Archive for Genetic Evaluation System

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
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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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New Genetic Evaluation For Cow Livabiliity

Breaking News ScreenWhen genetic evaluations for Productive Life (PL) were introduced by USDA’s Animal Improvement Programs Laboratory in 1994, U.S. dairy producers were handed an extraordinary opportunity to produce healthier cows. The good news is, it actually happened; when Predicted Transmitting Abilities (PTA) for Productive Life were incorporated into selection programs, the deterioration occurring in pregnancy rate for five decades (16 percentage points1) was soon reversed. In addition, genetic increases that were occurring in somatic cell score (SCS) that were revealed when PTA for SCS was initiated also were reversed and udder health improved as well. Now another genetic evaluation will be provided in August 2016 so producers will have a new tool to help even more. The new evaluation is PTA for Cow Livability (PTA C.LIV) which predicts cow’s transmitting ability to remain alive while in the milking herd. In contrast, PTA for Productive Life (PL) predicts transmitting ability for how long a cow is expected to remain in the milking herd before dying or being culled. Livability is just one of the several traits that determines Productive Life, yet one with a high economic influence that to date had not been accounted for adequately.

Populating US dairy herds with cows capable of longer productive life gave producers more opportunity for voluntary culling as they needed to dispose of fewer animals for health or management reasons. When a cow is sold for dairy or beef (voluntary or involuntary culling), the sale income is returned to the owner. In contrast, if a cow dies, or is euthanized as a consequence of ‘downer cow syndrome’, there is total loss of income. Just knowing which cows are likely to remain in the herd the longest is not the entire story. Instead, additional benefit comes from knowing which cows are likely to provide income at disposal. Because cow mortality rate averages 7% each lactation, death claims 20% of the U.S. cows while in the milking herd2. Conversely, 80% of cows remain alive permitting the producer to recoup their disposal income when they exit the herd. The lost ‘disposal income’ from current U.S. cows that will die is about $2.2 billion (20% × 9.2 U.S. million cows x $1200/cow) or $800 million per year.

Fortunately, in spite of the fact the heritability of mortality is low at 1.3%3, accuracy of PTA for Cow Livability is quite high as termination codes have been recorded in DHIA for decades. Over 92 million lactation records for 32 million cows have termination codes in the national database. As a result, genomic predictions having high accuracy can be derived for AI bulls for the new trait. Even the Reliability for young genomic tested bulls without daughters averaged 56%. Correlations between PTA for Cow Livability and PTAs for other traits have been calculated and vary considerably. For bulls having Reliability of 80% or higher, the correlation was 0.70 with Productive Life, 0.45 with Daughter Pregnancy Rate, but was rather low with the milk traits.

Cow Livability is defined such that if the cow died this lactation, the trait was set to 0%; if the cow lived through this lactation, it was set to 100%. To place it on a lifetime scale, the results are multiplied by 2.8 since average lactations per cow is 2.8. The table below show the average PTAs of animals that fall into the quintiles for Lifetime Net Merit $.

Table 1. Average PTAs of AI Holstein bulls with birthdates since January 1, 2000 for a number of traits* grouped by percentiles for Lifetime Net Merit Dollars (NM$).

80 to 99 +588 +1043 +52 +38 +1.3 2.2 +5.6 +2.1
60 to 79 +423 +944 +34 +30 +.9 2.2 +3.8 +1.4
40 to 59 +310 +612 +25 +22 +.4 2.2 +2.6 +.9
20 to 39 +197 +432 +18 +16 0 2.3 +1.4 +.2
0 to 19 -53 -164 -2 -2 -.8 2.4 -.8 -1.1

*PTA=Predicted Transmitting Ability, Prot=Protein, DPR=Daughter Pregnancy Rate, SCS=Somatic Cell Score, PL=Productive Life, C.LIV=Cow Livability

The top quintile of bulls for Net Merit Dollars had PTAC.LIV that averaged +2.1% while the bulls in the lowest quintile averaged -1.1%. This indicates the top quintile bulls will have about 3.2% more daughters that will not die during their milking life than will the lowest quintile bulls. Because the average of cow remaining alive throughout their entire milking life is 80%, a bull that is +2.1 is expected to have 82.1% of his daughters that remain alive while a bull from the lowest quintile is expected to average 78.9% (breed average of 80.0 – 1.1 = 78.9% that remain alive). This 3.2% difference in a 244 cow herd (the average DHIA herd size) would produce $9,400 in additional income.

Eventually the PTA for Cow Livability will be incorporated into all 4 lifetime merit indexes, but this will be completed after users become more familiar with the new trait. When this happens, the weight given to Productive Life is expected to decline from about 19 to 14%, and the emphasis assigned to Cow Livability will be near 7%. Thus, the total emphasis of cow longevity would increase to 21%.

Having Cow Livability is one more step toward adding value to the genetic information that will improve dairy producers’ profitability. Producers participating in DHIA can help to improve the reliability of this trait by accurately reporting the reasons why cows leave their herds.

Duane Norman works for the Council on Dairy Cattle Breeding; Janice Wright and Paul VanRaden are employees of USDA’s Animal Genomics and Improvement Laboratory.

1 Council of Dairy Cattle Breeding. 2016. Trend in Daughter Pregnancy Rate for Holstein or Red & White Calculated April 2016. Accessed June 1, 2016.

2 Norman, H.D., L. M. Walton, and João Dürr. Reasons that cows in Dairy Herd Improvement programs exit the milking herd (2014). CDCD Res. Rpt. (16-02). 2016. (Popular Publication)

3 Miller, R.H., M.T. Kuhn, H.D. Norman, and J.R. Wright. Death losses for lactating cows in herds enrolled in Dairy Herd Improvement test plans. J. Dairy Sci. 91(9):3710-3715. 2008.

Relationships of Rump with Fertility & Calving Performance

The dairy cattle breeding world has long promoted the importance of structurally sound rumps. Proper rump conformation has been touted as a promoter of fertility and calving ease. In this article we take a closer look at these relationships as well as genetic selection to improve them.

The Impact of Rump – Cow Level

At Canadian Dairy Network (CDN), we used recent classification, calving and breeding data in for over 60,000 first lactation Holsteins to quantify any phenotypic relationships that may exist between rump conformation with measures of calving performance and fertility. Rump conformation is assessed on a linear scale from 1 to 9 for Rump Angle, Pin Width, Loin Strength and Thurl Placement, which are combined into an overall score for Rump. Calving performance is measured both as calving ease and calf survival, which is the opposite of stillbirth rate. Measures of each cow’s fertility include the interval from calving to first service/insemination and the subsequent interval from first service to conception, with the sum of these together equalling days open.

Results of the analysis at the cow level indicate that some relationships exist between classification scores for rump traits and performance at first calving:

  • Very low pins (Rump Angle of 8 or 9) are associated with 2% easier calvings compared to cows with very high pins (Rump Angle 1 or 2)
  • Thurls too far back (scores of 1 or 2) are associated with nearly 3% more difficult calvings compared to other linear scores
  • The rate of calf survival is 5% higher for cows with very strong loins (scores of 8 or 9) compared to very weak loins (scores of 1 or 2)
  • Calf survival is 3% higher for cows with very low pins (Rump Angle of 8 or 9) compared to very high pins (Rump Angle of 1 or 2)

Although very little relationship was found between rump conformation and the interval from calving to first service, Figure 1 shows the significant association found between Rump Angle, Pin Width and Thurl Placement on the cow’s fertility when measured as the interval from first service to conception.

For Pin Width, it is clear to see that cows with very narrow pins (linear scores of 1 or 2) have conception delayed by 4 days compared to cows with pins assessed with a score of 5. Cows with very wide pins in this analysis also showed a delay in conception of one day.

The Canadian classification system for Rump Angle and Thurl Placement considers these traits as having an intermediate optimum. Cows with a linear score of 5 or 6 for Rump Angle are deemed ideal and a score of 6 is ideal for Thurl Placement. Figure 1 clearly supports this concept of intermediate optimum for both these traits since cows with linear scores at either extreme demonstrated poor conception rates. For Rump Angle, cows with very high pins had conception delayed by nearly 3 days compared to cows with a linear score of 5 and cows with very low pins also experienced a delay of one day. For Thurl Placement, cows scored at either extreme of the linear scale had conception delayed by an average of 2 days compared to those with the ideal score of 6.

The Impact of Rump – Sire Level

As mentioned earlier, type classification data for the four descriptive traits are combined to assign each cow an overall Rump score.  This score is used to calculate sire proofs for Rump, which is the primary tool for genetic selection to improve rump conformation. Table 1 shows proof correlations between Rump and selected key traits derived using data from 4,100 domestically proven Holstein bulls. Positive correlations above 10% are identified in green while negative correlations below 10% are labeled in red.

From these results, we can draw the following conclusions:

  • The negative correlation with Calving Ability indicates that sires with high Rump proofs tend to produce calves that have greater difficulty being born and/or surviving.
  • Daughter Calving Ability and Daughter Fertility are genetically unrelated to Rump in terms of sire selection, meaning that selection for Rump will not translate into genetic progress for these functional traits.
  • The positive correlation between Rump and Herd Life indicates sire selection can improve both of these traits at the same time.
  • Rump is positively correlated with both LPI and Pro$ so selection for either of these national indexes will result is genetic progress for Rump at the same time.

The positive correlation between Rump and LPI is of particular interest since Rump is not a trait that is directly included in the Holstein LPI formula. The genetic relationship between Rump with other traits in the LPI formula already translates to genetic gain for Rump. While it is useful to record individual rump traits and monitor breed trends over time, direct inclusion of Rump in the LPI formula is unnecessary since ample improvement can be made by using either national index as a primary selection tool. As a herd management tool, the Canadian classification system for rump traits aims to identify cows that will have better fertility and calving performance.

If improving rumps are important to you, either on a herd or individual cow basis, selection for rump traits will help you achieve your goals. If improving fertility and calving performance is important to you, good management combined with selection directly for the Daughter Fertility, Daughter Calving Ability and Calving Ability will get you there.

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

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Pin Setting and Set of Rear Legs: Termination of Publication in Canada

The conformation assessment program in Canada has included Rump Angle and Rear Legs Side View in all breeds for over 30 years. These traits are assessed by classifiers using a linear scale from 1 to 9 whereby an intermediate score of 5 or 6 is ideal for Rump Angle and 5 is ideal for Rear Legs Side View (see relevant sections from the Conformation Analysis sheet for Holsteins below).

Given the manner in which these traits are assessed, genetic evaluations are expressed using letter designations to reflect the expected outcome of an animal’s progeny, on average.  For Rump Angle, genetic evaluation values other than zero include the letters of either “H” to reflect a tendency towards high pins or “L” for a tendency toward low pins. Letters for Rear Legs Side View are “S” for a tendency toward straight legs or “C” for curved legs. Sires with a proof of zero are expected to produce more daughters with the ideal score for these traits.

Accompanying the publication of Rump Angle and Rear Legs Side View, CDN has also used the same classification data to publish genetic evaluations for analogous traits, Pin Setting and Set of Rear Legs, respectively. These traits have been published by CDN to facilitate the interpretation of evaluations by producers using a “desirability” scale whereby higher values towards +15 reflected sires that were most likely to produce daughters with the ideal/desired rump angle and rear legs when viewed from the side. At its most recent meeting in May 2016, the CDN Board of Directors approved the recommendation from its advisory committee, the Genetic Evaluation Board (GEB), to cease the publication of evaluations for Pin Setting and Set of Rear Legs effective the genetic evaluation release in August 2016.  The main reasons for this decision include:

  • The publication of two sets of evaluations for essentially the same trait has not been well understood by producers and industry personnel
  • These traits, expressed on the “desirability” scale have the lowest values of estimated heritability among all conformation traits, ranging from 2 to 7%, and are significantly lower than heritability values for the analogous traits of Rump Angle and Rear Legs Side View.
  • Internationally, most other countries publish genetic evaluations for Rump Angle and Rear Legs Side View, which are included in the MACE evaluation services offered by Interbull. Canada is the only country worldwide that has also published Pin Setting and Set of Rear Legs using the “desirability” scale.
  • With the arrival of genomic evaluations, observed gains in accuracy of prediction have been among the poorest for Pin Setting and Set of Rear Legs, reducing the value of these traits in current selection strategies.

To carry out the approved action and terminate the publication of genetic evaluations for Pin Setting and Set of Rear Legs, CDN has established the following implementation plan:

  • Data files associated with the August 2016 genetic evaluation release will no longer have actual values in fields associated with these two traits.  All such data fields will contain default values, which will be -99 for the actual genetic evaluation for all animals.
  • File formats for the December 2016 genetic evaluation release will be modified by excluding all data fields associated with Pin Setting and Set of Rear Legs.  The new file formats will also be modified to include data fields associated with the new Metabolic Disease Resistance (MDR) index, which will be introduced at that time for the Holstein, Ayrshire and Jersey breeds.
  • The CDN web site has been changed, effective immediately, to no longer display the genetic evaluations for these two conformation traits.  This affects each animal’s Genetic Evaluation Summary page as well as the Type Evaluation Details page for proven sires in Canada.
  • Industry partner web sites are also welcome to cease displaying evaluations for Pin Setting and Set of Rear Legs, when convenient in advance or at the time of the August 2016 release.
  • AI organizations are expected to exclude these traits from any proof sheets or other promotional materials, as well as genetic mating programs, effective August 2016, if not already excluded.

As genetic evaluation services offered by CDN continue to expand by adding new traits, it is also important to review the value of existing traits from time to time. The decision to terminate the publication of Pin Setting and Set of Rear Legs is an outcome of such a review without reducing the value of the conformation assessment program in Canada that includes Rump Angle and Rear Legs Side View.

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

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A Q&A on DWP$ and WT$

The Dairy Wellness Profit $ and Wellness Trait $ indexes may have you wondering whether you should adjust your genetic plan to include this new information. Here we have answers to 14 questions to help you decide what’s best for your dairy to make the maximum genetic progress in the direction of your goals!

What is Dairy Wellness Profit $ (DWP$) and Wellness Trait $ (WT$?)

These are genetic indexes calculated by Zoetis from producer-recorded data, in herds that are genomic testing or have genomic tested in the past.

How is the WT$ index compiled?

WT$ is a combination of the Wellness Traits (Ketosis, Displaced Abomasum, Retained Placenta, Metritis, Mastitis and Lameness). This means it is an index analogous to a 0-100-0 index, with 100% weight on health traits. However, those weights are divided between the various Wellness traits that Zoetis calculates.

Do each of the Wellness Traits get their own evaluation?

Yes. They are then combined into a Wellness Trait $ index to combine the expected impact.

How is DWP$ compiled?

DWP$ is a genetic selection index that equates to a genetic plan of 34% Production – 56% Health – 10% conformation. This differs from TPI (46-28-26) and the overall NM$ index (43-41-16).

The breakdown of the weight on health is different as well. DWP$ puts 30% of the weight on WT$, leaving 26% for the CDCB evaluated health traits of PL, DPR, SCS, DSB, DCE, CCR, HCR.

Are the Wellness traits developed by Zoetis?

The WT$ calculation is not a new concept, as it was first published in 2004, however this is the first routine evaluation and first genomic prediction for those traits.

Did Alta test all bulls for DWP$ and WT$?

No, but we tested the sires that we predicted would do well on the respective indexes based on their health trait values and how they rank on a 34% Production-56% Health-10% Conformation index. We are listing the top ten DWP$ sires and top five WT$ bulls in each of three categories: G-Stars, FutureStars and daughter-proven sires.

What is Alta’s testing plan going forward?

This will be dependent on the feedback from the customers and the demand for this information. In the short-term we will continue to test those sires that rank well on a traditional 34-56-10 index.

How can we predict which sires will do well on these indexes?

Because the correlation between DWP$ and a traditional 34-56-10 index is very high, we can predict quite well which sires will rank well on the DWP$ index.

How do these Wellness traits compare to Productive life?

Productive life encompasses every reason an animal leaves the herd, and the length of time she is productive compared to herdmates.

The Wellness traits are some of the exact reasons cows may leave, but instead measure incidence of disease, not departure from the herd. Of course many cows are affected, but do not leave the herd. Therefore the Wellness traits measure different things than Productive Life, however there is obviously a strong relationship between PL and WT$, with a stated correlation of 0.41. The relationship gets stronger if the combination of PL, DPR, and SCS is used, reinforcing that all the health traits are related to each other.

How should you use this information?

It’s still as important as ever to create your own, customized genetic plan based on your goals and the situation on your dairy.

Our stance at Alta has always been that the most important part of setting a genetic plan is getting the correct amount of weight in each of the three ‘buckets’ for production, health, and conformation – based on the current situation and future goals for your dairy. Once your genetic plan is decided, changing which individual traits are emphasized within each bucket will have far less impact.

If you select sires based on TPI (46% Production-28% Health-26% Conformation) or NM$ (43-41-16), the current DWP$ weighting of 34-56-10 puts significantly more weight on health than those two indexes, at the cost of production and conformation.

If your current genetic plan is set at 70-30-0, changing to DWP$ as a selection goal would be analogous to changing from 70-30-0 to 34-56-0. That doesn’t mean the change is wrong – it is just a VERY significant change, which should only be made because your goals or situation have changed, not just because there are new traits available.

However, if your genetic plan is set at 50-50-0, moving some of the 50% weight on health, and putting it towards the wellness traits, is a much less drastic adjustment.

Changing the bucket weights in a genetic plan is always a strategic decision. Therefore, plans should change only when economics or the situation on your farm changes, not just because new traits become available.

Is there anywhere else to get information on these traits?

In Canada, CDN has been calculating an evaluation on clinical mastitis for some time now, and those evaluations are readily available. They are also collecting data on each of the other five traits, and expect to have evaluations available within the next year.

In the Netherlands, these traits are routinely collected and evaluated. In the US, the CDCB is currently evaluating the possibilities to do genetic evaluations for these traits.

What is the correlation between DWP$ and other indexes?

The correlation between TPI and DWP$ is 0.89. The correlation between NM and DWP$ is 0.92. The correlation between a 34-56-10 index calculated with Alta’s Bull Search or AltaGPS is 0.94.

Are the Wellness traits heritable, or driven more by management?

Many traits that are heavily influenced by environment still have a genetic component, and the Wellness traits are no different. While the heritability of these traits ranges from 6%-8%, they should not be eliminated from a selection plan simply because of low heritability. Daughter fertility, Productive Life, and other traits also have relatively low heritability, but many herds have made substantial genetic progress, and see real results for these traits through genetic selection.

What is the reliability of the Wellness Traits?

The reliability of the Wellness Traits is ~0.50.  This is relatively low compared to other traits that are routinely selected for. This means more re-ranking can occur between animals as more data is gathered.

Comparatively, the reliability of other CDCB health traits such as PL, DPR, and SCS is around .70 on young AI bulls because there is more historical data available for these traits.

Reliability is a measure of the precision of an estimate, and the likelihood that estimate changes over time. It is NOT how likely traits are to pass from one generation to the next.

Source: Alta Genetics

To view a listing of Alta’s top 10 DWP$ and top 5 WT$ sires, please Click HERE.

Managing Recessives & Haplotypes

Does it feel like dairy cattle breeding has gotten more complicated? Truthfully… in some ways it has. We now know about many genetic recessives and haplotypes that negatively affect profitability, and in the future, we’re sure to find more. In this article, learn how these genetic anomalies work, how their impact can vary from one herd to another, and how you can manage them effectively.

How do Recessives and Haplotypes Work?

An animal carries two copies of a gene or haplotype (i.e.: short section of DNA strand), one inherited from their dam and the other from their sire. An animal is said to be either “homozygous” for a gene or haplotype, meaning they inherited the same DNA section from both sire and dam, or “heterozygous”, meaning the DNA section inherited from the sire and dam are different. Heterozygous animals are usually referred to as “Carriers”. Most genetic anomalies in dairy cattle are controlled by genes that are recessive in nature, rather than dominant, which is the case of all of the known haplotypes affecting fertility as well as HCD, the haplotype associated with cholesterol deficiency. For genetic recessives, only homozygous animals, which have inherited two copies of the gene or haplotype, are affected.  For the fertility haplotypes, affected animals die from early embryonic loss while HCD results in early calf mortality.

Figure 1 illustrates the possible outcomes when two known carriers are mated together. Using HCD as an example, in this situation, 25% of offspring will be homozygous dominant (AA) and unaffected, 50% will be heterozygous (AB) and unaffected but able to pass on the recessive gene, while another 25% will be homozygous recessive (BB) and die, likely before weaning.

Breed Frequency versus Herd Frequency

Haplotypes affecting fertility work in the same manner outlined above, only a lost early pregnancy is the result. There are five haplotypes known to affect fertility in Holstein, two known in both Jersey and Brown Swiss, and one known in Ayrshire. These haplotypes are particularly of concern for coloured breeds as the percentage of carriers within breed tends to be high (10-25%), depending on the haplotype in question. In the Holstein breed, less than 5% of animals carry a haplotype affecting fertility. However, 12% of Holstein females are carriers of the more recently discovered, more costly, and more complex HCD.

Overall carrier frequencies can help paint a picture of the scale of a problem in a given breed. Carrier frequencies can, however, be highly variable from herd to herd, meaning a genetic recessive or haplotype can be much more impactful in one herd than another.  For example, Figure 2 shows the distribution of Holstein herds based on the average HCD carrier probability of the heifers and cows currently active in each herd. Although the overall frequency of HCD in Canadian Holsteins born in 2015 is 12%, we can see that many herds have higher frequencies and some are much higher! In fact, roughly 1,200 herds are made of at least 20% that are HCD carriers.

Herds made up of more carriers than average likely have a higher proportion of daughters sired by HCD carrier bulls listed in Table 1. If bloodlines listed in Tables 1 and 2 make up a significant portion of your herd, you’ll want to read on.

Managing Recessives and Haplotypes

CDN calculates Carrier Probability values for every animal in its database for all haplotypes and publicly displays them on the website as part of each animal’s “Pedigree” page. These values reflect the likelihood an animal carries a given haplotype and provide producers with the opportunity to manage these potentially problematic attributes in their herd. Strategies for managing genetic recessives and haplotypes could include:

  • Using an AI mating program that incorporates CDN carrier probabilities for recessives and haplotypes. Verify that your AI representative is avoiding mating potential/known carrier females to known carrier sires.
  • Determine potential carrier animals based on CDN carrier probabilities. Genomic test these animals to determine true carrier status. Subsequently, avoid mating carrier males to known carrier females. Again, this could be done with help from AI via a mating program that incorporates carrier probabilities since genotyped animals will have a probability of either “1%” (Free) or “99%” (Carrier).
  • Create a user account on the CDN website and subscribe to the Data Management Service called “Evaluations by Prefix”. Canadian breeders pay an annual subscription fee of $100 for access to query tools and files specific to their herd for the next 12 months. Recessive and haplotype carrier probabilities for all females, genotyped or not, are available for subscribers upon download of a detailed spreadsheet that can be opened with software like Excel. This file also contains genetic evaluations for all traits. When logged in, producers can run mates via the Inbreeding Calculator. The output file from this calculator contains a probability of being affected for all potential progeny of the mating, helping producers make more informed decisions.

Avoiding carrier sires altogether is not a recommended strategy. A sire remaining in AI despite a positive carrier status for any single genetic recessive or haplotype means his genetic offering likely outweighs the fact that he may pass on a recessive gene. These sires simply need to be used appropriately on females known to be non-carriers.

Negative genetic anomalies can be difficult to keep track of and add a new complexity to breeding dairy cattle. Utilize the strategies presented in this article to minimize their impact in your herd. CDN services are there to help you do exactly this.

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

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Who needs another index?

Have you asked yourself or a fellow breeder that question? Genetic or management indexes are created for at least one reason or purpose.  It seems like every AI unit has developed their own index for one purpose or another.  Here are some Bullvine thoughts on multi-trait genetic indexes that are designed to assist breeders in genetic improvement and marketing. These indexes are usually referred to as total merit indexes.

Others Use Indexes

Read any business article and you will not get far without reading about the Dow Jones or Consumer Price indexes. Both are designed for specific purposes. They are to reflect the price trends in a selected group of companies on the NY Stock Market, or prices consumers must pay for a selected basket of goods that they usually purchase. We regularly hear whether they are trending upwards in inflationary times or down when the economy is trending negative. However, indexes do not end with the economy. Think about it – personal health indexes, student performance indexes, and equipment performance indexes all part of what we have in our daily lexicon.

Why Total Merit Indexes?

In the 1980’s, dairy cattle marketers were claiming to have the #1 bull or #1 cow in their country or the world. #1 for type, #1 for milk, or #1 for fat % improvement. Even then total animal improvement focused breeders were asking which animals put the total package together. As opposed to being single trait wonders.

In response, breeds and genetic evaluation centres saw the need for indexes that combined, on an appropriately weighted basis, the traits in need of improvement. In the United States, combined indexes like TPI, NM$ and JPI were created, and they came into wide use by breeders in their selection and marketing. In Canada, the index, created by all organizations working together, was LPI. Other country total merit indexes included BW in New Zealand, RZG in Germany, ISU in France and NVI in the Netherlands.

The principle behind all these indexes is that dairy cows are not bred with only one or two traits in mind. Some breeders indicate that having breeding indexes makes breeding dairy cattle more complicated. However, from our exposure to breeders, The Bullvine hears that having total merit indexes assists breeders who want to breed for lifetime profit or to compare animals before buying semen or embryos.

Blindly following a total merit index is not a good practice. Breeders need to know the purpose for which a total merit index is designed. BW (New Zealand) is designed for year round grazing and low body mass. JPI (American Jersey) is designed with an emphasis on milk solids production.

Breeders need to have goals and a herd breeding plan to make maximum use of total merit indexes. Readers may wish to refer to previous Bullvine articles when establishing a herd breeding plan ( Read more: What’s the plan?, 4 Steps to Faster Genetic Improvement, 8 Steps to Choosing What Sires to Use).  Breeders need to look five years into the future to decide what will be the criteria they will judge their females by. It is entirely possible if a breeder plans to operate his dairy farm business differently in the future than they have in the past, it could be time to use a different total merit index than they have utilized in the past.

Have Genetic Indexes Been Useful?

Annually CDCB and CDN publish reports showing ever increasing rates of genetic advancement for NM$ and LPI, respectively. In fact, a recent CDN article states that half of the gain in Canada can be attributed to increased genetic merit.

In the barns around the world, individual breeders are seeing gains in their cows’ ability for production, type and now SCS. When a breeder makes extensive use of sexed semen, it can be expected that 80% of a herd’s improvement can be attributed to the sires that have been used. Definitely having total merit index rankings three times a year gives breeders the opportunity to find new top sires and to eliminate bulls that may be high for one or two individual traits but in total are not able to do a complete job. Since the introduction of TPI and LPI, one of the outcomes has been that high type sires, with inferior production ability, are used very infrequently on a population basis.

Current Reality in Genetic Indexes

With many total merit indexes and many many individual trait indexes routinely published, it can be both time consuming and confusing to keep up-to-date.

Yet the fact is that the number of indexes is increasing with every index run. For example, in the past year, there have been three new trait indexes for mastitis resistance, fertility and feed efficiency. In 2015 new added total merit indexes were Pro$ (CDN) and DWP$(TM) (Zoetis), the latter being an index produced by a private company (Read more: Can you breed a healthier cow?, The Complete Guide to Understanding Zoetis’ New Wellness Traits – CLARIFIDE® Plus, Will Genetic Evaluations Go Private?)

Tomorrow’s Indexes

Every year new indexes for important traits for varying herd management systems will continue to come into the world of dairy cattle breeding. The following questions may assist breeders in deciding upon which genetic indexes to consider:

  • Is the new index designed for the way you plan to practice dairy farming?
  • Why would you not take the opportunity to use new relevant information?
  • Who can give you the most objective view of new genetic indexes?

One size does not fit all.  Not every new genetic index, total merit or individual trait, will assist a breeder in breeding an ever more profitable herd.

The Bullvine Bottom Line

Are there too many indexes? Only if you don’t have a breeding plan, and you don’t make the right choice of a total merit index for your herd. It is not about the total number of genetic indexes. In the end, it’s about being selective and only using what’s best for you.



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Seven Key Players Form New EuroGenomics Cooperative

Eurogenomics[1]Seven key players have formed a co-operative aimed at exchanging genomic data in the Holstein breed as well as improving genomic evaluation techniques. The seven organizations are Viking Genetics from Scandinavia, Evolution and Origin Plus from France, CRV from the Netherlands, CONAFE from Spain and MCB Krasne and the Polish Federation of Cattle Breeders and Dairy Farmers. The newly formed co-operative EuroGenomic will use reference population that consists of over 33,000 genotyped bulls and will be looking for new ways to improve the effectiveness of  bovine breeding. The EuroGenoimcs Co-operative will also provide genomic test results on AI bulls over 10 months of age that are owned by third parties.

On-Farm Data: Challenges & Opportunities

There is no doubt that new technologies are changing our lives… seemingly every day! While this is true in our personal lives it is also true in the barn. In an effort to improve herd management and profitability by making timely, accurate decisions, technologies now exist for monitoring several important variables including the feed intake, body temperature, heat detection as well as lying, sleeping, movement and pre-calving behaviours of each cow in the herd. In addition to these, significant advances have been made in terms of technologies for measuring variables associated with milking, which can vary from daily milk weights from automated milking systems in parlours to more comprehensive data gathered from each cow and milking with robotic systems.

Milking Systems in Canada

Table 1 provides herd and cow statistics from across Canada by the type of milking system based on herds enrolled on DHI, which represents nearly 75% of all herds. Currently, over two-thirds of the herds in Canada, representing almost half of all cows, have a tie-stall environment.  Nearly 40% of all cows are milked in parlours even though these herds represent 22% of all herds.  In terms of the adoption of robotic milking systems as a new technology on the farm, a total of 567 herds on DHI (6.6%) currently have at least one robotic installation, representing over 60,000 and 8.7% of the cows on DHI.

Looking at Table 2 shows the regional variation in terms of the percentage of cows enrolled on DHI by milking system. Obvious differences include the percentage of cows in tie-stall herds in Quebec (76.5%), Ontario (47.6%), Atlantic Canada (28.6%) and Western Canada (6%), which is generally offset by the proportion in herds with a milking parlour.  Less regional variation exists in terms of cows milked with robotic systems, ranging from 10.6% in the West to 5.7% in Atlantic Canada.

On Farm Data

Considering the entire Canadian population on DHI,  nearly half of the cows are housed in a free stall environment, based on statistics for milking parlour and robotic systems combined. With advanced parlour setups and robotic milking systems comes sophisticated technology, and with sophisticated technology, comes an abundance of data. This is especially true in the case of the ever-growing segment of herds with robotic installations. After each milk recording test day, routinely collected data flows to the Canadian DHI centralized database and onward to CDN. However, “non-routine” data such as daily milk weights, in-line measurements of milk components, somatic cell count and/or progesterone, milk conductivity, milking times and flow rates, etc. are not currently being transferred.

Most producers with this additional data have the opinion that it has important value to the industry, especially for genetic improvement, and should be collected and used.  In some cases, this perspective becomes a source of producer frustration to a point where they question the value of participating in traditional programs such as registration, milk recording and/or conformation assessment. The reality, however, is that the accuracy and benefit of this additional data needs to be assessed and quantified.  While daily milk weights for each cow from robotic and other automated milking systems are likely quite accurate, it becomes critical that the cow identification information is also correctly aligned with the animal’s lifetime identification and registration number. More specific to assessing the value of on-farm technologies, the accuracy of in-line milk analysis of fat and protein components as well as somatic cell count needs to be validated.  Even if the overall herd results for average fat and protein percentages as well as average somatic cell score line up well with results based on the milk shipped, this does not confirm that results for each cow are accurate.  For such in-line results to be of benefit for genetic evaluation, in addition to herd management reports and benchmarking, the accuracy levels must be understood and validated. This type of validation research is an important topic here in Canada as well as several countries around the world.

Industry Initiatives

In early 2014, the Board of Directors of Canadian Dairy Network (CDN) appointed an ad-hoc committee to develop a plan to address the future needs of data collection in Canada. The final report, which was tabled in 2015, included recommendations associated with five specific strategies that were identified as important opportunities.  One of these strategies focused on the growing adoption of robotic and other automated milking systems on dairy farms across Canada. The primary need is the development and implementation of an internet-based interface for the routine transfer of authorized data for loading into a national centralized database. In 2015, Holstein Canada also initiated a project to assess the on-farm data that currently exists and the opportunities for collecting it as a means of improving the efficiency of core services provided by Holstein Canada and potentially other benefits to the industry and Canadian producers.

In summary, on-farm technologies are creating new opportunities for the collection of data for both herd management and genetic improvement.  Industry partners are in the process of assessing these opportunities, identifying which data has been validated to be of value, and considering technical solutions for efficiently retrieving data from on-farm systems in an automated manner and returning useful management information and/or genetic evaluations to producers. This will take some time and, as with many things, we need the best outcome not the fastest one!

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

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CDN is Improving Existing Traits and Adding Exciting New Ones

Some believe genomics is the be-all and end-all of the opportunity for genetic improvement. In reality, genomics is a by-product of solid traditional genetic evaluation systems and would not work without them as input. For this reason, Canadian Dairy Network (CDN) is continually improving both genomic AND traditional genetic evaluations to provide you with the most accurate overall genetic information possible for each animal. Read about some recent changes that have been made, as well as about some exciting things to come on the horizon.

Separating Somatic Cell and Production Traits

In 1999, Canada was one of the very first countries in the world to use each cow’s test day information for genetic evaluations instead of lactation-based data. Since that time the production traits, namely Milk, Fat and Protein yields, were evaluated simultaneously with Somatic Cell Score using statistical software called the “Canadian Test Day Model” (CTDM). While this system has served the industry very well for the past 15 years or so, research at CDN in recent years identified an opportunity to improve the stability of published Somatic Cell Score proofs.  Given the growing importance of this trait in the eyes of producers and its contribution towards both LPI and Pro$ indexes, CDN geneticists found that both production and Somatic Cell Score proofs would be improved, in terms of variability over time, if they were analyzed using two separate test day models rather than calculated simultaneously within a single multiple trait system.

Effective April 2016, the new approach of calculating production evaluations separately from Somatic Cell Score will be used for all breeds. This enhancement also required the calculation of new genetic parameters such as heritabilities and genetic correlations across traits. In addition to affecting Milk, Fat, Protein and Somatic Cell Score, the update can also lead to changes for Lactation Persistency and a minor impact on Herd Life, since Somatic Cell Score is a predictor of indirect Herd Life. For Holsteins, this improvement is expected to have no impact on LPI for 85% of proven sires and 76% of genotyped cows, and the most extreme changes will be a one-time adjustment of up to ±40 and ±130 LPI points for proven sires and cows respectively.

Daughter Fertility and Female Fertility Traits

Improvements to CDN’s traditional evaluations for female fertility are also expected before the end of this year, which mainly entails the use of pregnancy check data to better determine conception dates. The pregnancy check data collected from producers by DHI now provides CDN with the opportunity to improve the existing genetic evaluation system for traits related to female fertility, of which three reflect heifer fertility and four represent fertility in lactating cows.

The main traits to be affected by this improvement are the interval from first service/insemination to conception in both heifers and cows as well as days open. To date, subsequent calving records have been used to determine when conception occurred, simply by using the insemination record approximately 280 days prior to the calving date.  Utilizing data that confirms pregnancy status will reduce the time required to validate that conception actually did occur and it will also allow for the inclusion of conception dates for females that do not have a subsequent calving date at CDN. In terms of sire proofs for First Service to Conception, more data on daughters will be available, and about six months earlier, which therefore increases the accuracy of this trait, as well as Daughter Fertility as the overall index that combines key female fertility traits.

Novel Traits to Come in Canada

On-going research is set to release a wealth of new information in the coming years. Key areas of current research include health traits as well as feed efficiency and methane emissions.

  • Ketosis & Displaced Abomasum: Genetic evaluations for Clinical Mastitis and a Mastitis Resistance index were officially introduced in August 2014 as the first outcome of the National Health Project in 2006. The next fruit of this national system for producers to report on-farm health events are genetic evaluations for Ketosis, including BHB as an indicator of sub-clinical ketosis, and Displaced Abomasum, which will all be combined into a Metabolic Disease Resistance index. The target date for official implementation of this new genetic evaluation system is December 2016.
  • Metritis & Retained Placenta: Stemming from the same source of on-farm data collection of health events mentioned above, genetic evaluations are under development for resistance to fertility disorders, including Metritis and Retained Placenta. Expect to see new proof information available in 2017.
  • Hoof Health/Lameness: Hoof health data acquired from Hoof Supervisor software, used by a growing number of Canadian hoof trimmers, has undergone research and proven to be an area of opportunity for genetic selection. The recording of various infectious and non-infectious lesions as well as other hoof health characteristics, observed at the time of hoof trimming, serves as an excellent source for building a national system for herd management and genetic evaluation with the aim of reducing costs of treatment and lameness. The ongoing research project has established a data collection system to allow routine data transfer from Hoof Supervisor to DHI and on to CDN. An important outcome of this project will be the implementation of genetic and genomic evaluations for hoof health traits with targeted implementation by 2018.
  • Feed Efficiency and Methane Emissions: CDN has taken the leadership role in conducting a major research initiative, involving international partners, that targets the use of genetics and genomics for improving feed efficiency and reducing methane emissions in dairy cattle.  The project received $3.8M in funding from Genome Canada and will involve the collection of individual cow feed intake data and genotypes from two research herds and two producer-owned partner herds in Canada.  The ultimate goal is the implementation of new genetic and genomic evaluation systems for these traits in the coming years.

As is the case in all industries, the only thing constant is change – the same goes for Canadian genetic evaluations. Improvements to methodology, incorporating new data to strengthen existing evaluations, and the development  of novel traits all contribute to maintaining Canada’s status as a world leader in dairy cattle improvement.

By: Lynsay Beavers, Industry Liasion Coordinator, CDN & Brian Van Doormaal, General Manager, CDN

Améliorer les caractères existants et en ajouter de nouveaux passionnants

Certains croient que la génomique est l’alpha et l’oméga des possibilités d’amélioration génétique. En réalité, la génomique est un sous-produit de systèmes d’évaluation génétique traditionnels solides et ne pourrait pas fonctionner sans leur contribution. Pour cette raison, le Réseau laitier canadien (CDN) améliore continuellement à la fois les évaluations génomiques ET les évaluations génétiques traditionnelles pour vous offrir l’information génétique globale la plus précise possible pour chaque animal. Découvrez les changements qui ont été effectués ainsi que les choses passionnantes qui se pointent à l’horizon.

Séparer les cellules somatiques et les caractères de production

En 1999, le Canada a été un des tout premiers pays au monde à utiliser l’information du jour du contrôle de chaque vache pour les évaluations génétiques au lieu des données basées sur la lactation. Depuis ce temps, les caractères de production, notamment les rendements en lait, en gras et en protéine, ont été évalués simultanément au moyen de la cote de cellules somatiques utilisant un logiciel statistique appelé le « Modèle jour du test canadien» (MJTC). Bien que ce système ait très bien servi l’industrie pendant une quinzaine d’années, la recherche effectuée à CDN au cours des dernières années a permis d’identifier une possibilité d’améliorer la stabilité des épreuves publiées pour la Cote de cellules somatiques. Compte tenu de l’importance croissante de ce caractère aux yeux des producteurs et de sa contribution aux indices d’IPV et Pro$, les généticiens de CDN ont constaté qu’à la fois les épreuves en production et la Cote de cellules somatiques seraient améliorées, en matière de variabilité au fil du temps, si elles étaient analysées au moyen de deux modèles du jour du test séparés au lieu d’être calculées simultanément à l’intérieur d’un seul système à caractères multiples.

À partir d’avril 2016, la nouvelle approche visant à calculer séparément les évaluations de la production et de la Cote de cellules somatiques sera utilisée dans toutes les races. Cette amélioration a aussi exigé le calcul de nouveaux paramètres génétiques comme les héritabilités et les corrélations génétiques entre les caractères. En plus d’affecter le Lait, le Gras, la Protéine et la Cote de cellules somatiques, la mise à jour peut aussi entraîner des changements dans la Persistance de lactation et avoir un impact mineur sur la Durée de vie, puisque la Cote de cellules somatiques est un prédicteur de la Durée de vie indirecte. Chez les Holstein, il est prévu que cette amélioration n’aura pas d’impact sur l’IPV de 85 % des taureaux éprouvés et de 76 % des vaches génotypées, et les changements les plus extrêmes seront un rajustement unique pouvant aller respectivement jusqu’à ±40 et ±130 points d’IPV pour les taureaux éprouvés et les vaches.

Caractères de Fertilité des filles et de Fertilité femelle

Des améliorations aux évaluations traditionnelles de CDN pour la fertilité femelle sont aussi prévues d’ici la fin de l’année, ce qui entraîne principalement l’utilisation de données de vérification de la gestation pour mieux déterminer les dates de conception. Les données de vérification de la gestation que le contrôle laitier recueille auprès des producteurs donnent maintenant à CDN l’occasion d’améliorer le système d’évaluation génétique existant pour les caractères liés à la fertilité femelle, dont trois reflètent la fertilité des génisses et quatre représentent la fertilité chez les vaches en lactation.

Les principaux caractères qui seront affectés par cette amélioration sont l’intervalle entre la première insémination et la conception à la fois chez les génisses et les vaches, ainsi que les jours ouverts. Jusqu’à maintenant, des relevés de vêlages subséquents ont été utilisés pour déterminer le moment de la conception, simplement en utilisant le relevé d’insémination environ 280 jours avant la date de vêlage. L’utilisation de données qui confirment le statut de la gestation réduira le temps requis pour valider que la conception a effectivement eu lieu et permettra aussi l’inclusion des dates de conception pour les femelles qui n’ont pas une date de vêlage subséquent à CDN. En ce qui concerne les épreuves des taureaux pour la Première insémination jusqu’à la conception, un plus grand nombre de données sur les filles seront disponibles environ six mois plus tôt, ce qui augmente donc la précision de ce caractère, ainsi que la Fertilité des filles, en tant qu’indice global qui combine les principaux caractères de fertilité femelle.

Nouveaux caractères à venir au Canada

Les recherches en cours devraient fournir une mine de nouveaux renseignements au cours des prochaines années. Les domaines clés de la recherche actuelle incluent les caractères de santé ainsi que l’efficience alimentaire et les émissions de méthane.

  • Cétose et déplacement de caillette : Les évaluations génétiques de la Mammite clinique et de la Résistance à la mammite ont été officiellement introduites en août 2014 en tant que premier résultat du Projet national de santé en 2006. Le prochain fruit de ce système national par lequel les producteurs signalent les problèmes de santé à la ferme est l’évaluation génétique de la cétose, incluant le BHB comme un indicateur de la cétose sous-clinique, et du déplacement de la caillette, qui seront tous combinés en un indice de Résistance aux maladies métaboliques. La date ciblée pour la mise en œuvre officielle de ce nouveau système d’évaluation génétique est décembre 2016.
  • Métrite et rétention du placenta : Issues de la même source de collecte de données à la ferme pour les problèmes de santé mentionnés ci-dessus, des évaluations génétiques sont en cours de développement pour la résistance aux troubles de fertilité, incluant la métrite et la rétention du placenta. Attendez-vous à ce que de nouveaux renseignements sur les épreuves soient disponibles en 2017.
  • Santé des sabots/boiterie : Des données sur la santé des sabots recueillies par le logiciel Hoof Supervisor, utilisé par un nombre croissant de pareurs canadiens, ont fait l’objet de recherche et se sont avérées comme étant une occasion de sélection génétique. La consignation de différentes lésions infectieuses et non infectieuses ainsi que d’autres caractéristiques sur la santé des sabots, observées au moment du parage, sert d’excellente source pour bâtir un système national de gestion de troupeau et d’évaluation génétique dans le but de réduire les coûts du traitement et de la boiterie. Le projet de recherche en cours a permis de mettre sur pied un système de collecte de données permettant un transfert régulier de données de Hoof Supervisor au contrôle laitier, puis à CDN. Un important résultat de ce projet sera des évaluations génétiques et génomiques des caractères de santé des sabots avec une mise en œuvre ciblée d’ici 2018.
  • Efficience alimentaire et émissions de méthane : CDN a assumé le rôle de chef de file en dirigeant une importante initiative de recherche, à laquelle ont participé des partenaires internationaux, qui cible l’utilisation de la génétique et de la génomique pour améliorer l’efficience alimentaire et réduire les émissions de méthane chez les bovins laitiers. Le projet a fait l’objet d’un financement de 3,8 M$ de Génome Canada et consistera en la collecte de données individuelles sur la prise alimentaire et les génotypes des vaches dans deux troupeaux de recherche et deux troupeaux partenaires appartenant à des producteurs au Canada. Le but ultime est de mettre en œuvre de nouveaux systèmes d’évaluation génétique et génomique de ces caractères dans les années à venir.

Comme c’est le cas dans toutes les industries, la seule chose qui ne change pas est le changement – et cela s’applique aussi aux évaluations génétiques canadiennes. Des améliorations à la méthodologie, en incorporant de nouvelles données pour renforcer les évaluations génétiques et le développement de nouveaux caractères contribuent tous au maintien du statut du Canada comme chef de file mondial dans l’amélioration des bovins laitiers.

Auteurs :
Lynsay Beavers, coordonnatrice de la liaison avec l’industrie, CDN
Brian Van Doormaal, directeur général, CDN

Source: Canadian Dairy Network

GENETICS vs. ENVIRONMENT: Do Genetics Perform Uniformly in All Environments?

In current genetic evaluations, we lump data together, nationally and internationally. It is combined into one data set where we carry out the various analyzes to arrive at genetic indexes for all animals. But is that combining correct? Are there, in fact, any genetics by environment interactions situations that need consideration when combining data?  Should genetic evaluations be run separately for grazing herds compared to barn fed and housed herds?

What Does Cow Sense Tell Us?

Cow people know that there are some sire daughter groups and some cow families that perform differently when placed in different environments.

How often have you heard knowledgeable cow persons say – “He sires good useful barn cows but not enough show ring worthy daughters to have a PTAT of 3.21.” Or. “That cow family is great provided you go to the effort of pampering them like babies.”

Some Examples Where Proofs Have Not Always Told the Story

I have seen situations where sires’ daughters do not uniformly perform according to their indexes across all environments.

Quality Ultimate sired strength and stature as well as average milk and good fat percent, but he got the knock for not being tie stall friendly and lacking in daughter mobility in Canada, where he was proven. Yet in Australia breeders have told me that his mobility was not a problem. Why? Well, in Canada in tie stall barns with little to no access to exercise for 60% of the year, Ultimate daughters did not get the exercise they needed and so his proof was accurate, he had a feet and legs limitation. But, in Australia where cattle are outside walking on the ground all year, his daughter’s feet and legs were not a problem. (Read more: Mobility – The Achilles Heel of Every Breeding Program)

Looking beyond Ultimate, each of us can think of other bulls that may not suit all breeders’ needs. I think of Roybrook Starlite whose daughters were high yielders, but they often needed some special care and close monitoring. That is not something most commercial milk producers were prepared to do. Starlite’s maternal line had been a line bred family from a herd that took superb care of their animals.

Love Them or Hate Them

Today breeders either love or hate show bull Goldwyn and the commercial breeder’s dream bull, Oman. (Read more: Why Braedale Goldwyn Wasn’t a Great Sire of Sons)

A bull’s proof is an estimate of his average daughter. In extreme situations or environments, a bull’s proof may not be an accurate prediction of his true worth. How can breeders know if a bull will work, as his proof predicts, on their farm? Very little gets a breeder more upset that having a bull not perform in accordance with his proof.

Goldwyn in large commercially run groups of cows and Oman in the show ring are not good fits for what their proofs said should have ben expected.

Cow Indexes Open To More Environmental Influence

Of course, when it comes to cow indexes there are numerous examples of cows and cow families where the indexes are not accurate in predicting how they will breed on. (Read more: Has Genomics Knocked Out Hot House Herds?)

Now with genomic information included in genetic evaluations, the accuracies of prediction for cow indexes have been doubled and, therefore, may not be quite as variable in accuracy as they were in the past. Discerning breeders know that some cow families work best in certain single environments.

Points To Ponder

When conducting genetic evaluations, assumptions are made. Most of these assumptions have been shown to enhance the resulting genetic indexes. However here are a few assumptions that may contribute to inaccuracies when the indexes are used across all dairy farming situations.

  • Including Only Partial Herd Data
    Not including all contemporaries in type classification or herd recording data, when conducting BLUP genetic evaluations, violates the BLUP assumption that all animals are handled in a similar manner within a herd. Applying the results from selected data can lead to breeders questioning the daughters they get from a sire or cow family based on their genetic indexes.
  • Combining International Data Sets
    Definition of traits, variances within the data and methods of farm operation are different country to country. Interbull includes data from many production environments from many countries when doing its index calculations. Breeders should carefully interpret the results of combined international indexes when applying them back to their own herd environment.
  • Multiple Breeding Programs Within A Herd
    BLUP genetic evaluations assumes that only one breed program, one feeding program, and one management system exists in a single herd. If that assumption is violated then genetic evaluation results, especially cow indexes, can be less accurate than reported.
  • Sires Proven on Early Release Semen
    Most breeding companies release their high genomic young sires to themselves or selected herds six to nine months before it is made available to all breeders. It is imperative that the genetic evaluation procedures used for evaluating early release sires accurately adjusts for the genetic merit of the sire’s mates and the herds where the daughters are found.
  • Cows and Technology
    With many new technologies coming to market, breeders can expect to see genetic indexes for how cows adapt or perform within a technology. One such area is how cows work in single robotic milking farms. For example, breeders need to understand what is included when a bull’s daughters are called robot ready. Is that simply rear teat placement or does it include other factors as well (i.e. udder depth, milk let down, milking temperament, etc.)?
  • Genomic Information Not Yet Universal
    Even though the global dairy cattle breeding industry is almost into the ninth year of using genomic information, the genomic information and method of including the genomic results in genetic evaluations are not universal country to country. Breeders using genomic indexes from other countries need to do their homework before buying semen or embryos from abroad.

Does This Topic Need Attention?

The short answer is YES. To constructively improve their dairy cattle, breeders need to trust the numbers they use when making breeding decisions. Differences, biases, and inaccuracies in the data must be accounted for when conducting genetic evaluations.  As milk products become more of the global diet and as dairy cow populations expand, especially into more tropical conditions, breeders will need to know which cow families and sire daughter groups will work best in which environments.

The Bullvine Bottom Line

The genetic evaluations of tomorrow need to make sure that biases and inaccuracies are not created but rather eliminated when data sets are combined. The saying “Horses For Courses” comes to mind when considering bloodlines that will work better in one environment than another.



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The Complete Guide to Understanding Zoetis’ New Wellness Traits – CLARIFIDE® Plus

For the first time, dairy producers can genetically select heifers to build a healthier herd.  But with this new ability comes the challenge of understanding Zoetis’ New Wellness Traits marketed at CLARIFIDE® Plus (Read more:  ZOETIS LAUNCHES CLARIFIDE® PLUS and Can you breed a healthier cow?).  In order to help you understand the power of this new tool here are some useful resources to guide you in your understanding.

Key Points

  • CLARIFIDE® Plus represents the first commercially available dairy genetic evaluation specifically designed for wellness traits in U.S. dairy cattle.
  • CLARIFIDE Plus genomic predictions for wellness traits provide reliable assessments of genetic risk factors for economically relevant health challenges in Holstein cattle.
  • The use of Dairy Wellness Profit Index (DWP$) would be expected to offer very similar selection emphasis to that achieved by Net Merit (NM$), making it a practical consideration for producers that have historically used NM$, but would like to apply additional selection emphasis on wellness traits.
  • CLARIFIDE Plus provides an expanded suite of genetic selection tools that provide highly relevant information to dairy producers who seek to incrementally improve the health, productivity and profitability of the dairy cattle they care for.

Genetic evaluation and selection in dairy cattle has largely focused on production traits such as milk and protein production. Indirect predictors of health and fertility (e.g.,somatic cell score, productive life, daughter pregnancy rate) are available and there is evidence to support some genetic improvement for these traits. However, presumably as a result of genetic antagonisms between production and health traits as well as changes in management practices, data supports increased incidence of many common diseases in contemporary dairy production systems. Consequently, dairy cows are considered to be less ‘robust’ than previous generations, which has serious implications for the health and fertility of the modern day dairy cow.

Profitable dairy cows are fertile, productive and require minimal extraneous inputs to maintain their health through all phases of production. They generally require fewer veterinary treatments or interventions, without compromising the health, welfare or economic efficiency of the cow, and are less likely to be prematurely culled. Genetic improvement programs that incorporate knowledge regarding differences in risk of disease into selection and breeding strategies have the potential to improve profitability of dairy production through improved prevention and control of economically relevant diseases as well as enhanced animal productivity.

Improving health and fitness traits, commonly referred to as functional or wellness traits, through genetic selection presents a compelling opportunity for dairy producers to help manage disease incidence and improve profitability when coupled with sound management practices. To date, direct predictors for wellness traits related to common disease conditions in dairy production have not been readily available in the U.S. CLARIFIDE® Plus represents the first commercially available dairy genetic evaluation specifically designed for wellness traits in U.S. dairy cattle, providing predictions describing the risk for six common diseases. Routine dehorning of commercial dairy cattle is also of concern for the industry as it relates to animal well-being and costs associated with routine dehorning methods. The selection and breeding of polled stock has been proposed as a strategy for proactively managing these concerns, including use of direct tests for polledness in cattle as well as including the economic benefits within selection indexes. CLARIFIED Plus includes the Zoetis Polled genomic test prediction in the offering to accurately identify and differentiate homozygous vs. heterozygous polled Holstein animals.



  • Mastitis, lameness, metritis, retained placenta, ketosis, displaced abomasum and other health events referred to as wellness traits have a significant impact on herd health, saleable milk and overall herd profitability.
  • Profitability is enhanced when the dairy has the advantage of mature cows that are productive for multiple lactations. To reach this longevity, cows must stay healthy and be reproductively sound, in addition to producing milk. Until now, management practices were the primary way to help cows either avoid or survive these health events.
  • CLARIFIDE Plus represents the first commercially available dairy genetic evaluation specifically designed for wellness traits in U.S. dairy cattle. Dairy producers can now genomically select heifers for wellness traits at an early age to help build a healthier herd.
  • CLARIFIDE Plus is the only genomic test that allows producers to rank animals with the new Dairy Wellness Profit IndexTM (DWP$TM) based on traits that affect health, performance and profit.
  • The use of Dairy Wellness Profit Index (DWP$) would be expected to offer similar selection emphasis to that achieved by Net Merit (NM$), making it a practical consideration for producers that have historically used NM$, but would apply additional selection emphasis on wellness traits.
  • CLARIFIDE Plus derives accurate genetic predictions for six new wellness traits derived using cutting‐ edge genetic evaluation methodology applied to data collected from millions of health records within U.S. commercial herds. This results in an average Reliability of 50% for the six traits.
  • Higher values are more desirable for all traits, thus selecting for a high Standardized Transmitting Abilities (STA) will apply selection pressure for reduced risk of disease.
  • In addition to wellness traits, CLARIFIDE Plus includes genetic information for the Zoetis propriety Polled trait.
  • DWP$ includes production, fertility, type, longevity and the dairy wellness traits, including polled test results.
  • Wellness Trait IndexTM (WT$TM) focuses on the wellness traits (Mastitis, Lameness, Metritis, Retained Placenta, Displaced Abomasum and Ketosis) in addition to Polled and estimates difference in expected lifetime profit associated with risk of disease.
  • DWP$ differs from other economic indexes because it includes direct predictions for economically important diseases. By including more characteristics affecting profitability, DWP$ describes more variation in profitability than other indexes.
  • With the use of DWP$, producers can potentially make more than $55 more profit per selected female over 10 years using a 15% culling selection strategy, even when test cost is higher than a NM$‐based ranking.

Development of Dairy Wellness Predictions

Genomic predictions for wellness traits were developed by Zoetis based on an independent database of pedigrees, genotypes and production records assembled from commercial dairies and internal assets. Health events were assembled from on-farm dairy production records provided with consent by commercial dairy producers. Data editing procedures to reduce recorded disease incidence to a common format were developed based on review of event codes in on-farm software and consultation with dairy production and veterinary experts. Targeted phenotypes included:

  • Mastitis (MAST)
  • Lameness (LAME)
  • Metritis (METR)
  • Retained placenta (RP)
  • Displaced abomasum (DA)
  • Ketosis (KET)
 All diseases were defined as a Holstein female diagnosed with the respective disease one or more times in a given lactation on the basis of qualifying event codes in on-farm dairy software in the case of commercial data, or clinical research records in the case of internal research assets. As of August 2015, the database used to derive CLARIFIED Plus predictions incorporated, primarily large commercial U.S. dairy operations from across the nation and included more than 10 million lactation records; 4 million cases of mastitis; 3 million cases each of metritis, retained fetal membranes, displaced abomasum, and lameness; more than 1.9 million cases of ketosis; and more than 15 million pedigree records. Additional records are continuously added to this database on a monthly basis from producer-supplied farm records.

Genomic data was obtained from commercially tested animals with owner consent or available genotypes within Zoetis research databases. More than 100,000 genotypes were available for consideration as of August 2015. Additional commercial genotypes are added on a weekly basis. Genotypes included in the evaluation were derived from both low and medium density genotypes, all imputed to Illumina®  BovineSNP50v2 using an internal imputation reference set and FImpute.CLARIFIDE Plus predictions are derived from a weekly internal genetic evaluation that employs single-step statistical methods for estimating genomic breeding values. This method for genetic evaluation derives a joint relationship matrix based on pedigree and genomic relationships and provides a unified framework that eliminates several assumptions and parameters, thus enabling more accurate genomic evaluations. Table 1 shows the average reliability of genomic predictions for wellness traits in CLARIFIDE Plus. Among approximately 29,901 Holstein heifers less than 2 years of age within the reference dataset, the average reliability was greater than or equal to 49% for all traits. Notably, as direct predictions for individual wellness traits are not presently available, this represents a substantial increase in reliability from zero. Further, the average reliability of genomic predictions for wellness traits continues to increase as more records are added to the evaluation.

Table 1 - clarifiedplus

Reporting of Wellness Traits in CLARIFIDE® Plus

CLARIFIDE® Plus predictions for wellness traits are expressed as genomic standardized transmitting abilities (STA), similar to how type traits are expressed. Values are centered at 100 with a standard deviation of 5. The reference population included 76,840 animals that had wellness predictions and CLARIFIDE results (Table 2). For all wellness trait predictions, a value of 100 represents average expected disease risk and values of greater than 100 reflect animals with lower expected average disease risk relative to herdmates with lower STA values. Higher values are more desirable for all traits, thus selecting for a high STA will apply selection pressure for reduced risk of disease.

Table 2 - clarifiedplus

CLARIFIDE Plus predictions for the Polled test will be reported as:

  • Tested homozygous polled: The genotype demonstrates that the animal is homozygous polled and will always produce a polled animal regardless of the horned status of the other parent.(Coded PP)
  • Polled carrier: The genotype reveals a heterozygous polled animal capable of producing a horned progeny. (Coded PC)
  • Tested free of polled (i.e., horned): The genotype is consistent with an animal that is horned. (Coded TP)
  • Indeterminate: The polled status of the animal cannot be definitively determined. (Coded I)

Two New Dairy Wellness Indexes

In addition to reporting of individual wellness traits, CLARIFIDE Plus also reports two economic selection indexes to inform selection decisions. Selection indexes are a critical component of many selection strategies as they provide a path for dairy producers to select for comprehensive genetic improvement across many economically important traits. The use of economic selection indexes helps to ensure that the distribution of selection pressure applied to component traits is appropriately balanced relative to the economic impact of the individual traits on dairy profitability. To support selection for reduced risk of disease in dairy females, two economic indexes were developed.

  • Wellness Trait Index (WT$): This multi-trait selection index exclusively focuses solely on the wellness traits1 (Mastitis,Lameness, Metritis, Retained Placenta, Displaced Abomasum, Ketosis and Polled) and directly estimates potential profit contribution of the wellness trait for an individual animal that will be passed onto the next generation.
  • Dairy Wellness Profit Index (DWP$): This multi-trait selection index includes production, fertility, type, longevity, calving ability, milk quality and the wellness traits, including Polled test results. By combining the wellness traits with those found in the current Net Merit (NM$) index, DWP$ directly estimates the potential profit contribution an individual animal will pass along to the next generation.

Table 3 - clarifiedplus copyThe economic indexes in CLARIFIDE Plus were derived using standard selection index theory. Economic assumptions were derived from those used in NM$ for the case of core traits, and from a review of peer-reviewed literature for wellness traits. Economic values for health traits that are considered in the derivation of NM$ were removed to avoid double-counting of the contributions of disease to dairy profitability. Economic values were then adjusted within the range of reported values based on the covariance among traits to achieve the final index weights.
To assess the extent to which use of CLARIFIDE Plus wellness trait indexes would alter selection emphasis relative to use of NM$, the expected response to selection per standard deviation of genetic improvement in the index was estimated. In examining the response of selection between DWP$ and NM$, it is clear that use of DWP$ will result  in greater genetic improvement in wellness traits and largely the same selection response for the rest of the traits. There is some decrease in selectionemphasis and expected genetic progress for production traits associated with the use of DWP$ (Table 3), which is consistent with our understanding of the relationship between increased production and disease risk. However, selection using DWP$ will increase milk, fat and protein production, just at a slightly lower genetic rate than would be achieved with alternative indexes that do not consider direct selection for wellness traits. Importantly, the use of DWP$ would be expected to offer very similar selection emphasis to that achieved by NM$, making it a practical consideration for producers who have historically used NM$ but would like to apply additional selection emphasis on wellness traits to achieve healthier, more profitable cows.

Table 4 defines the relative values for component traits in each of the two  wellness indexes. All indexes are expressed in a dollar value with higher positive numbers indicating the animal has the genetic potential to generate and transmit more profit over her lifetime.

Table 4 - clarifiedplus

CLARIFIDE® Plus Educational Videos 

  •  Improving Dairy Health and Profitability With CLARIFIDE® Plus in Holsteins
    CLARIFIDE Plus represents the first commercially available dairy genetic evaluation specifically designed for wellness traits in U.S. dairy cattle. Dairy producers now can genomically select heifers for wellness traits at an early age to build a healthier herd. Cheryl Marti, associate director of genetics and reproduction with Zoetis, provides an overview of the technology and how it benefits Holstein dairy producers.
  • Creating Wellness Trait Genomic Predictions
    Dr. Sue DeNise, executive director of VMRD genetics with Zoetis, describes the process and research that went into product development for the wellness traits associated with CLARIFIDE Plus.
  • Understanding How CLARIFIDE Plus Wellness Traits Are Reported
    Dr. Dan Weigel, director of Outcomes Research at Zoetis, describes the wellness traits associated with CLARIFIDE Plus and how the genetic results for each wellness trait are reported.
  • Exploring CLARIFIDE Plus Wellness Traits: Mastitis
    Mastitis is one of the most costly diseases on U.S. dairy herds. Dr. Gary Neubauer, senior manager of Dairy Technical Services, and Dr. Dan Weigel, director of Outcomes Research, discuss the genetic components of mastitis and how the wellness trait is reflected within CLARIFIDE Plus.
  • Exploring CLARIFIDE Plus Wellness Traits: Lameness
    Lameness is a widespread disorder among the U.S. dairy cattle population and has a significant impact on health and productivity. Two Zoetis technical services personnel — Dr. Gary Neubauer, senior manager of Dairy Technical Services, and David Erf, a Dairy Technical Services geneticist — provide an overview of the genetic component of the lameness wellness trait.
  • Exploring CLARIFIDE Plus Wellness Traits: Metritis and Retained Placenta
    Metritis and retained placenta are two significant disorders that impact fresh cows. Two Zoetis technical service personnel — Dr. Michael Lormore, director of Cattle and Equine Technical Services – Dairy, and Dr. Anthony McNeel, senior scientist with Global Genetics Technical Services — discuss the genetic components of these traits and how they are reflected within CLARIFIDE Plus outcomes.
  • Exploring CLARIFIDE® Plus Wellness Traits: Ketosis and Displaced Abomasum
    Two Zoetis technical service personnel — Dr. Michael Lormore, director of Cattle and Equine Technical Services – Dairy, and David Erf, a Dairy Technical Services geneticist — explore two traits included within the CLARIFIDE Plus offering: ketosis and displaced abomasum. The presentation details the significance of the two disorders and the genetic components of each trait.
  • The CLARIFIDE Plus Wellness Trait Index™ (WT$™)
    Brenda Reiter, a Global Genetics Technical Services scientist with Zoetis, provides an overview of the Wellness Trait Index (WT$). The index is a multitrait selection index that focuses specifically on genomic predictions for common health disorders of dairy cattle.
  • The Power of the Dairy Wellness Profit Index™ (DWP$™)
    CLARIFIDE Plus is the only genomic test that allows producers to rank animals with the Dairy Wellness Profit Index (DWP$) based on important traits that affect health, performance and profit. Dr. Jason Osterstock, director of Global Genetics Strategic Marketing with Zoetis, describes how DWP$ was developed and how dairy producers can use DWP$ to make more informed heifer selection decisions.
  • Strategies for Using the Dairy Wellness Profit Index™ (DWP$™)
    David Erf, a Dairy Technical Services geneticist with Zoetis, provides an overview of how to use the Dairy Wellness Profit Index (DWP$). The presentation outlines strategies dairy producers can use to implement DWP$ data to sort, select and mate Holstein dairy heifers.
  • Achieving Faster Genetic Progress with DWP$
    In traditional breeding programs without genomics, it can be challenging to make significant progress within traits that have low heritability. Dr. Dan Weigel, director of Outcomes Research at Zoetis, describes how faster genetic progress can be made through genomic technology by using direct selection of the new wellness traits and using DWP$ within CLARIFIDE Plus.
  • Achieving Dairy Wellness Outcomes with CLARIFIDE Plus
    Cheryl Marti, associate director of genetics and reproduction with Zoetis, provides an overview of the Zoetis Dairy Wellness outcomes approach and how CLARIFIDE Plus supports this process for healthy animals and healthy dairies

Frequently Asked Questions

Q: What health events will be covered by wellness trait predictions?
A: Common diseases in dairy cattle including mastitis, lameness, metritis, retained placenta, displaced abomasum and ketosis will be part of the wellness trait offering.

Q: Why do I need DWP$?
A: There are several reasons to utilize DWP$ in an effective genetic management strategy:
* DWP$ provides comprehensive, accurate and specific information on wellness traits to provide clarity and opportunity to make more profitable animal rankings and decisions.
* By including more characteristics affecting profitability, DWP$ describes more variation in profitability than other indexes.
* The use of DWP$ would be expected to offer very similar selection emphasis for production, reproduction and type traits as NM$ but with additional selection emphasis on wellness traits.

Q: As a dairy producer, if I select cattle based on their wellness trait profile, does that mean that they won’t get mastitis, metritis, etc.?
A: Risk of disease is influenced by genetic and environmental factors. CLARIFIDE Plus describes differences in the genetic risk factors, but genetic selection will not compensate for suboptimal management practices that may cause animals with apparent lower risk of disease to get sick. Producers should continue to use best management practices to prevent disease and apply CLARIFIDE Plus as another tool to improve dairy wellness.

Q: How long before I see a benefit to using these wellness traits?
A: The rate of Genetic progress depends on 4 factors—selection intensity, genetic variation, heritability and generation interval. Herds can make faster genetic progress by using DWP$ through greater selection pressure and higher genetic variation compared to NM$.

Q: How can I justify the investment in CLARIFIDE Plus?
A: The combination of wellness trait information and economic implications delivered through DWP$ provide dairy producers with powerful information that can be used to help build a healthier, more productive herd. With DWP$, producers get a more comprehensive ranking because of the additional differences in profitability described by including direct predictions for economically important health events such as mastitis, lameness, metritis, etc. By including more characteristics affecting profitability, DWP$ (offered only in CLARIFIDE Plus) describes more genetic variation in profitability than other indexes.

Q: How can I order the wellness trait predictions or find additional information?
A: Currently, CLARIFIDE Plus is only available for use in Holstein cattle. Holstein producers can order the CLARIFIDE Plus test through the order form at or via Enlight® . For more information, contact Zoetis Customer Service at 877‐233‐3362 or your Zoetis representative.


Dairy producers have enjoyed the availability of a comprehensive list of economically relevant traits and a robust genetic evaluation system to fuel their genetic improvement strategies. To date, a gap has existed in the ability to improve dairy profitability and dairy cow well-being through direct genetic selection for susceptibility to common diseases. CLARIFIDE® Plus provides accurate genetic predictions for wellness traits derived using cutting-edge genetic evaluation methodology applied to data collected from commercial production settings. The result is an expanded suite of genetic selection tools that provides highly relevant information to dairy producers that seek to continue to improve the health, productivity and profitability of the dairy cattle they care for.

Want to learn more?  Check out our upcoming webinar  “New Innovation in Genomic Selection to Reduce Disease Risks” presented with Zoetis on March 16th  & March 23rd

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