When 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$).

*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. https://www.cdcb.us/eval/summary/trend.cfm

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.

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.

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

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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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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.

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

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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.

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!

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

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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

Following a two-year transition, U.S. sire and genomic evaluations are being done by the Council on Dairy Cattle Breeding (CDCB), as part of the A Non-funded Cooperative Agreement (NFCA) between the Animal Genomics and Improvement Laboratory (AGIL), United States Department of Agriculture and the Council on Dairy Cattle Breeding (CDCB)

The evaluations had previously been done by the United States Department of Agriculture’s Animal Genomics and Improvement Laboratory (AGIL) in Beltsville, Md.

The agreement to transfer the evaluations to CDCB was signed in March, 2013, with the goal of having the transfer complete within two years. “After two years of investments and intense preparation, the transition has been completed,” says Joao Durr, CDCB CEO. “Since Friday, December 11th, 2015, all data processing for genetic evaluations is being conducted by six permanent staff and two contractors at the CDCB.”

For its part, AIGL will continue to do research and develop methods to better compute estimates of genetic merit of dairy cattle, Durr says.

Read more here

There’s a new buzz word in the dairy cattle industry around the world… “Feed Efficiency”. What is this trait? How is it measured? What is the Canadian industry doing in this area? Let’s take a closer look.

What is Feed Efficiency?

In dairy production, we feed cows primarily to produce milk and its components. Some cows need to eat more to produce the same amount of output as other cows that eat less. This difference among dairy cows is a function of their “efficiency” to convert “feed” nutrients into milk and its components, therefore called Feed Efficiency. Given that cows in different herds consume different feed rations, the measurement of feed intake is standardized in units of dry matter intake. A cow with better feed efficiency will produce more kilograms of milk, fat and protein per kilogram of dry matter intake consumed. Interest in Feed Efficiency has grown in recent years since it contributes to higher profit margins while also decreasing the production of methane emissions that negatively affect the environment.

Factors Affecting Feed Efficiency

The dietary energy that a dairy cow consumes is used for various purposes including body maintenance, growth, pregnancy and milk production. Therefore, factors that affect any of these body functions can also affect feed efficiency. Examples include the number of days in milk during a lactation, a cow’s age since she is usually still growing in first lactation, the type of forages in the diet, and stress or disease experienced by the cow.

How is Feed Efficiency Measured?

One of the major challenges with monitoring and improving feed efficiency is the recording of accurate data in terms of both input and output. To start with, dry matter intake needs to be measured accurately for each cow in the herd and include both the amount of feed provided to each individual cow as well as the amount left over after eating. This is obviously a very expensive process and not feasible on most dairy farms without sophisticated equipment. The output side of the feed efficiency equation is also more complex than generally assumed. Standard milk weights and sample analysis collected by DHI at 4 to 6 week intervals is not accurate enough – daily or weekly data is required. In terms of expressing each cow’s performance for feed efficiency, one strategy is to simply use the actual dry matter intake measured throughout the lactation. This approach is sub-optimal since dry matter intake is highly correlated to milk production, which makes sense since high producing cows need to consume more feed. To solve this problem, the overall consensus amongst scientists globally is the use of Residual Feed Intake (RFI) when assessing feed efficiency. RFI is simply the difference in dry matter intake between a cow and her herdmates after adjusting for the energy used for milk production, body weight and changes in body weight over time.

Canadian Feed Efficiency Research Initiative

On behalf of its industry partners, Canadian Dairy Network (CDN) prepared a 4-year research proposal aimed at improving feed efficiency and reducing methane emissions in Canadian dairy cattle using genomic evaluation and selection. The total project budget is $10.3M, including a total contribution of $860,000 from CDN, and Genome Canada approved financial support totalling $3.8M. The research will be led by Dr. Filippo Miglior, Chief of Research and Strategic Development at CDN and Adjunct Professor at the University of Guelph, while Dr. Paul Stothard, Professor at the University of Alberta is project co-leader. There are a several critical
components to this research project including:

• Consolidating dry matter intake and methane emissions data collected for groups of dairy cows in Canada, Australia, United Kingdom, Switzerland and United States into a common database at CDN;
• Establishing a database of genotypes for all cows with feed efficiency and/or methane emissions performance data;
• Quantifying the accuracy of milk mid-infrared spectroscopy data as a predictor of feed efficiency and methane emissions in dairy cattle;
• Development of genetic and genomic evaluation systems at CDN for Feed Efficiency and Methane Emissions that would be used for genomic selection of young bulls by A.I. organizations in Canada; and
• Assessment of the social benefits, costs and acceptance towards genomic selection for feed efficiency and reduction of methane emissions.

Given the importance of accurate data collection towards the success of the major research initiative, one of the major project partners is GrowSafe Systems Ltd., located in Airdrie, Alberta (www.growsafe.com). GrowSafe has developed and manufactured equipment to accurately collect daily feed intake on an individual cow basis. In addition to this type of data being collected in two state-of-the-art research herds in Canada, one owned by the University of Guelph and the other by the University of Alberta, the project proposal includes the involvement of two producer-owned dairy operations that include 200 or more milking cows. CDN is in the process of seeking out those two producers for this important project so those interested should contact CDN.

Summary

Dairy cattle producers around the world have a growing interest to improve the feed efficiency of their animals since it has a major impact on herd profitability. The dairy industry has also an increased awareness of the importance of reducing methane emissions from dairy production from an environmental and social perspective. On behalf of the dairy cattle improvement industry in Canada, CDN has taken the leadership role in developing 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. This project has received $3.8M in
funding from Genome Canada and will involve the collection of accurate individual cow feed intake data and genotypes from two research herds and two producer-owned herds in Canada. The ultimate goal is the implementation by CDN of new genetic and genomic evaluation systems for these traits in the coming years.

Source: Canadian Dairy Network

Genetic variance for Jersey type traits

By Jan Wright

The genetic SD of several conformation traits will decrease by about 5% in Dec 2015 for Jerseys because an array overflow had affected the iterative herd variance adjustments for that breed only. The program bug had caused almost no change in PTA rankings, only the small changes in SD. Formulas for net merit will not be affected. New and previous SD for each trait are compared below.

Unknown parent group definitions

By Paul VanRaden, Jay Megonigal, Curt Van Tassell, and Mel Tooker

The automated system to assign unknown parent groups was revised to improve stability and convergence with data updates. The new group definitions are applied to yield traits, productive life (PL), somatic cell score (SCS), daughter pregnancy rate (DPR), heifer conception rate (HCR), and cow conception rate (CCR). Since Dec 2014 the animal model includes pedigrees for young animals, but too few cows with data were included in the most recent groups, so those groups will be combined. Genomic PTAs should change little because most parent averages were recomputed as needed, but parent averages for young, non-genotyped animals with missing sires or dams are the most affected.

Additional breeds from Interbull

By Paul VanRaden and Gary Fok

Bulls with breed codes MO (Montbeliard), NO (Normande), SM (Simmental), and Fleckvieh (FL) will be on the Simmental scale in the Interbull multitrait across-country evaluation (MACE) instead of the Holstein scale. As a result, about 7,000 foreign MO, NO, SM, and FL bulls will be converted by MACE onto the U.S. Holstein base. PTAs for bulls of those breeds will include the expected heterosis when mated to Holstein cows and be comparable to Holstein evaluations, as previously. The MACE system does not exchange fertility PTAs for those breeds, and conformation traits on U.S. scale are not available, so Holstein birth year averages are substituted for the missing traits. Reliability improves for the foreign bulls with U.S. daughters because of more pedigree information and additional ancestor PTAs from MACE for the additional breeds.

Editing changes for sire conception rate

By Duane Norman

An edit previously used in the calculation of sire conception rate (SCR) was if the expected calving date (last breeding date plus 280 days) was 21 or more days greater than the actual subsequent calving date, the breeding was deleted because it was assumed the date was recorded wrong or the service was to a cow already pregnant. However, the average heat cycle is 21 days but individual heats can vary by a few days. According to Ray Nebel (personal communication), “the industry uses 18 to 24 as the normal estrous interval.” Therefore CDCB is changing this edit from 21 to 17 days to allow for the variation expected in the heat cycle.   The gestation period previously used in editing was 280 days; this is being modified to use the gestation period appropriate for the specific breed addressed, i.e., changed to the breed average in the literature (AY, 282; BS, 288; GU, 286; HO, 279; JE, 280; MS, 281; and WW, 280 days). These breed averages were obtained from national data from 1999 through 2006 (Norman et al., J. Dairy Sci. 92(5):2259–2269, 2009).

Another edit previously programmed in SCR was “A herd needed a conception rate between 10 and 90% over the entire 4 year period or the inseminations from the herd were not used” (Kuhn and Hutchison, J. Dairy Sci. 91(6):2481–2269, 2008 and Kuhn et al., J. Dairy Sci. 91(7):2823–2835, 2008). This range seems extreme so we are lowering this on the top to 75% to make it more in line with other procedures being used.

The number of age categories for SCR will be reduced in the Jersey breed to make them resemble more closely a smooth biological curve.

Pro$ was introduced in August 2015 as a new national genetic selection index in the Holstein and Jersey breeds, in addition to a modified LPI formula. A.I. organizations, breed associations and other industry organizations have embraced this new index that targets producers that earn essentially all of their farm revenue from milk sales. So far, extension has focused on interpreting sire Pro$ values. But what about females? Canadian Dairy Network (CDN) also calculates and publishes Pro$ values for cows and heifers. Learn how they can be used in your breeding program.

Pro$ for Sires

Pro$ ranks bulls based on the expected average accumulated profit their daughters will achieve until they reach six years of age. There are various ways for sires to achieve high Pro$ values and rankings depending on the ability of their daughters to produce and reproduce well over multiple lactations and experience fewer problems that would otherwise increase herd expenses.

When developing the Pro$ index, CDN felt it was important that the Pro$ difference between sires was directly related to the extra lifetime profit to six years that the daughters would generate for Canadian producers. For this reason, the scale used for Pro$ is specifically in Canadian dollars.

Let’s look at an example with the current #1 proven sire compared to the #40 proven sire for Pro$. The #1 sire has a Pro$ of $2200 while the #40 sire has a Pro$ of $1700. This means that, on average, daughters of the #1 sire are expected to generate about $500 more profit per daughter over their lifetime up to six years of age (Example 1). The take home message here is that sire Pro$ values directly represent the average difference in profit that their daughters are expected to earn up to the age of six years.

Pro$ for Females

On the female side, Pro$ can be used in two distinct ways. On one hand, Pro$ values for cows can be interpreted in the same way as described above for sires. In this context, you must compare Pro$ values between two or more cows and these differences will directly reflect the expected difference in lifetime profit that future replacement heifers, daughters of those cows, would generate for your herd (Example 2). In your herd, your highest Pro$ cows, based on their genetic evaluations for production, conformation and functional traits, will have values that are hundreds of dollars higher than the average of your herd. These cows, on average, are expected to produce the most profitable replacement heifers for your herd.

A second way to use Pro$ values for females is to compare them for heifers born within the same months or year. In this context, the goal is to identify heifers that are expected to be more profitable over their lifetime to six years of age. When comparing Pro$ values for heifers, the differences in Pro$ values need to be doubled to reflect the expected differences in realized accumulated profit to six years. For example, a heifer that has a Pro$ value that is $500 higher than another one is expected to accumulate, on average, $1000 more profit over its lifetime up to six years of age (Example 3).

Animal’s Transmitting Ability Versus Genetic Merit

While it may seem confusing to interpret Pro$ values differently for cows compared to heifers, you simply need to remember why you are using Pro$. When selecting sires or comparing Pro$ among cows in your herd, your focus is producing the most profitable replacement heifers possible. Since the primary use of Pro$ is for sire selection, it has been expressed in a manner that represents the genetics that the animal, sire or cow, is expected to transmit to its progeny, on average. In this way, Pro$ values are considered as the animal’s “Transmitting Ability”.

When considering Pro$ values among a group of young heifers, the objective is to get a better understanding of each heifer’s own “Genetic Merit”, which means doubling the Pro$ values that are expressed as a Transmitting Ability. Doubling Pro$ values for heifers represents how they are expected to perform, on average, as cows in a herd with typical management. Actual lifetime profit realized by each animal can clearly be different due to the significant impact of herd management levels and other non-genetic factors that can affect a cow’s expression for production, conformation and functional traits.

Summary

Pro$ is a selection index that allows producers to improve the lifetime profitability of the dairy herd. The scale of expression for Pro$ values allows direct comparison between sires to easily understand the expected differences in profit of their daughters. This is also true when comparing Pro$ for cows since differences reflect the average lifetime profit their daughters are expected to achieve as future replacements. Since Pro$ is expressed as a “Transmitting Ability”, the values need to be used differently when comparing among a group of heifers. In this case differences need to be doubled in order to serve as a prediction of differences in their future accumulated profit in a herd with typical management.

Source: Canadian Dairy Network

National news raises the possibility of a U.S. Government shutdown on October 1, 2015. One of the consequences of a shutdown is that all Government computer systems, including AGIL, would be turned off for the duration of the shutdown. The CDCB and AGIL are joint devoting significant resources to speed up the transfer of the Cooperator’s database and the genetic evaluation software to the CDCB servers, but the transition will not be completed by September 30. In order to ensure the release of the October 2015 monthly genomic evaluation, we will be adhering strictly to our published deadline and only data uploaded by Friday, September 25, 11:59 p.m. EST will be included in the run. This includes pedigree corrections uploaded by nominators. This should guarantee that a normal release can happen on October 6, regardless of whether or not a Government shutdown occurs.

A second consequence is that the weekly preliminary genomic prediction to be released on September 29 will include only those genotypes uploaded by Friday, September 25, 11:59 p.m. EST. Data uploaded later will be included in following week’s predictions.

CDCB apologizes for any disruption or extra work this may cause our service users, but CDCB is working to minimize the consequences of a situation beyond our control. Hopefully the political impasse can be resolved and the shutdown avoided.

When all operations have been switched to CDCB servers by the end of the year, such interruptions should not occur

Whether you’re milking 50 or 500 cows, heifer rearing represents a significant cost to any dairy operation – one that is typically second only to feed costs. What’s more, a heifer spends her first lactation paying for herself, generally not making you money until second lactation. Research has shown that the single most important factor influencing heifer rearing costs is age at first calving. Using cow profitability data, CDN examined the influence of age at first calving on lifetime profit in the four breeds of largest population in Canada.

Average Age at First Calving – How are we doing?

Trends in age at first calving are shown for Holstein, Ayrshire, Jersey and Brown Swiss in Figure 1. From around 2003 to 2006 there was a slight increase in the average age at first calving for all breeds. This was likely associated with border closures due to BSE, leading producers to wait longer to calve heifers due to an industry-wide oversupply of cows. Since this time, however, the average age at first calving has been decreasing steadily in all breeds. From 2006 to 2014, the average first calving age in Holsteins has dropped 1.4 months to the current average of 25.8 months. Interestingly, this is the same average age at first calving for Jerseys – a breed that reaches puberty one to two months earlier than the other breeds represented. In general, age at first calving is higher in the Ayrshire and Brown Swiss breeds, which average 27.2 and 26.7 months, respectively.

Age at First Calving and Profitability

Using DHI cow profitability data, CDN calculated profit to six years of age for a subset of roughly 690,000 Holsteins, 17,000 Jerseys, 17,500 Ayrshires and 4,000 Brown Swiss cows born from 2005 to 2008. These profit values take into account rearing cost, cow income and cow expenses. A cut-off of six years of age was used as it proved to capture each cow’s ability to survive through multiple cycles of reproduction, health, functional conformation and production – an imperative feature when looking at lifetime profitability.

Figure 2 shows how average profit to six years varies based on the age at first calving for Holsteins. As mentioned above, the national average first calving age for this breed currently sits at around 26 months. However, the data suggests that 22 months of age is the ideal time for Holstein heifers to calve in order to maximize their future lifetime profitability. Interestingly, and in accordance with research, calving Holstein heifers before 22 months contributes to decreased total lifetime profit.

The most profitable age at first calving may differ to some degree between breeds. For example, the analysis reveals that the most profitable first calving age for Holstein and Jersey is 22 months whereas for Ayrshire and Brown Swiss, it is 23 months (Table 1). What also varies by breed is the amount of extra profit per cow to be gained by decreasing the age at first calving from the current breed average to the most profitable age. For example, the amount of lifetime profit lost due to calving one typical Holstein heifer at 26 months compared to 22 months amounts to $880, on average. Assume a 100 cow herd calves 30 replacements per year, most of them at 26 months. If the same herd calved even 10 of the 30 replacements at 22 months instead of 26 months, the increased profit to six years for the ten animals that calved earlier would amount to nearly $9,000!

While all breeds could benefit from reducing their average age at first calving, the greatest benefits could be reaped by the Brown Swiss breed. Of the four breeds studied, the average first calving age is the highest for Brown Swiss and Ayrshire heifers at 27 months. Profitability in Brown Swiss, however, is more negatively impacted by a higher age at first calving. Calving Brown Swiss heifers at 23 months, as opposed to 27 months, could lead to an average profit gained of nearly $1,400 per animal.

The main advantages of lowering age at first calving include reducing rearing costs as well as reducing the amount of time in which the heifer is a drain on farm resources. Disadvantages of lowering the average age at first calving may include a reduction in first lactation milk yield. However, research has shown that despite this possible reduction in first lactation, production per year of herd life is typically increased by lowering the age at first calving. In addition, while the first lactation may be influenced by younger calving ages, future lactations, longevity and health are not, as long as first calf heifers freshen at an adequate weight.

Since each dairy operation has its own set of unique management and environmental conditions, it may not be possible for all herds to attain one industry-wide goal for age at first calving. This, however, does not mean that we should not work towards shorter rearing periods by calving heifers earlier – clearly there is profit to be made in doing so. Work with your herd veterinarian to assure you’re meeting defined targets for age at first calving that optimize profitability and are in line with your operations specific management needs.

Source: Canadian Dairy Network

The recent genetic evaluation release in August marked the introduction of a new formula for the Lifetime Performance Index (LPI) in each breed as well as the new Pro$ (Pro Dollars) index for the Holstein and Jersey breeds. If Pro$ is the ideal profit-based genetic selection index, how come it wasn’t introduced for Ayrshires as well? This decision was made over the course of multiple meetings during the past few years involving the Ayrshire Canada Breed Improvement Committee and Canadian Dairy Network (CDN). The bottom line is that the new LPI formula for the Ayrshire breed has been specifically designed to mimic essentially the same result as if Pro$ had been implemented. Let’s take a closer look.

Cow Profitability to 6 Years of Age

The extensive analysis carried out by CDN to develop Pro$ required the calculation of actual profitability values for cows in various breeds. For Ayrshires, accumulated profit over each cow’s lifetime until the age of six years was calculated for 17,400 cows born from 2005 to 2008. Cow profitability values were calculated based on the same economic parameters and equation used by Valacta and CanWest DHI for producing the Profitability Reports they provide to their clients on an annual basis. In addition to the heifer rearing costs from birth to first calving, the income generated from milk sales, as well as the associated expenses, were estimated based on each cow’s production performance accumulated during each lactation until reaching six years of age. For cows that left the herd before this age, the revenue and expenses accumulated to the age at disposal determined the lifetime profit. Using profit accumulated to six years of age allows each cow the opportunity to express up to four cycles of reproduction, calving, health, functional conformation and production performance.

Sire LPI Versus Average Daughter Profit

Once individual cow profitability values were calculated, CDN examined the relationship between a sire’s LPI and the average accumulated profit to six years of age of their daughters. Figure 1 shows this relationship for the current LPI formula introduced for Ayrshires in August.

There are two main points demonstrated by this graph. Firstly, there is a strong correlation of 79% between a sire’s LPI in August 2015 and the realized average daughter profit to six years of age, based on the group of cows analyzed born from 2005 to 2008. This high degree of relationship indicates that LPI is currently an excellent indicator of the expected lifetime profit of an animal’s daughters. In fact, one might say this correlation is outstanding given the many nongenetic factors that can affect a cow’s lifetime profitability, especially herd management and other environmental influences.

Secondly, we can learn from this chart how to translate current LPI values for sires into expected differences in profit of their daughters. For Ayrshire sires, every 100-point increase in LPI translates to an extra average profit to six years of age of $150 per daughter! One way to look at this interpretation of LPI values is to compare the extra cost for a dose of semen for higher ranking LPI sires relative to the expected lifetime profit the daughters of the higher LPI sire will generate.

LPI Versus Pro$ in Ayrshires

During the course of developing Pro$, CDN applied the resulting equation to Ayrshires as well as the other dairy breeds in Canada. Given the strong relationship between LPI and the average daughter profit to six years of age, it was ultimately decided not to introduce a second national genetic selection index for Ayrshires. In fact, if Pro$ was introduced for the Ayrshire breed in August it would have a correlation of 98.7% with the published LPI values for proven sires. Stated in another way, only one of the current Top 20 LPI proven sires would not be among the top 20 if sorted by Pro$ and only minor reshuffling in their specific order would exist. Ayrshire breeders interested in making genetic selection decisions that target maximum profit from milk sales can use the current LPI rankings with confidence.

Expected Response from LPI Selection

One of the critical components of the educational campaign designed to communicate the new Pro$ to Holstein and Jersey breeders is the concept of “expected response” (Figure 2).

Basically, all traits of interest in dairy cattle improvement tend to be genetically correlated to each other to some extent. Some traits may be positively correlated, meaning that selection for one trait will lead to a correlated improvement in the second trait as well. For other traits that have an antagonistic genetic relationship, such as production yields and fertility, specific attention must be made to apply selection for both at the same time or else one will fall behind as the other improves. Therefore, to understand the genetic progress you can expect from selection using an index like LPI, the best tool is the expected response per trait as shown in Figure 2. Clearly, selection for LPI in Ayrshires will produce the highest gains for production yields but significant gains can also be expected for Herd Life, Conformation, Mammary System, Feet & Legs, Dairy Strength and Somatic Cell Score. For most other traits, some genetic gain is expected through selection purely for the new LPI. Two exceptions are Milking Speed and Daughter Fertility due to the negative correlations they have with other traits of importance. For example, in the Ayrshire breed, Daughter Fertility is negatively correlated with the major type traits in addition to the usual antagonistic relationship with production yields that is common to
all breeds. Therefore, with high importance placed on production and type improvement in the breed, it is difficult to also achieve genetic improvement for Daughter Fertility without significantly increasing the emphasis on this trait in the LPI formula. Fortunately, among the current list of high ranking LPI proven sires in the breed, several have above-average proofs for Daughter Fertility.

Summary

The primary goal of every dairy producer, regardless of breed, is profitability. In August 2015 the Holstein and Jersey breeds introduced Pro$ as a second selection index since it differed significantly from the LPI formula in those breeds. Ayrshire breeders can directly use LPI for genetic selection to maximize cow and herd profitability since it is 98.7% correlated to Pro$ if it had been introduced. Using LPI, every 100-point difference between Ayrshire sires translates to an average extra profit per daughter of $150 to six years of age. Expected response resulting from selection for LPI is favourable for essentially all traits of interest with significant gains achievable for the main production and conformation traits as well as resistance to mastitis and longevity.

Source: Canadian Dairy Network

A strong collaboration on common reference population for genomic prediction has been established among College of Animal Science and Technology (CAST), China Agriculture University, Dairy Association of China, Center for Quantitative Genetics and Genomics (QGG), Department of Molecular Biology and Genetics, Aarhus University, and VikingGenetics. Nordic Cattle Genetic Evaluation, is an associated partner.
The aim of this exiting Chinese and Nordic Collaboration is to strengthen Chinese and Nordic Holstein breeding through enhanced use of genomic selection, which will have great importance in a number of aspects:

• Faster improvements in Chinese Holstein breeding will be achieved by significantly higher reliabilities of genomic evaluations
• The Dairy Association of China sees the collaboration as a quantum leap for Chinese Holstein breeding to increase the benefit from genomic selection in China
• The Nordic bulls can be assessed accurately on the Chinese scale
• Precise genomic evaluation of Nordic Holstein bulls will have a great export advantage for VikingGenetics
• China can import and VikingGenetics can export semen from bulls which can perform optimally under Chinese production environments by taking genotype by environment interactions into consideration
• The model developed in this cooperation will be a framework for VikingGenetics to increase market competitiveness in other countries
• University partners CAST and QGG will collaborate on new scientific improvements based on the joint data
• The agreement will support the existing, fruitful collaboration between QGG and CAST, which has already resulted in 12 joint PhD projects among which 3 students have achieved degrees from both universities.

All partners see the collaboration as a great possibility to combine scientific and commercial forces within genomic selection to the benefit of Holstein breeding in China and the Nordic countries.

The Council on Dairy Cattle Breeding will be hosting its 2015 Industry Meeting on September 29, 2015 at the Madison Marriott West Hotel & Conference 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 program (attached) consists of an initial update on CDCB progress and plans ahead and two discussion panels, one addressing the status of dairy cattle breeding research in the U.S. and the other celebrating the landmark of one million genotypes on a reflection about how genomics re-shaped the dairy industry. All interested to participate are gently requested to complete an online pre-registration form prior to attending (follow the link: https://www.rsvpmenow.com/rsvpbeta/?id=27444). The deadline to register is September 18, 2015 at midnight EST.

We hope that you can join us and we look forward to your presence.

There is a new #1 PFT sire in Italy and it’s Heidenskipster Selleck with a +3537 gPFT. He is a Cashcoin son out of the Heidenskipster Silver’s, going back on the American brood cow, Morningview Converse Judy.  He is followed by KNS Brasilero a Balisto son from the Epic daughter KNS Reality. The former #1 gPFT bull Holbra Doorman Rodanas will be find on the 4th place currently.

• ITALY – Genomics (Owned by Italian AI’s) – 08/15
• ITALY – Proven (Owned by Italian AI’s) – 08/15

Canada is world renowned for having outstanding dairy cattle with superior genetic potential. In 2014, the exports of dairy genetics from Canada exceeded $158M, which was nearly a 30% increase over 2013 and a 43% increase over 2012. The world has confidence in Canadian genetics and the high quality of our animals in terms of production, conformation, longevity and other functional traits. An important part of the confidence stems from the high level of integrity associated with the information published for all dairy animals in Canada.

DHI Options
For over 15 years now, Canadian producers have a wide spectrum of service levels made available to them when enrolled on milk recording. The ultimate goal of DHI services provided by CanWest DHI and Valacta is to provide valuable information for management decisions to maximize cow and herd profitability. The definition of “valuable” can vary from producer to producer and, therefore, so might the type of services they receive from their milk recording agency. Producers may decide if they want monthly herd visits to achieve 12 tests per year or decrease the frequency to 10, 8 or even 6 times per year. At each visit, they can decide if they want to conduct a 24-hour test based on all milkings that day, or if they only want to take milk weights and samples for one milking, from which a 24-hour yield is estimated using national
procedures applied consistently across the country. Over and above all these options, producers can also decide if they want to involve milk recording staff on test day to conduct supervised testing instead of the herd owner recording each cow’s milk production on test day and collecting milk samples for sending to the DHI laboratory for component and somatic cell count analyses.

Publishable Lactations
Depending on the milk recording services a herd receives, the lactations for each cow may be officially published by Canadian Dairy Network (CDN) for the world to see or they may only be reported back to the producer for management purposes only. Not every producer sees the value in having “publishable” lactations and they are therefore not prepared to pay for the higher level of milk recording services required to meet the standards for official publishablility.

In Canada, there are approximately 960,000 dairy cows spread across 12,000 herds, which equates to an average of 80 cows per herd. Of these, 700,000 (73%) cows in 9,000 (75%) herds are voluntarily enrolled on some level of milk recording service. Based on the choices made by herd owners, 54% of the herds enrolled on DHI have decided to meet the national standards required for the official publication of lactations. These herds represent nearly 60% of the cows on milk recording. Publishable lactations are made publicly available on the CDN web site and distributed to the breed associations for public access on web sites, official pedigrees,
sale catalogues, etc. Publishable lactations are the basis for calculating official herd average production levels as well as for inclusion in the calculation of various awards including Master Breeder, Star Brood Cow points, Superior Production, Lifetime Production Certificates and other recognitions at the cow and herd levels. In general, herds enrolled on DHI service levels that meet the requirements for publishable lactations will also end up with official genetic evaluations for production traits published by CDN. Classified cows with official production indexes will also receive official type indexes as well as an official LPI and, starting in August 2015, they will also receive an official Pro$ value, which is the new genetic selection index for the Holstein and Jersey breeds in Canada.

Official Publication Requires National Standards
Herd owners that opt to enroll on DHI at services levels that result in officially published lactations and genetic evaluations can benefit significantly from the world exposure this brings to their cows, herd and breeder’s prefix. The integrity of the data published is dependent upon the way that Canada ensures the national standards are met by all herd owners involved with supervised testing. These standards are established by an industry committee under the leadership of CDN and administered at the field level by DHI. On behalf of the dairy cattle improvement industry, CanWest DHI and Valacta use various indicators to monitor milk recording data collected from herds involved with supervised testing and/or qualifying for genetic
evaluations. Part of this data analysis involves identifying herds that have individual cows performing at very high levels and/or have very high herd average production levels. Checks are also done comparing milk weights recorded on test day to the amount of milk shipped from the bulk tank. Any combination of these data indicators may trigger a mandatory retest of a herd, without prior notice, immediately following a regularly scheduled test day. On occasion, any herd may also be selected for conducting such a retest, simply to ensure the overall integrity of Canada’s system for publishing official lactations. All herd owners enrolled on milk recording services that involve supervised testing and/or qualify for inclusion in genetic evaluations, are subject to the terms, conditions and obligations of the Canadian service standards manual. Herein, it is clearly written, among other things, that herd owners must:
• Uniquely and accurately identify each cow in the herd,
• Test all milking cows in the herd on each test day,
• Maintain the same schedule of milking and animal milking order on test day as on other days,
• Maintain the same herd management practices on test day as on other days,
• Assure the accuracy and completeness of all information collected and recorded,
• Not engage in any activity that may mislead, impair or attempt to impair the reliability of any information about an animal or the herd,
• Use approved milk-metering devices and corresponding sampling devices, and
• Accept any retest, without prior notice, at the time and date determined by the milk
recording agency.

In the event that any of the above obligations are not fully respected by the herd owner, appropriate disciplinary actions have been established by CDN for application by the milk recording agencies in a consistent manner across the country. CDN also has procedures in place for herd owners to subsequently appeal any imposed disciplinary sanction, which would then be reviewed by a group of independent producers also enrolled on DHI services with publishable lactations.

Freedom of Choice
For the most part, Canadian producers fully understand and respect the industry standards currently in place relative to the official publication of lactation records. For herd owners wishing to use lactation records only for internal herd management decisions, the same standards do not apply. It is a choice of each producer to decide if they want to receive publishable lactation records and official genetic evaluations for their cows. When electing to do so, however, they also become part of the national system for data verification to ensure the integrity of all lactations that become publicly accessible to the world. These lactations also form the basis of
the major awards given to Canadian producers and breeders for the outstanding performance and genetic potential of their cattle and herds.
Author: Brian Van Doormaal, General Manager, CDN
Date: June 2015

Les normes de l’industrie: pourquoi?
Le Canada est reconnu à l’échelle mondiale comme ayant des bovins laitiers remarquables dotés d’un potentiel génétique supérieur. En 2014, l’exportation de produits génétiques laitiers du Canada a dépassé les 158 M$, ce qui représente une hausse de près de 30 % par rapport à 2013 et de 43 % par rapport à 2012. Le monde fait confiance à la génétique canadienne et à la grande qualité de nos animaux sur le plan de la production, la conformation, la longévité et les autres caractères  fonctionnels. Une part importante de la confiance découle du niveau élevé d’intégrité associé à l’information publiée pour tous les animaux laitiers au Canada.

Options de contrôle laitier
Depuis maintenant plus de 15 ans, les producteurs canadiens ont accès à un large éventail de niveaux de services lorsqu’ils s’inscrivent au contrôle laitier. Le but ultime des services de contrôle laitier offerts par Valacta et CanWest DHI est de  fournir des renseignements précieux pour la prise de décisions de gestion visant à maximiser la rentabilité des vaches et des troupeaux. La définition de « précieux » peut varier d’un producteur à l’autre et, par conséquent, il en va de même pour le type de services qu’ils reçoivent de leur agence de contrôle laitier. Les producteurs peuvent décider s’ils souhaitent recevoir des visites mensuelles pour réaliser douze
tests par année ou diminuer la fréquence à dix, huit ou même six fois par année. À chaque visite, ils peuvent décider s’ils veulent réaliser un test de 24 heures basé sur toutes les traites effectuées ce jour-là, où s’ils souhaitent seulement prendre les pesées et les échantillons de lait d’une seule traite, à partir desquels un rendement de 24 heures sera évalué au moyen de procédures nationales appliquées de façon uniforme dans l’ensemble du pays. En plus de toutes ces options, les producteurs peuvent aussi décider s’ils souhaitent que le personnel du contrôle laitier effectue des tests supervisés lors du jour du test au lieu que ce soit le propriétaire du troupeau qui enregistre la production de lait de chaque vache le jour du test et qui recueille les échantillons de lait pour les envoyer au laboratoire de contrôle laitier en vue d’une analyse des composants et des cellules somatiques.

Lactations publiables
Selon les services de contrôle laitier que reçoit un troupeau, les lactations de chaque vache peuvent être officiellement publiées par le Réseau laitier canadien (CDN) de façon à ce que le monde entier les voie, ou elles peuvent être retournées au producteur à de seules fins de gestion. Ce ne sont pas tous les producteurs qui perçoivent la valeur des lactations « publiables » et ils ne sont donc pas prêts à payer pour un niveau plus élevé de services de contrôle laitier requis pour répondre aux normes relatives aux lactations publiables officielles.

Le Canada compte approximativement 960 000 vaches laitières réparties dans 12 000 troupeaux, ce qui équivaut à une moyenne de 80 vaches par troupeau. De ce nombre, 700 000 (73 %) vaches dans 9 000 (75 %) troupeaux sont soumises sur une base volontaire à un certain niveau de service de contrôle laitier. Selon les choix effectués par les propriétaires de troupeaux, 54 % des troupeaux inscrits au contrôle laitier répondent aux normes nationales exigées pour la publication officielle des lactations. Ces troupeaux représentent près de 60 % des vaches soumises au contrôle laitier. Les lactations publiables sont accessibles au public dans le site web de CDN et elles sont distribuées aux associations de race en vue de leur accès public dans les sites web, les généalogies officielles, les catalogues de vente, etc. Les lactations
publiables servent de base au calcul de la moyenne des niveaux officiels de production des troupeaux et sont incluses dans le calcul de différentes reconnaissances, y compris le titre de Maître-éleveur, les points d’Étoile, les certificats de Production supérieure et de Production à vie, ainsi que d’autres reconnaissances décernées aux vaches et aux troupeaux. De façon générale, les troupeaux inscrits aux niveaux de services de contrôle laitier qui répondent aux
exigences des lactations publiables obtiendront aussi des évaluations génétiques officielles pour les caractères de production publiées par CDN. Les vaches classifiées avec des indices en production officiels obtiendront aussi des indices en conformation officiels ainsi qu’un IPV officiel et, à partir d’août 2015, elles obtiendront aussi une valeur Pro$ officielle, qui est le nouvel indice
de sélection génétique dans les races Holstein et Jersey au Canada.

La publication officielle exige des normes nationales
Les propriétaires de troupeaux qui choisissent de s’inscrire aux niveaux de services de contrôle laitier qui permettent d’obtenir des lactations et des évaluations génétiques publiées officiellement peuvent profiter grandement du degré d’exposition mondiale qu’elles procurent à leurs vaches, à leur troupeau et à leur préfixe d’éleveur. L’intégrité des données publiées dépend de la façon dont le Canada s’assure que les normes nationales sont respectées par tous les propriétaires de troupeaux participant aux tests supervisés. Ces normes sont établies par un comité de l’industrie sous la direction de CDN et sont administrées sur le terrain par le contrôle laitier. Au nom de l’industrie de l’amélioration des bovins laitiers, Valacta et CanWest DHI utilisent différents indicateurs pour contrôler les données du contrôle laitier recueillies dans des troupeaux participant aux tests supervisés et/ou admissibles aux évaluations génétiques. Une partie de cette analyse de données consiste à identifier des troupeaux où des vaches réalisent des rendements individuels à un niveau très élevé et/ou atteignent des niveaux de production très élevés par rapport à la moyenne du troupeau. Des vérifications sont aussi effectuées afin de comparer les pesées de lait enregistrées lors du jour du test aux quantités de
lait expédiées du réservoir à lait. Toute combinaison de ces indicateurs de données peut déclencher un test à l’improviste obligatoire pour un troupeau, sans avis préalable, immédiatement après le jour du test de l’horaire régulier. À l’occasion, un troupeau peut aussi être sélectionné afin de subir un test à l’improviste, simplement pour s’assurer de l’intégrité globale du système canadien de publication des lactations officielles.

Tous les propriétaires de troupeaux inscrits aux services de contrôle laitier qui comportent des tests supervisés et/ou des données admissibles aux évaluations génétiques sont assujettis aux modalités, aux conditions et aux obligations du manuel canadien des normes de service. Dans ce manuel, il est clairement indiqué que les propriétaires de troupeaux doivent, entre autres :
• Identifier de façon unique et précise chaque vache dans le troupeau,
• Soumettre au test toutes les vaches en lactation dans le troupeau lors de chaque jour du test,
• Maintenir lors du jour du test le même horaire de traite et le même ordre de traite des animaux que celui utilisé les autres jours,
• Maintenir lors du jour du test les mêmes pratiques de gestion du troupeau que celles
utilisées les autres jours,
• Assurer la précision et l’intégralité de toute l’information recueillie et consignée,
• Ne pas se livrer à des activités qui pourraient induire en erreur, compromettre ou tenter de compromettre la fiabilité de tout renseignement sur un animal ou un troupeau,
• Utiliser des appareils de mesure du lait approuvés et des appareils d’échantillonnage
correspondants,
• Accepter tout test à l’improviste, sans avis préalable, à l’heure et à la date fixées par
l’agence de contrôle laitier.

Advenant que le propriétaire du troupeau ne respecte pas entièrement les obligations décrites ci-dessus, des mesures disciplinaires appropriées ont été établies par CDN en vue de leur application par les agences de contrôle laitier de façon uniforme dans l’ensemble du pays. CDN dispose aussi de procédures permettant aux propriétaires de troupeaux d’en appeler subséquemment de toute sanction disciplinaire imposée, et cet appel serait alors étudié par un groupe de producteurs indépendants aussi inscrits aux services de contrôle laitier avec des lactations publiables.

Liberté de choix
Dans l’ensemble, les producteurs canadiens comprennent bien et respectent les normes de l’industrie actuellement en vigueur en ce qui concerne la publication officielle des relevés de lactation. Les mêmes normes ne s’appliquent pas dans le cas des propriétaires de troupeaux qui souhaitent utiliser les relevés de lactation uniquement pour des décisions de gestion interne du troupeau. Il appartient aux producteurs de décider s’ils souhaitent recevoir des relevés de lactation publiables et des évaluations génétiques pour leurs vaches. Toutefois, lorsqu’ils choisissent de le faire, ils font aussi partie du système national de vérification de données visant
à assurer l’intégrité de toutes les lactations qui deviennent publiquement accessibles à l’échelle mondiale. Ces lactations forment aussi la base des principales reconnaissances décernées aux producteurs et aux éleveurs canadiens pour le rendement et le potentiel génétique remarquables de leurs bovins et de leurs troupeaux.
Auteur : Brian Van Doormaal, directeur général, CDN
Date : Juin 2015

Fill in the blank: When making genetic selection decisions, my ultimate goal is to create a ___________ cow. If you filled in the blank with the word “profitable”, a new tool is on the way that will be of interest to you. Over a year of research has led to the development of a new genetic selection index that will allow Canadian dairy producers to improve their herd profitability.
Why do we need a second national index?

This index was developed by Canadian Dairy Network (CDN) over the past year following an industry request to explore the possibility of developing a second national index that targets dairy producers who generate essentially all of their farm revenue from milk sales. The newly developed, profit-based index has been named “Pro$” (pronounced Pro Dollars), and has officially been approved for release in August 2015. Pro$ will be available in the Holstein and Jersey breeds, while other dairy breeds will use the research behind the development of Pro$ to modify their existing LPI formula to better reflect profit.

The development of Pro$
The backbone of Pro$ is cow profitability data from Valacta and CanWest DHI – data that comes directly from Canadian dairy farms. This information is provided to their customers across Canada in the form of a Cow Profitability Report as well as a Herd Summary Profitability Report. The economic parameters used to derive the profitability values for each cow are updated annually by economists in order to assure their relevancy.

Using the cow profitability formula derived by Valacta and CanWest DHI, CDN calculated the accumulated profit to six years of age for nearly 700,000 Holstein cows born from January 2005 to September 2008. This time period was chosen in order to give each cow the opportunity to reach six years of age when the analysis was conducted at the end of 2014. If cows did not survive to six years of age, their accumulated profit until the date they left the herd was considered as their lifetime profit. While profit can be accumulated to any age, or to each calving, the decision to define profit to six years of age allows each cow the opportunity to express its ability to survive through multiple cycles of reproduction and production, which is important for defining which traits are most important contributors to lifetime profitability. Once the accumulated profit was calculated for each animal, the cows were grouped by sire to calculate the average profit of its daughters to six years of age.

The final step required to develop Pro$ involved performing a statistical regression analysis, which is a technical way of saying sire proofs for various traits were used as input to predict the average daughter profit to six years. Sires were only included if they had at least 100 daughters with profit data, leading to a total of 830 Holstein sires analyzed. Using regression analysis allowed CDN to consider the genetic relationships among all traits to determine the contribution that sire evaluations for each trait have in terms of predicting the average profit of their daughters in a scientifically sound and objective way.

Interpreting bull ratings for Pro$
Pro$, the “Pro” standing for “profit”, will be expressed in dollars and as a deviation from breed average. In other words, sires with a Pro$ of $0 are expected to produce daughters that have an average accumulated profit to six years that is equivalent to the average cow in Canada, which is approximately $2500 for Holsteins. Likewise, bulls with a Pro$ of $1000, can be expected to sire daughters that have an average accumulated profit to six years that is $1000 higher than daughters of the average Pro$ bull. In other words, selecting sires with a higher Pro$ value will directly translate to increased lifetime profit of the resulting daughters. This concept is illustrated in Graph 1 and Figure 1 below. If your herd is better managed than the average herd in Canada, your herd’s average accumulated profit to six years may be higher than the national average but the interpretation of the difference between the Pro$ values for two sires remains equal across all herds.

LPI and Pro$ – Similarities and Differences
Effective August 2015, the updated LPI formula for Holsteins will have relative weights of 40%, 40% and 20%, respectively, on the Production, Durability (longevity and functional conformation), and Health & Fertility components. Also of importance is the inclusion of the new Mastitis Resistance index introduced in August 2014 into the LPI formula. Taking these LPI updates into consideration, what can you expect as a result of selecting for Pro$ compared to LPI?

First off, it is important to realize that lifetime profit can be defined differently from farm to farm, depending on the sources of revenue and associated expenses. While Pro$ is targeted to meet the needs of producers who generate essentially all their revenue from milk sales, LPI retains the interests of those who market genetics domestically and abroad. Compared to LPI, using Pro$ as your primary selection tool will maximize production yields, longevity and overall fitness. On the other hand, using LPI as your primary selection tool will lead to a herd with exceptional conformation and fat and protein deviations. No matter which index you align yourself with, you can be confident that all of the information that feeds the traits in each index is sourced directly from Canadian dairy farms.

So which proven sires top the charts for Pro$? Table 1 shows the sires that would currently rank in the Top 15 for Pro$ as well as their rank for the current LPI. Examining the two lists reveals 10 out of 15 bulls are in common. Five bulls ranking in the Top 15 for Pro$ rank outside of the Top 15 for LPI, as is indicated by the shaded cells in the LPI rank column.

The differences in ranking between the two lists above highlight some of the differences between the two indexes and may help producers better align themselves with the index that serves their goals. Over a year of research has led to the development of Canada’s new profit-based index, Pro$, to be released for the first time with the August 2015 official genetic evaluation run. The provided background on the creation of Pro$, the explanation of Pro$ proof interpretation, and the comparison between Pro$ and LPI should allow Canadian producers to feel confident in this new and innovative genetic selection tool.

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

Pro$:  sélection génétique en vue du profit

Complétez l’énoncé suivant : lorsque je prends des décisions en matière de sélection génétique, mon but ultime est de créer une vache ___________. Si vous avez rempli l’espace avec le mot « rentable », un nouvel outil bientôt disponible saura vous intéresser. Plus d’une année de recherche a mené au développement d’un nouvel outil de sélection génétique qui permettra aux producteurs laitiers canadiens d’améliorer la rentabilité de leur troupeau.

Pourquoi avons-nous besoin d’un deuxième indice national?
Le Réseau laitier canadien (CDN) a élaboré cet indice au cours de la dernière année à la suite d’une demande de l’industrie visant à explorer la possibilité de développer un deuxième indice de sélection ciblant les producteurs laitiers dont essentiellement tous les revenus à la ferme proviennent de la vente de lait. L’indice nouvellement conçu, basé sur le profit, a été appelé « Pro$ » (se prononce Pro Dollars) et il a été officiellement approuvé en vue de son lancement en août 2015. Pro$ sera disponible dans les races Holstein et Jersey, alors que les autres races laitières utiliseront la recherche derrière le développement de Pro$ pour modifier leur formule d’IPV existante afin de mieux refléter le profit.

Le développement de Pro$
La pierre angulaire de Pro$ repose sur les données de rentabilité des vaches fournies par Valacta et CanWest DHI – des données qui proviennent directement des fermes laitières canadiennes. Cette information est fournie à leurs clients dans l’ensemble du Canada sous la forme d’un Rapport de rentabilité des vaches ainsi que d’un Rapport sommaire de rentabilité de troupeau. Les paramètres économiques utilisés pour établir les valeurs de rentabilité de chaque vache sont actualisés chaque année par des économistes afin d’en assurer la pertinence. En utilisant la formule de rentabilité des vaches établie par Valacta et CanWest DHI, CDN a calculé le profit accumulé jusqu’à l’âge de six ans par près de 700 000 vaches Holstein nées de janvier 2005 à septembre 2008. Cette période a été choisie de façon à donner à chaque vache la possibilité d’atteindre l’âge de six ans lorsque l’analyse a été réalisée à la fin de 2014. Si les vaches ne survivaient pas jusqu’à six ans, leur profit accumulé au moment où elles ont quitté le troupeau était considéré comme leur profit à vie. Même si le profit peut être accumulé jusqu’à n’importe quel âge, ou jusqu’à chaque vêlage, la décision de définir le profit à l’âge de six ans donne à chaque vache la possibilité d’exprimer sa capacité de survivre à de multiples cycles de reproduction et de production, ce qui est important pour définir les caractères qui contribuent le plus à la rentabilité à vie. Une fois que le profit accumulé a été calculé pour chaque animal, les vaches ont été regroupées en fonction de leur père en vue du calcul du profit moyen de ses filles jusqu’à l’âge de six ans.

L’étape finale exigée pour l’élaboration de Pro$ consistait à effectuer une analyse statistique de régression, ce qui est une façon technique de dire que les épreuves des taureaux pour différents caractères ont été utilisées comme données de départ pour prédire le profit moyen des filles jusqu’à six ans. Les taureaux n’étaient inclus que s’ils avaient au moins 100 filles avec des données de profit, ce qui a mené à l’analyse de 830 taureaux Holstein au total. L’utilisation d’une analyse de régression a permis à CDN de considérer les corrélations génétiques entre tous les caractères en vue de déterminer la contribution qu’apportent les évaluations des taureaux pour chaque caractère sur le plan de la prédiction du profit moyen de leurs filles de façon scientifiquement rigoureuse et objective.

Interprétation du classement des taureaux selon Pro$
Pro$, où « Pro » désigne le « profit », sera exprimé en dollars et en tant qu’écart par rapport à la moyenne de la race. En d’autres mots, les taureaux dotés d’un Pro$ de 0 $ devraient engendrer des filles ayant un profit accumulé à six ans qui équivaut à celui de la vache moyenne au Canada, soit approximativement 2 500 $ chez les Holstein. De même, on peut s’attendre à ce que les taureaux avec un Pro$ de 1 000 $ engendrent des filles dont le profit moyen accumulé à six ans sera de 1 000 $ supérieur par fille à celui des filles d’un taureau Pro$ moyen. De cette manière, la sélection de taureaux dotés d’une valeur Pro$ supérieure entraînera directement
une augmentation du profit à vie de leurs filles. Ce concept est illustré au Graphique 1 et à la Figure 1 ci-dessous. Si votre troupeau est mieux géré que le troupeau moyen au Canada, le profit accumulé moyen des vaches de votre troupeau jusqu’à l’âge de six ans pourrait être plus élevé que la moyenne nationale, mais l’interprétation de la différence entre les valeurs Pro$ de deux taureaux demeure égale d’un troupeau à l’autre.

IPV et Pro$ – similitudes et différences
À partir d’août 2015, la formule d’IPV modifiée chez les Holstein comportera des pondérations relatives respectives de 40 %, 40 % et 20 % pour les composants de Production, de Durabilité (longévité et conformation fonctionnelle) et de Santé et Fertilité. L’inclusion du nouvel indice de Résistance à la mammite introduit en août 2014 dans la formule d’IPV revêt aussi de l’importance. Compte tenu de ces actualisations de l’IPV, à quoi pouvez-vous vous attendre à la suite de la sélection en fonction de Pro$ par rapport à l’IPV?

Tout d’abord, il est important de réaliser que le profit à vie peut être défini différemment d’une ferme à l’autre, selon les sources de revenus et les dépenses associées. Alors que Pro$ vise à répondre aux besoins des producteurs dont les revenus proviennent essentiellement de la vente de lait, l’IPV suscite l’intérêt de ceux qui commercialisent des produits génétiques au pays et à l’étranger. Par rapport à l’IPV, l’utilisation de Pro$ comme principal outil de sélection maximisera les rendements en production, la longévité et les caractères fonctionnels. D’autre part, l’utilisation de l’IPV comme principal outil de sélection fera en sorte que le troupeau affichera une conformation exceptionnelle ainsi que des différentielles de gras et de protéine supérieures. Quel que soit l’indice que vous adopterez, vous pouvez avoir bon espoir que toute l’information qui alimente les caractères dans chaque indice provient directement de fermes laitières canadiennes.

Quels taureaux éprouvés dominent le classement selon Pro$? Le Tableau 1 indique quels taureaux devraient actuellement se classer parmi les 15 meilleurs pour Pro$ ainsi que leur rang actuel selon l’IPV. Un examen des deux listes révèle que 10 taureaux sur 15 sont les mêmes. Cinq taureaux classés parmi les 15 meilleurs selon Pro$ ne figurent pas parmi les 15 meilleurs pour l’IPV, comme l’indiquent les cellules ombragées dans la colonne du classement de l’IPV.

Les différences de classement dans les deux listes ci-dessus font ressortir quelques-unes des différences entre les deux indices et pourraient aider les producteurs à mieux se positionner par rapport à l’indice qui répond à leurs objectifs. Plus d’une année de recherche a mené à l’élaboration du nouvel indice canadien basé sur le profit, Pro$, qui sera publié pour la première fois lors de la ronde d’évaluations génétiques officielles d’août 2015. Le contexte de la création de Pro$, les explications sur l’interprétation des épreuves Pro$ ainsi que la comparaison entre
Pro$ et l’IPV devraient permettre aux producteurs canadiens d’avoir confiance en cet outil de sélection génétique nouveau et novateur.

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

The numbers, letters and acronyms on a proof sheet can be confusing and overwhelming, even for the genetic enthusiasts. Here you’ll find an explanation of the separate indexes, as well as definitions and explanations of proof and linear traits.

Click on a proof trait or selection index below to find the definition for that trait or index.

Selection index definitions

While we advocate that each producer sets their own customized genetic plan to put emphasis only on the traits that matter to them, the following are industry standard indexes used to help the average dairy producer increase profitability on their farm.

TPI = Total Performance Index
TPI is calculated by the Holstein Association USA (HA-USA) and includes the following trait weightings.

Trait weights for Total Performance Index (TPI)

NM$ = Net Merit Dollars
NM$ is a value that describes the expected lifetime profit per cow as compared to the base of the population born in 2005. Trait weightings are updated approximately every five years and include emphasis on the following traits.

Trait weights for the Net Merit $ (NM$) Index

CM$ = Cheese Merit Dollars
CM$ is an index calculated to account for milk sold to be made into cheese or other products. The following trait weights are considered.

Trait weights for the Cheese Merit $ (CM$) Index

MACE = Multiple-trait Across Country Evaluation
Denotes that a bull’s proof evaluation includes daughter information from multiple countries

CDCB = Council on Dairy Cattle Breeding, calculates production and health trait proof information

GFI% = Genomic Future Inbreeding percentage

aAa = Read more about this breeding guide HERE.

DMS = Dairy Mating Service.  Read more about it HERE.

Production traits

PTA = Predicted Transmitting Ability
The estimate of genetic superiority or inferiority for a given trait that an animal is predicted to transmit to its offspring. This value is based on the animal’s own records and the records of known relatives.

PTAM = Predicted transmitting ability for milk

PTAP = Predicted transmitting ability for protein, shown in pounds and percent

PTAF = Predicted transmitting ability for milk fat, shown in pounds and percent

CFP = Combined fat and protein

PRel = the percent reliability for a sire’s production proof

Conformation traits

PTAT = Predicted transmitting ability for type, also referred to as conformation

UDC = Udder composite index, which is comprised of the following trait weights:

• 35% Udder Depth
• 16% Fore udder attachment
• 16% Rear udder height
• 12% Rear udder width
•   9% Udder Cleft
•   7% Rear teat placement
•   5% Front teat placement

FLC = Foot and leg composite index, which is comprised of the following trait weights

• 50% foot and leg classification score
• 24% foot angle
• 18.5% rear legs rear view
• 7.5% rear legs side view

TRel = the percent reliability for a sire’s conformation/type proof

Health and calving traits

PL = Productive life
Measured as the total number of additional or fewer productive months that you can expect from a bull’s daughters over their lifetime.  Cows receive credit for each month of lactation, with more credit given to the first months around peak production, and less credit given for months further out in lactation. More credit is also given for older cows than for younger animals.

DPR = Daughter pregnancy rate
Daughter Pregnancy Rate is defined as the percentage of non-pregnant cows that become pregnant during each 21-day period. 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. Each increase of 1% in PTA DPR equals a decrease of 4 days in PTA days open.

SCS = Somatic cell score
The log score of somatic cells per millilitre.

SCE = Sire calving ease
The percentage of births of bull’s calves that are considered difficult in first lactation animals

DCE = Daughter calving ease
The percentage of a bull’s daughters who have difficult births during their first calving

SSB = Sire stillbirth
The percentage of a bull’s calves that are born dead to first lactation animals

DSB = Daughter stillbirth
The percentage of a bull’s daughters who give birth to a dead calf in their first lactation

HRel = the percent reliability for a sire’s health trait proof numbers

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

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.

Genetic codes

PO = Observed polled  |  PC = Tested heterozygous polled  |  PP = Homozygous Polled

RC = Carries recessive gene for red hair color  |  DR = Carries dominant gene for red hair color

Undesirable Recessives, Tested Free codes, and haplotypes

BY = Brachyspina  |  TY = Tested free of Brachyspina

BL = Bovinve Leukocyte Adhesion Deficiency (BLAD)  |  TL = Tested free of BLAD

CV = Complex Vertebral Malformation (CVM)  |  TV = Tested free of CVM

DP = Deficiency of the Uridine Monophosphate Synthase (DUMPS)  |  TD = Tested free of DUMPS

MF = Mulefoot  |  TM = Tested free of Mulefoot

HH1
HH2
HH3    = Holstein haplotypes that negatively affect fertility
HH4
HH5

Source: Alta Genetics

May 2015 marks CDN’s 20th anniversary; 20 years of providing leadership in dairy herd improvement through genetic evaluation services and an information infrastructure that are envied around the world. The company was officially incorporated on May 29th, 1995 as the result of the privatization of national genetic evaluation services from the federal government to industry. CDN member organizations include breed associations, milk recording agencies and A.I. companies marketing genetics in Canada, as well as Dairy Farmers of Canada (DFC). CDN
is fully funded by its industry member organizations with an annual operational budget approaching two million dollars in addition to over $400,000 per year to support genetics research in universities across Canada. The Board of Directors consists of eight representatives from the member organizations, with the vast majority being dairy producers.

CDN staff from left to right: Front row: Gladys Huapaya, Janusz Jamrozik, Brian Van Doormaal (General Manager), Jamie Zimmerman, Lynsay Beavers, Patti Beaumont (Information Services Manager) Back row: Pete Sullivan, Gerrit Kistemaker (Chief Geneticist), Filippo Miglior (Chief of Research & Strategic Development), Jarmila Johnston, Michela Arbuthnott, Shakeel Ahmad

Genetic Evaluation and Research
CDN’s primary mandate is to provide genetic evaluation services for all dairy cattle breeds in Canada. To accomplish this objective with timely and accurate proofs, there are six geneticists  at CDN. Dr. Gerrit Kistemaker has worked at CDN for 16 years and, in his role as Chief Geneticist, he ensures that genetic evaluation systems are executed properly while conducting ongoing research to continually improve existing systems. Gladys Huapaya has been with CDN for 15 years and assists with the calculation of genetic evaluations. New to CDN in the past five years, Drs. Jarmila Johnston and Janusz Jamrozik carry out research activities to address industry concerns and identify improvements in methodology. Dr. Pete Sullivan has been Research Scientist for nearly 10 years and concentrates his time on developing and implementing new methods associated with CDN’s genetic and genomic evaluations but also significantly contributes to the international genetic and genomic evaluation services provided by Interbull. With more than 15 years experience working in the CDN environment, Dr. Filippo Miglior is the Chief of Research and Strategic Development at CDN and is also an Adjunct Professor at the University of Guelph. His activities target industry-driven research priorities by developing new methodologies and tools for implementation by CDN as well as coordinating research projects and securing government funding for major industry initiatives.

Industry Services and Data Management
In addition to genetic evaluation services and research, CDN is responsible for the maintenance of a national dairy database for the exchange of data among industry partner organizations, as well as for public access via the CDN website. As Information Services Manager, Patti Beaumont has nearly 15 years experience at CDN and supervises all activities related to computer hardware, software, database design, data exchange and internet services. Patti is also a database programmer and expert in Oracle, and therefore ensures the proper functionality of the database processes and develops new ones as required.

As Coordinator of Data Exchange and Information Services, Jamie Zimmermann is responsible for the regular receipt and processing of data from milk recording, breeds and A.I. for loading in the CDN database as well as the genotypes for all animals tested in North America. In addition, she coordinates the provision of all data from CDN back to the industry organizations, which is a continual process. Shakeel Ahmad has been the information technology expert at CDN in the role of System and Network Administrator for over 13 years and is responsible for the maintenance of all hardware and software including the powerful computers used for genetic evaluation calculations, research and web queries accessing the CDN database. A new role developed a few years ago is that of Industry Liaison Coordinator. This position is held by Lynsay Beavers who writes articles and gives presentations on topics related to the genetic improvement of dairy cattle. She also interacts directly with industry personnel and producers on matters related to genetic and genomic evaluation services provided by CDN.

Management, Administration and Communications
As General Manager since the creation of CDN twenty years ago, Brian Van Doormaal and Michela Arbuthnott, as Administrative Assistant for the past 8 years, are a solid team that cover all activities related to the management, finances, administration and record keeping for the corporation. Working closely with the Board of Directors, they implement policies and directives and coordinate activities associated with three advisory committees, namely the Dairy Cattle Genetics Research and Development Council (DairyGen), the Genetic Evaluation Board (GEB) and the Industry Standards Committee. CDN is also responsible for the organization of the Dairy Cattle Improvement Industry Forum held in September of each year in conjunction with the CDN Annual General Meeting.

The Future
Today, genetic evaluation systems and services at CDN are highly respected and envied around the world. In this era of genomics, the need for information management is growing while industry partners strive for continued efficiencies. Under the umbrella and structure of CDN, the dairy cattle industry in Canada is well positioned to face the challenges of the future and maintain the profitability of Canadian producers in the years to come.

Les 20 ans de CDN!

Mai 2015 marque le 20e anniversaire de CDN; 20 ans comme chef de file dans l’amélioration des troupeaux laitiers par le biais de services d’évaluation génétique et d’infrastructure de l’information qui suscitent l’admiration dans le monde entier. La compagnie a été officiellement incorporée le 29 mai 1995, à la suite de la privatisation des services nationaux d’évaluation génétique qui sont passés du gouvernement fédéral à l’industrie. Les entreprises membres de CDN sont des associations de race, des agences de contrôle laitier et des compagnies d’I.A.
commercialisant des produits génétiques au Canada, ainsi que les Producteurs laitiers du Canada (PLC). CDN est entièrement financé par ses entreprises membres oeuvrant dans l’industrie, avec un budget d’exploitation annuel de près de deux millions de dollars, en plus d’au-delà de 400 000 $ par année en guise d’appui à la recherche en génétique dans diverses universités au Canada. Le conseil d’administration est formé de huit représentants des entreprises membres, la majorité étant des producteurs laitiers.

Les gens de CDN

Au total, douze personnes travaillent à CDN, réparties dans trois principaux secteurs d’activité, soit (1) l’évaluation génétique et la recherche, (2) le traitement des données et les services à l’industrie et (3) la gestion, l’administration et les communications.

Évaluation génétique et recherche
CDN a pour mission première d’offrir des services d’évaluation génétique à toutes les races de bovins laitiers au Canada. Pour atteindre cet objectif au moyen d’épreuves précises publiées en temps opportun, CDN emploie six généticiens. Dr Gerrit Kistemaker travaille à CDN depuis 16 ans, et en sa qualité de généticien principal, il s’assure que les systèmes d’évaluation génétique sont exécutés correctement tout en poursuivant la recherche afin d’améliorer constamment les systèmes existants. Gladys Huapaya est à CDN depuis 15 ans et elle contribue au calcul des évaluations génétiques. Des nouveaux venus à CDN au cours des cinq dernières années, Dre Jarmila Johnston et Dr Janusz Jamrozik, mènent des activités de recherche visant à répondre aux préoccupations de l’industrie et à identifier des améliorations
dans la méthodologie. Dr Pete Sullivan occupe le poste de chercheur scientifique depuis près de 10 ans, et il consacre son temps à développer et à mettre en oeuvre de nouvelles méthodes associées aux évaluations génétiques et génomiques de CDN, mais il contribue aussi grandement aux services internationaux d’évaluation génétique et génomique fournis par Interbull. Fort d’une expérience de plus de 15 ans dans l’environnement de CDN, Dr Filippo Miglior est le chef de la recherche et du développement stratégique à CDN et il est aussi professeur auxiliaire à l’Université de Guelph. Ses activités visent les priorités de recherche axées sur les besoins de l’industrie par le développement de nouvelles méthodologies et d’outils
à être mis en oeuvre par CDN, ainsi que la coordination de projets de recherche et l’obtention de crédits gouvernementaux pour les initiatives majeures de l’industrie.

Services à l’industrie et gestion des données
En plus des services d’évaluation génétique et de la recherche, CDN est responsable de la maintenance de la base de données nationale en vue de l’échange de données entre les entreprises partenaires de l’industrie, ainsi que de l’accès public par l’entremise du site web de CDN. Dans son rôle de directrice des services d’information, Patti Beaumont possède près de 15 années d’expérience à CDN et elle supervise toutes les activités liées à l’équipement informatique, aux logiciels, à la conception de la base de données, à l’échange de données et aux services internet. Patti est aussi programmeuse de base de données et experte en Oracle, elle s’assure ainsi du bon fonctionnement des processus de la base de données et en développe de nouveaux au besoin.

En tant que coordonnatrice de l’échange des données et des services d’information, Jamie Zimmermann est responsable de la réception et du traitement réguliers des données provenant du contrôle laitier, des races et de l’I.A. en vue de leur chargement dans la base de données de CDN ainsi que des génotypes de tous les animaux testés en Amérique du Nord. De plus, elle coordonne le transfert de toutes les données de CDN aux entreprises de l’industrie, ce qui représente un processus continu. Shakeel Ahmad est l’expert en technologies de l’information à CDN où il assume le rôle d’administrateur du système et du réseau depuis plus de 13 ans, et il
est responsable de la maintenance de tout le matériel informatique et des logiciels, incluant les puissants ordinateurs utilisés pour le calcul des évaluations génétiques, la recherche et les requêtes reçues dans la base de données de CDN. Un nouveau rôle créé il y a quelques années est celui de coordonnatrice de la liaison avec l’industrie. Ce poste est occupé par Lynsay Beavers qui rédige des articles et effectue des présentations sur des sujets liés à l’amélioration génétique des bovins laitiers. Elle interagit aussi directement avec le personnel de l’industrie et les producteurs sur des sujets associés aux services d’évaluation génétique et génomique offerts par CDN.

Gestion, administration et communications
En qualité de directeur général depuis la création de CDN il y a vingt ans, Brian Van Doormaal forme avec Michela Arbuthnott comme adjointe administrative depuis les huit dernières années une solide équipe qui couvre toutes les activités liées à la gestion, aux finances, à l’administration et à la tenue de registres pour la corporation. Travaillant en étroite collaboration avec le conseil d’administration, ils mettent en oeuvre des politiques et des directives, et  coordonnent les activités associées à trois comités consultatifs, soit le Conseil de recherche et développement en génétique des bovins laitiers (DairyGen), le Conseil d’évaluation génétique  (GEB) et le Comité des normes de l’industrie. CDN est aussi responsable de l’organisation du Forum de l’amélioration de l’industrie des bovins laitiers tenu en septembre chaque année,
conjointement avec l’assemblée générale annuelle de CDN.

L’avenir
Aujourd’hui, les systèmes et les services d’évaluation génétique de CDN sont hautement respectés et admirés dans le monde entier. Dans cette ère de la génomique, il existe un besoin croissant pour la gestion de l’information alors que les partenaires de l’industrie s’efforcent de maintenir l’efficacité. Sous l’égide et la structure de CDN, l’industrie canadienne des bovins laitiers est en bonne position pour relever les défis de l’avenir et préserver la rentabilité des
producteurs canadiens dans les années à venir.

The breeding value of some New Zealand bulls will alter when a new trait is integrated into genomic evaluations, worth thousands of dollars to each herd.

The economic impact of Body Condition Score (BCS) has led to its inclusion in the 2016 ‘Breeding Worth’, levy board Dairy New Zealand has announced.

Dairy NZ, the group overseeing the development of the new trait, says the cost is NZ$106.6 per BCS and its inclusion could enhance the rate of improvement in breeding worth.

This was discovered three years ago in the 2012 National Breeding Objective Review where BCS, particularly in late lactation, was identified as an important trait to farmers.

The value of BCS comes in two main components – maintaining milk yield and saving on feed costs.

A DairyNZ spokesperson said: “Firstly, the reduced costs from a cow maintaining or losing less condition as opposed to a cow that loses lots of condition in spring and then has to replenish that condition in autumn or winter when feed is more expensive.

“Secondly, the value of a well-conditioned cow milking well into late lactation, rather than drying her off early for poor condition. These result in an economic value of $106.6 per BCS.”

Breeding value for BCS is calculated from the records of two year old heifers. These are collected in early lactation with the majority coming from industry standard progeny tests.

However, the adjustments mean the “vast majority” of bulls will have a shift in breeding worth of ten units higher or lower, potentially greater in young bulls, warned DairyNZ.

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:

The table below indicates the amount of base change realized in 2015 compared to 2014 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.

1 – Base change for LPI is set to zero since it is already reflected by the change in the “Constant” included in the LPI formula. 2 – Traits expressed on scale of Relative Breeding Values (RBV). 3 – For Somatic Cell Score only, negative base change values represent a desirable trend in genetic progress.

The Canadian Dairy Network (CDN) is pleased to launch a second national genetic selection index starting with the genetic evaluation release in August 2015. This new profit-based index, named Pro$ (pronounced Pro Dollars), has been developed by CDN over the past year following an industry request to explore the possibility of developing a second index that targets dairy producers with essentially all of their farm revenue generated by milk sales. To-date, Holstein Canada and Jersey Canada have indicated formal support for introducing Pro$ in August 2015 for their respective breeds to be published alongside the longstanding LPI. For other dairy breeds, results from the research behind the development of this new profit index will most likely be used to modify the existing LPI formula.

CDN Chairman, Gary Bowers applauded CDN staff, members of the Genetic Evaluation Board (GEB) and industry partners for the development of this new and innovative profit index. He stated “The use of existing cow profitability calculations offered by CanWest DHI and Valacta to their customers as the underlying data for carrying out the scientific analysis to develop the Pro$ formula makes the resulting genetic ratings of sires and cows very applicable and understandable in concrete dollar terms”. “The new Pro$ serves to complement the strength of the LPI nationally and internationally while recognizing that lifetime profit can be defined differently from farm to farm, depending on sources of revenue and associated expenses”, added Bowers.

To minimize any possible confusion between the two national genetic indexes, the CDN Board of Directors also approved a slight name change for LPI, becoming Lifetime Performance Index. While the CDN research has clearly shown that LPI is strongly correlated to lifetime profit, the new profit index optimizes the association between a sire’s Pro$ and the average accumulated profit of daughters to six years of age. In addition, the CDN Board of Directors approved the new LPI formula for Holsteins, effective August 2015, which will have relative weights on the Production, Durability and Health & Fertility components of 40%, 40% and 20%, respectively. For specific traits included in the LPI, the Mastitis Resistance index introduced in August 2014 will now be included within the Health & Fertility component and replace Somatic Cell Score, Udder Depth and Milking Speed, which served as indicator traits associated with udder health.

Canadian Dairy Network (CDN) is the national genetic evaluation centre for dairy cattle and provides services to Canadian dairy producers and member organizations including breed associations, DHI agencies, A.I. organizations and Dairy Farmers of Canada. It also serves as the hub of the national Data Exchange System by which all dairy cattle improvement industry organizations share authorized data collected from dairy herds across the country.

For more information, please contact:
Brian Van Doormaal
General Manager
Canadian Dairy Network

The April 2015 genetic evaluation release will include various improvements officially introduced by Canadian Dairy Network (CDN). The combined impact of these changes, which will vary from trait to trait, will be especially important for genomic young bulls and genotyped heifers. What has changed and how should you adjust your selection decisions accordingly?

What has Changed?

In April of each year, CDN updates the genetic base used for the expressing of Canadian genetic evaluations to account for the annual rate of genetic progress for each trait. In addition to this usual adjustment associated with the upcoming genetic evaluation release in April 2015, CDN will also be introducing the following improvements to various components of its genetic and genomic evaluation calculations:

• The Canadian Test Day Model for production traits has been enhanced to allow for different shapes of lactation curves from herd to herd, which can also change over time within a herd. Herd management practises and environmental effects can affect production levels differently throughout the lactation and therefore affect the shape of lactation curves. This adjustment, which has shown to provide more accurate sire proofs for production traits, will have an important impact on cow evaluations in some herds while other herds will be less affected.
• The calculation of indexes and associated Reliabilities for Daughter Fertility, Calving Ability and Daughter Calving Ability has been improved in a manner that provides consistency between sires proven domestically and foreign sires with a MACE evaluation in Canada.
• The prediction for Indirect Herd Life has been updated following the introduction of Mastitis Resistance and Body Condition Score as newly evaluated traits in recent years.
• For the calculation of genomics, the methodology for de-regressing sire proofs has been significantly improved such that foreign sires with a MACE evaluation contribute to the estimation of genomic evaluations in a manner more consistent to the contribution from domestically proven sires. An important consequence of this new methodology is that it significantly reduces the current over-estimation of genomic young bulls and heifers compared to proven sires and cows.

Although most of the improvements above are specific to certain traits, the enhanced procedure for proof de-regression affects genomic evaluations for all traits to one degree or another.

Impact on Genomic Young Bulls

To demonstrate the impact of these improvements, which will be observed with the April 2015 release, Table 1 shows the average change for all North American genomic young bulls as well as for the Top 100 based on GPA LPI. For most traits, the average impact across all genomic young bulls is relatively small although an overall decrease is observed for production and major type traits as well as Herd Life, which translates to an average LPI drop of 65 points. The average change is more important, however, for high genomic young bulls as indicated by the Top 100 GPA LPI bulls in Table 1. For LPI, these bulls experience an average decrease of 129 LPI points and the traits that drop the most include Conformation, Herd Life, the other major type traits and Fat yield. Similar changes can be expected for genotyped heifers so breeders will have to adjust their criteria for evaluating and selecting the most elite genomic young bulls and heifers in the breed.

Figure 1 shows the relationship for LPI values before and after the April 2015 improvements to the genetic and genomic evaluations, with the dark diagonal line representing values that are equal in each case. The impact of these changes is quite clear with essentially all of the highest genomic young sires reducing to some degree, which is roughly 3% on average for bulls over 3000 GPA LPI and about 2% for bulls between 2500 and 3000. Among genomic young bulls currently over 3000 GPA LPI, essentially 99% will decrease due to the improvements implemented in April with the most extreme changes being as high as -250 LPI points.

Since Conformation is the trait most affected by the improvements introduced in April 2015, Figure 2 shows the relationship between the before and after genomic evaluations for genomic young bulls in A.I. that are positive for Conformation. As expected, the new methodologies implemented by CDN will reduce the over-estimation of young bulls compared to proven sires and a similar impact will been seen for genotyped heifers. While the average change for the Top 100 GPA LPI young bulls is -2.4 for Conformation (Table 1), the most extreme decreases will be 4 points or more. In addition to this impact, the genetic base update to be implemented in April is expected to result in an overall decrease of close to one point for Conformation for all animals.

Summary

A fundamental principle and mandate of CDN is to provide the most accurate genetic evaluations possible for all dairy breeds in Canada. The arrival of genomics over five years ago has increased the challenges associated with this key objective. CDN geneticists have worked hard in recent years to identify improvements to methods used to calculate traditional genetic evaluations as well as genomic evaluations. Through the process of research and presentation of results to industry partners, various genetic and genomic evaluation improvements will be implemented in April 2015 in addition to the usual annual genetic base update. These improvements have shown to provide more accurate evaluations going forward but will result in a significant one-time adjustment that especially impacts elite genomic young bulls and genotyped heifers. Breeders and industry organizations must adjust their criteria and selection decisions according to the narrowed scale of genomic evaluations at the extreme levels.

Source: CDN

CDCB Action Items from the CDCB Board Meeting & CDCB Annual Meeting – February 4, 2015

1. The CDCB board composition has changed.
   1. Four directors were elected for a three year term (2015 through 2017, Class II):
      1. Dan Sheldon, representing the Dairy Records Providers (re-elected)
      2. Marvin Helbig, representing the Dairy Records Processing Centers (first term)
      3. Gordon Doak, representing National Association of Animal Breeders (first term)
      4. Neal Smith, representing Purebred Dairy Cattle Association (re-elected)
   2. The two non-voting, advisory members of the board, Doug Ricke (Zoetis) and Juan Tricarico (Dairy Innovation Center) were also re-elected for another one year term.
   3. A reorganization meeting followed with the election of the new executive board:
      1. Chair: Jay Mattison (DRPs)
      2. Vice-chair: Gordon Doak (NAAB)
      3. Secretary: John Clay (DRPCs)
      4. Treasurer: Neal Smith (PDCA)
2. The 2015 budget proposal was approved by the board including a review to the CDCB Fee Schedule. Several fees charged by the CDCB for genomic services will be reduced. The revised fee schedule will be published soon and will be effective March 2, 2015.
3. Since a new system for compensating the DRPC’s has not been established yet, the CDCB will continue payments equivalent to the previous year’s rate for the April 2015 official evaluations.
4. Starting in April 2015, all bulls with daughters contributing data to the national database will receive CDCB evaluations for calving traits and sire conception rate.
5. The CDCB will be the exclusive sponsor of the Interbull/JAM Afternoon Symposium: Use of Genomics to Improve Limited and Novel Phenotypes in Animal Breeding to be held on July 12, 2015, in Orlando, Florida.

Identical twins have identical genotypes. Pedigree-based genetic evaluation systems treat identical animals as full-sibs. This strategy was known to be suboptimal since it assumes that identical twins only have 50% of their genes in common, when in reality they have the exact same DNA and identical genotypes.

For purposes of genetic evaluations, identical twins are expected to transmit the exact same genetic potential to their progeny. However, before genomics it was very difficult to prove that animals were genetically identical.

Since the identification of genetically identical animals was no longer an issue in the genomic era, Canadian Dairy Network (CDN) implemented an improved methodology in 2011 for handling proofs of identical males. As long as they were born after April 1, 2006, any pair of sires identified as having identical DNA via genotyping received the same genetic and genomic evaluations. Identical sires that were already progeny proven as of December 2010 continued to be evaluated as if they were regular full brothers.

Identical sires are treated as one individual animal by pooling their daughter information and calculating one domestic genetic evaluation. For example, if one sire in the pair has 300 daughters and its identical brother has 200 daughters, both sires receive the same genetic evaluation based on the combined group of 500 daughters. Pooling daughter information increases the reliability of their combined proof, compared to treating them as full-sibs in the past. The same proof for identical sires is sent to Interbull for the calculation of MACE evaluations on other country scales. Depending on how the other country, say United States for example, handles the MACE evaluation from Interbull in addition to any daughter data that either
brother may have in that country, identical twins may receive differing official evaluations in other countries.

Case Study – Jordan and Jerrick

Identical twins Gillette Jordan and Gillette Jerrick were first progeny proven in August 2010 and ranked #1 and #7 LPI, respectively, including genomics. As a result, they were both returned to active service and widely used across the country, although Jordan was also previously used as a high-ranking genomic young bull. Since these bulls were born prior to April 1, 2006, their proofs remained separate. Now, both have thousands of daughters in lactation and type classified. Although over 80% of their daughter production data is still from first lactation, these bulls serve as an excellent example of how proofs of identical sires evolve over time (Figure 1).

When first proven in August 2010, the bulls had an LPI difference of 278 points based solely on their traditional proof without genomics. Over the following months and years, their traditional proofs fluctuated to some degree, both upwards and downwards, with the largest difference between them exceeding 400 LPI points. As of April 2013, the variation in the LPI scale was halved and the average LPI was increased by 1700 points so the differences between Jordan and Jerrick for LPI and its components were reduced as expected. Once both bulls reached over 1,700 production daughters in May 2014, their LPI difference before including genomics has consistently been less than 100 points.

With the December 2014 national dairy genetic evaluations, USDA and the Council on Dairy Cattle Breeding (CDCB) introduced a new method of measuring Daughter Pregnancy Rate (DPR), along with other model enhancements. The old definition of DPR was number of Days Open, which was then converted to a pregnancy rate within a 21-day cycle. Days open was measured from the end of the voluntary waiting period to either a confirmed pregnancy or 250 days-in-milk. The new definition is an actual observation of pregnancy; a series of “no” or “yes” measures at 21-day intervals between 50 and 250 days in milk. Cows lacking pregnancy confirmation data at 250 days-in-milk are now assumed to be open.

The new DPR measurements are much more accurate. The genetic trend for all breeds is estimated to be twice as large as before. Improvements in fertility management from the early 1960s until the year 2000 was not sufficient to keep up with the decline in genetic merit. From 2000 on, Holstein breeders have emphasized fertility in their breeding selections. That not only halted the long term decline, but the Holstein is the only breed to see a significant upturn in the DPR values.

The new DPR information utilizes the actual breeding info and conception rates more fully to determine the 21-day pregnancy rate. The change in definition of DPR has had an impact on not only the DPR values but also on several other traits and subsequently on our estimate of breed differences and the ranking of top animals. The new DPR values show a greater increase for the top Holstein genomic young bulls compared to their contemporaries from the Jersey breed.

The improved fertility and Productive Life (PL) evaluations now have a stronger relationship with an animal’s TPI® value. The new DPR value handles differences in voluntary waiting period much better. There’s less emphasis on early conception and more on conception rates throughout the lactation. Bulls whose daughters had a longer voluntary waiting period have seen an improvement in their DPR proof. For example, the DPR values on high type bulls like Atwood and Gold Chip have gone up. The first breeding of the daughters of these bulls would have been delayed to obtain a 365-day record. The DPR values of high-index bulls like Robust, Numero Uno, and Shamrock have also gone up. Some of their daughters were being flushed and would have had a longer voluntary waiting period.

All of this has led to a higher correlation with the TPI® values. The new DPR values are more highly correlated with Heifer Conception Rate (HCR), Cow Conception Rate (CCR), and Productive Life. We even see a slight increase with production, giving us an overall increase correlation between the new DPR values with TPI®.

Many breeders were surprised to see the higher relationship among the top TPI® animals and their corresponding high fertility values. Part of the explanation of this change is an increase in the spread, or range (Standard Deviations), of the PTAs for all of the fertility traits, as well as Productive Life. Adjusting the Standard Deviations of the traits used in the TPI® formula will move some emphasis from the fertility traits over to the production traits. This comes closer to the original TPI® formula changes announced this summer.

The Genetic Advancement Committee of the Holstein Association USA, Inc. (HAUSA), met on December 17 to discuss the December genetic evaluation changes and recommended an adjustment to the Standard Deviations used in the TPI® formula. The implementation plan, approved by the HAUSA board of directors on December 18, is:

Implementation Plan:

• The current December 2014 TPI® values will remain official until the next full genetic evaluation update in April 2015.
• New Standard Deviations will be used in April 2015 to account for the increased spread created by the new DPR definition.
• The updated values of 2187 and 3.9 in the TPI® formula are being used to maintain the same genetic base and range as the current December 2014 TPI® values.

The complete TPI® formula with updated Standard Deviations, starting in April 2015, is as follows:

[27*PTAP +16*PTAF + 3*FE + 8*PTAT – 1*DF + 11*UDC + 6*FLC + 7*PL – 5*SCS + 13*FI – 2*DCE – 1*DSB] 3.9 + 2187 19 22.5 44 .73 1 .8 .85 1.51 .12 1.25 1 .9

Adjusting the TPI® formula for the new Standard Deviations will only have a small impact on TPI values and the ranking of top animals. For example, for the top 100 Genomic bulls, the average change is 1 TPI point when comparing the current TPI® values with the TPI® value using the new Standard Deviations. The average change up or down is 11 TPI points, so there is a little reshuffling or reranking. However, we will not alter the status of any of the top bulls or top cows; they are still top animals.

Announcing the April 2015 TPI® formula now will help breeders to better plan their future purchasing, breeding, and mating decisions.