDN

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Council on Dairy Cattle Breeding 2016 Industry Meeting

c[1]The Council on Dairy Cattle Breeding will be hosting its 2016 Industry Meeting on October 4, 2016 at the Alliant Energy Center. Dairy farmers and representatives from all sectors of the dairy breeding industry are welcome to attend in connection with the World Dairy Expo activities. The CDCB is a cooperation between dairy records providers (DRPs), dairy records processing centers (DRPCs), the Purebred Dairy Cattle Association (PDCA) and the National Association of Animal Breeders (NAAB), and its mandate is to host and administrate the U.S. national database of dairy records, to provide benchmarks and to carry out the official dairy genetic and genomic evaluations. The CDCB annual Industry Meeting is an opportunity to provide feedback to the stakeholders on the progress made, the current activities and the future developments.

The program of the 2016 Industry Meeting consists of an initial session of progress reports, including Board actions, staff activities, finances, research and development provided by USDA/ARS/AGIL and Interbull news. The process of defining AGIL’s next five-year research programs will also be presented as part of the reports, as well as the results obtained by the 2016 CDCB Summer internship student.

Then the focus of presentations will turn into the benefits provided to the dairy farmers by the CDCB in collaboration with member organizations. Starting with the efforts to ensure data quality flowing into the system, the invited speakers will also present how the availability of recessive haplotypes and genomic inbreeding estimates enhances dairy herds’ management, what is being done to develop genomic evaluations for health traits and the opportunities offered by genomic sequencing techniques. Cow livability evaluations, the latest product launched by the CDCB, will be introduced to the audience as well.

Finally, different perspectives about where the dairy industry is heading to will be presented as an effort to identify the challenges and opportunities that the dairy industry will be facing in this era of change.

The 2016 Industry Meeting venue is conveniently located inside the World Dairy Expo grounds and holds up to 200 attendees. All interested to participate are gently requested to complete an online pre-registration form prior to attending. The deadline to register is September 16, 2016.

CDCB Hires Dr. George Wiggans

unspecified[1]The Council on Dairy Cattle Breeding (CDCB) is pleased to announce that Dr. George R. Wiggans who retired in June 2016 after serving 38 years as a Research Geneticist with the Agricultural Research Service of U.S. Department of Agriculture is employed on a part-time basis as a consultant with the CDCB since August 2016.

Dr. Wiggans had a productive career with USDA as evidenced by his 335 publications. He has been the recipient of numerous awards including the Jay L. Lush Award (1996) and Fellow Award (2012) from the American Dairy Science Association, National Association of Animal Breeders’ Research Award (1996), National Dairy Herd Information’s Outstanding Service Award (2006), and the American Dairy Goat Association’s Mary Farley Award (2000).

Dr. Wiggans has made numerous contributions to improving the accuracy of genetic evaluation procedures for economically important traits of dairy cattle and goats. He will be providing expertise to CDCB in areas concerning improved management and genetic of dairy cattle, particularly in assisting CDCB gain operational efficiency in the evolving genomic era. The CDCB is pleased to have the opportunity to benefit from Dr. Wiggans’ expertise and welcomes George into the team.

Understanding Pro$ and the Lifetime Profit Curve

August 2016 marks one year since the introduction of Pro$ as one of Canada’s national genetic selection indexes. Since its inception, Pro$ has been well received by both producers and industry personnel. As a genetic selection tool, Pro$ maximizes genetic response for lifetime profitability, leading to realized daughter profit on farm. The accumulated profit a cow achieves over her lifetime depends on several contributing factors, all of which are reflected in the Pro$ index. Let’s take a closer look to better understand how Pro$ can help Canadian producers develop a herd of profitable cows.

Lifetime Profit Curve

From the day a heifer calf is born, she starts to incur costs, the majority of which are related to feeding. With an average age at first calving near 26 months, the cost of heifer rearing is roughly $2,800 for Holsteins. Once calved and lactating, a dairy cow starts to generate her primary source of revenue – milk and its components. At the end of each lactation, no revenue is generated during the dry period but expenses continue. This concept of describing how a cow’s profit accumulates over time is its lifetime profit curve, which is shown in Figure 1 for the typical Canadian Holstein. This lifetime profit curve covers the first six years of life since this was the definition of lifetime profit used by Canadian Dairy Network (CDN) to develop Pro$.

For the typical Holstein in Canada, the complete repayment of costs incurred from birth is achieved by 40 months of age, at which time she is in her second lactation (Figure 1). Looking closely, it can be seen that each new dry period and subsequent calving leads to higher levels of accumulated lifetime profit compared to the scenario of a cow having only one calving followed by years of consecutive production.  Normally, prior to reaching six years of age, the typical cow will have had four calvings, including three dry periods, and is in progress on her fourth lactation.  This underlying cycle of reproduction and production is fundamental to the dairy enterprise since heifer calves are required as future replacement animals for the milking herd. On average, about one-third of all lactating Holsteins in Canada stay in the herd to at least the age of six years.  Those that do, typically end up with about 40 months of productive life in lactation along with six months for dry periods.

When producers aim to maximize herd profitability, it is important to think of the factors contributing to each cow’s lifetime profit curve, which include:

  • Age at first calving since prior to this point a heifer only incurs costs.  The earlier an animal first calves, the sooner it can start paying back those rearing costs.
  • Production levels of milk, fat and protein since these are the primary sources of revenue but they are also associated with some expense, mainly feed costs.
  • Days in lactation since this is the only period during which revenue is generated.
  • Days dry, which is longer with poorer reproduction.
  • Ability to stay in the herd, which reflects a multitude of possible factors.

When examining Pro$ values, higher bulls are expected to produce more profitable daughters compared to lower Pro$ bulls.  This means that the average lifetime profit curve for daughters of high Pro$ sires will be somewhat different, and higher, compared to daughters of poorer Pro$ sires. CDN recently conducted an analysis to help demonstrate how the key factors contributing to a cow’s lifetime profit curve vary between sires that are higher or lower for Pro$.  To conduct this analysis only older sires could be used since their daughters would have to have been born early enough to have had the opportunity to reach six years of age. Table 1 provides various statistics describing the performance of daughters of the sires that were in either the top 10% for Pro$ of the group included in the analysis, or the bottom 10% for Pro$, relative to the daughters of the middle 10% of sires for Pro$.

Relative to daughters of the middle group of sires for Pro$, 7.4% more daughters of the top Pro$ sires and 6.0% fewer daughters of the bottom Pro$ sires stayed in the herd to six years of age. Evidently, longevity is a crucial component of lifetime profitability. By looking specifically at the daughters that stayed in the herd until at least six years of age, we can illustrate the profitability differences, beyond longevity, that exist between the two sire groups based on Pro$. For example, daughters of the top group for Pro$ calved younger, had more days of productive life and produced more milk, fat and protein than daughters of average Pro$ sires. On the other hand, daughters of the bottom sire group for Pro$ had an older age at first calving, fewer days in production, spent more days dry and produced significantly less than daughters of average Pro$ sires.

Since all these performance measures impact profitability, there is a clear difference in the average accumulated profit to six years of age, based on all daughters, for each of the two sire groups by Pro$. Daughters of the top sire group for Pro$ generated an extra $1,300 profit to six years than daughters of the middle sire group, while daughters of the bottom sire group generated $1,200 less profit to six years than daughters of the middle group. Bottom line is that selecting sires based on Pro$ produces daughters with higher lifetime profit curves and improved herd profitability.

Brian Van Doormaal, General Manager, CDN
Lynsay Beavers, Industry Liaison Coordinator, CDN

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New Body Size Composite An Improved Way To Estimate Body Weight


A key component to improving feed efficiency is being able to accurately estimate the body weight of our cows, and a good tool for that is linear classification.  As a part of the USDA multi-state research project on feed efficiency, Holstein Association USA classifiers scored 1,920 cows with weekly body weight and feed intake data, at seven different locations throughout the United States. Meanwhile, a similar study was conducted in the Netherlands on another 1,665 cows. This cooperative effort has led to more accurate predictors of body weight in both countries.

Results from the 2016 Feed Efficiency study indicate that an accurate prediction of body weight needs to include a measure of both body size, i.e., the dimensions of the cow, and dairy form. By including dairy form, we now take into account how hard that cow is working, and account for an excess or lack of body fat. A distinctive feature of our modern-day dairy cow is its ability to convert large amounts of roughage and feed into milk.  Bigger cows have greater mass or volume and tend to be heavier. But, they also tend    to eat more and produce more milk. When estimating the body weight of a cow, or the progeny of a bull, breeders need to take into account their frame, as well as their strength and   dairyness.

Dairy form measures how hard a cow is likely to work. High dairy form indicates a high level of production, where she’ll be carrying less body fat throughout most of her lactation. She’s more angular, open ribbed, and thinner. A cow with low dairy form is one who’s thicker through the neck, shoulders and ribs; is lower producing with higher body condition; and is heavier than her frame would   indicate.

The new Body Size Composite (BSC) is more complete and accurate by looking at both the size of the cow and how heavy she’s milking (how much extra condition she carries). A bull with an old BSC of +1.0 would be expected to sire offspring that were +24 pounds heavier than breed average; a bull with a new BSC of

+1.0 is expected to sire offspring that are +40 pounds heavier.

2016 Body Size Composite (BSC)

BSC = (.23 x Stature) + (.72 x Strength) + (.08 x Body Depth) + (.17 X Rump Width) – (.47 x Dairy Form)

Every 1.0 STA increase in body size correlates with a 40 pound predicted increase in mature body weight. For example, daughters of bulls that sire heavier cows (large positive evaluation for BSC, +3.00) are predicted to weigh 240 lbs. more than those bulls that sire lighter weight cows (large negative evaluation for BSC, -3.00).

Impact on Feed Efficiency

The Feed Efficiency Index has also been adjusted to reflect the change in Body Size Composite. Where we previously had a $7.44 deduction, that now changes to a $12.40 deduction, for each 1 unit increase in BSC.

2016 Feed Efficiency (FE)

FE = (-0.0248 x PTA Milk) + (1.16 x PTA Fat) + (2.18 x PTA Protein) – (12.4 x Body Size Composite)

New Cooperation on exchange of genotypes for genomic young Holstein bulls between North America and Germany

cdcbStarting with the August evaluation the members of the Cooperative Dairy DNA Repository (CDDR) including ABS Global, Accelerated Genetics, ALTA Genetics, CRI, Select Sires and Semex and the German Genomic Consortium (all German Holstein organizations) will routinely exchange the genotypes of all new young genomic AI bulls that are at least 10 month of age. The owners of the bulls will receive non-published genomic breeding values from the other country’s routine genomic evaluation. With these evaluations they can decide which bulls are to be published on the other country’s scale. As ‘Approved Partners’ both sides are granted beneficial fees for genomic evaluation and publication. The initial exchange included bulls 2,054 bulls from CDDR members and 484 bulls from the German associations. The exchange will continue monthly

Cow Livability: Breeding for Cows That Stay in the Herd

Quite often these days a new genetic index comes along that has been produced for breeders to use in their breeding plan. This month, August 2016, the new index is one that the Council on Dairy Cattle Breeding (CDCB) is calling Cow Livability (C.LIV). For breeders wanting their cows to live for many lactations, this will be a trait of interest.

What is Cow Livability?

CDCB is defining Cow Livability (C.LIV) as a prediction of a cow’s transmitting ability (aka genetic index) to remain alive while in the milking herd.

Every extended day that a cow remains milking in the herd gives the opportunity for more herd profit from more milk revenue and lower replacement costs. Cows that can remain alive when exiting the herd generating breeding stock or beef revenue, instead of the cost associated with deadstock disposal.

Facts About the USA Dairy Herd

It is interesting to note that CDCB reports that USA cow mortality rate averages 7% each lactation and death claims 20% of the USA cows while in the milking herd. On an annual basis that death loss costs the U.S. dairy farms $800 million or approximately $90 per milking cow per year.

How is C.LIV Different than PL?

CDCB provides the following explanation. “In contrast (to C.LIV), PL predicts how long a cow is expected to remain in the milking herd before dying or being culled.”

Livability is one of the traits that make up Productive Life, and it is economically important that cows remain alive, productive and not requiring another cow to replace her.

For decades, cow termination codes have been captured from DHIA herds with 32 million cows in CDCB’s database. Based on that extensive amount of data, CDCB has calculated correlations between C.LIV and PL of 0.70. So they are, in fact, different traits and breeders can expect to see that some sires may be ranked differently for the two traits.

Other Useful Traits

Already available, for a considerable time now, for breeders to use in breeding long-lived trouble free cows have been traits like PL and SCS.  But they only partially cover the spectrum of what breeders want to know. For instance, SCS does report the expected SCC level, but it does not cover if in fact a cow is able to resist mastitis. Each mastitis flare up, even though not life threatening, costs $400 (lost revenue, treatment, added labor, lost future production, etc.)  To address that, CDN now produces a genetic index for Mastitis Resistance. It includes factors (Read more: MASTITIS RESISTANCE SELECTION: NOW A REALITY!) beyond SCC.  Furthermore, Zoetis has now developed a Dairy Wellness Profit Index (DWP$) that is a genetic estimate of a cow’s ability to avoid or resist health problems or disease. (Read More: THE COMPLETE GUIDE TO UNDERSTANDING ZOETIS’ NEW WELLNESS TRAITS – CLARIFIDE® PLUS)

CDN has recently reported a three-year release plan for health and fertility traits.  In December 2016 it will publish a metabolic disease (ketosis & displaced abomasum) resistance index, in 2017 an index for resistance to fertility disorders (metritis & retained placenta) and in 2018 a hoof health index.

Considerable research is currently under way, and it will be interesting to see if breeds and/or bloodlines within breeds have different genetic capabilities for these added indexes. Many breeders feel that they detect differences between cow families for these various auxiliary traits.

What Do the Numbers Show for C.LIV?

The following CDCB table shows the importance of having high genetic indexes for individual traits when it comes to a sire having a high NM$ index.  All traits are directly or indirectly included the NM$ except for C.LIV.  That makes the comparison of C.LIV to NM$ truly independent.

Table 1 Average Genetic Index for USA AI Bulls (born after 1999), Grouped by Percent Rank for NM$

&RK for NM$Avg NM$Milk-lbsFat - lbsProtein-lbsDPRPLC.LIV
80 to 99588104352381.35.62.1
60 to 7942394434300.93.81.4
40 to 5931061225220.42.60.9
20 to 39197432181601.40.2
0 to 19-53-164-2-2-0.8-0.8-1.1

Soures: CDCB Article ” Genetic Evaluation for Cow Livability”

It is estimated by D Norman, CDCD and J Wright and P VanRaden, AIPL-USDA that having cows at 2.1 C.LIV compared to -1.1 C.LIV would be worth an additional annual net income of $9,400 (or $38.50 per cow) in the average USA DHIA herd of 244 cows.

CDCB reports that at some time in the future that C.LIV will be included in the four NM$ indexes replacing some of the current emphasis on PL. When that change is made CDCB sees the possibility that the combination of PL (14%) and C.LIV (7%) will move from the current 19% emphasis on PL in NM$ to 21% for PL plus C.LIV

Will These Functionality Traits Be Used?

For breeders that follow the concept of breeding for type and feeding for production, these functional traits are often regarded as a ho-hum issue.

However, for breeders wanting herds of cows that cause few problems, have minimal added expenses, and that remain in the herd a lactation or two longer than cows have in the past, then these additional traits, including C.LIV, will be important, when selecting the sires to buy semen from.

It is highly unlikely that there will be even one sire that is a standout for all functional traits. In fact, that is impossible. However, knowing bull ratings for added functional traits will allow breeds to avoid using sires that are below average for the traits that breeders find relevant to their breeding plan.

 The Bullvine Bottom Line

C.LIV is the latest, but certainly not the last, genetic index that will be available for breeders to use to breed functional, commercially profitable cows. Time will tell if it is useful. But the fact remains breeders need to consider all traits for which there are genetic indexes and then make informed choices about which ones to include in their sire selection plan.




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