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Can you really trust dairy genomics?

You’ve had the option to include dairy genomics in your genetic toolbelt for nearly ten years now. By now, fear of the unknown mystery surrounding genomics has faded. The progressive dairy industry accepts this as a new era in rapid genetic progress.

Yet, we don’t blame you if you wonder whether genomic-proven bulls are your best option, when many daughter-proven sires still offer a great genetic package. With that in mind, we look for answers in the real proof data on bulls across the entire AI industry.

What did we learn about genomics?

In graphs 1 and 2, our geneticist, Ashley Mikshowsky, analyzed proof figures on nearly 6,000 industry Holstein bulls released between January 2010 and April 2015, that currently have a daughter proof.

Graph 1 shows TPI trends. The blue line on top charts the average GTPI by initial genomic release date. The orange line shows the average August 2018 daughter proven TPI for those same bulls. The space between the two lines represents the average TPI change from initial genomic release to daughter proof.

A graph to show the average trend comparing the genomic proof versus daughter proof of industry Holstein bulls

As you can see on the left side of the graph, the bulls first released in January 2010 changed 177 TPI points from their genomic debut to their August 2018 daughter proof.

When you compare that to the newest daughter-proven bulls, including those released as genomic sires in April 2015, you see only a 105-point TPI difference from their initial genomic proof to their August 2018 daughter proof.

This means the stability in GTPI from genomic release until daughter proofs has improved by more than 70 TPI points! As a bonus, it’s clear to see that the genetic levels of bulls continue to rise!

The same goes for Net Merit $. Check out those results in Graph 2.

Industry bulls first released as genomic-proven sires in January 2010 dropped, on average, 150 NM$ from their first release until their August 2018 daughter proof. Whereas, the bulls first released as genomic sires in April 2015 only changed 89 NM$ from their initial release.

A graph to show the average trend comparing the genomic proof versus daughter proof for the Net Merit $ value of industry Holstein bulls

Looking at these results, your argument might be that dairy genomics are still inflated. Yes, and while that is true, the gap between genomic and daughter proofs has clearly improved since the start of genomics.

Let’s dig deeper into genomic proof stability

To understand from another angle, we took a look at the facts and figures in a different light.

Graph 3 and Graph 4 are based on proof data that our geneticist, Ashley, evaluated from 1,073 industry bulls released in 2014. She uses this age group because those bulls released in 2014 now have a daughter proof for production, health and conformation traits.

Graph 3 shows that the bulls released in 2014 changed an average of -110 TPI points from their initial release in 2014 to their daughter proof in August 2018.

Nearly 120 of these bulls have a daughter-proven TPI within just twenty points of their original genomic TPI. Only about 30 bulls from the entire group of 1,073 lost more than 300 TPI points – that’s less than 3%.

A histogram showing the skewed bell-shaped curve distribution of the amount of change in TPI points an average bull had from his genomic proof to daughter proof

We see the same trend for NM$. Graph 4 shows the average NM$ change and standard deviation of the same 1,073 industry bulls. The average sire released in 2014 changed -89 NM$ from their initial genomic proof in 2014 to their daughter proof in August 2018.

More than 160 of the 1073 bulls held steady within the small 20-point swing from genomic to daughter-proven NM$. Just 12 bulls changed more than 300 NM$.

A histogram showing the skewed bell-shaped curve distribution of the amount of change in Net Merit $ an average bull had from his genomics proof to daughter proof

What are your genetic options today?

Still debating whether your best bet is to use daughter-proven or genomic-proven sire groups? Take a look at the top 10 daughter-proven TPI sires available from Alta today.

AUGUST 2018 Top daughter-proven sires

Sire CodeSire NameAug. 2018 TPI
11HO11478AltaLEAF2712
11HO11437AltaSPRING2663
11HO11531AltaSABRE2624
11HO11493AltaHOTROD2616
11HO11601AltaHIFASHN2588
11HO11523AltaHOTSHOT2576
11HO11499AltaMEGLO2572
11HO11508AltaCONSUL2547
11HO11440AltaCORNELL2528
11HO11537AltaJANGO2508
Average2594

AUGUST 2018 Top genomic-proven sires

Sire CodeSire NameAug. 2018 TPI
11HO12115AltaFORCE2826
11HO12165AltaBUGGY2820
11HO12122AltaSTARJACK2818
11HO12169AltaEMIRATES2813
11HO12161AltaAROLDIS2793
11HO12124AltaGOPRO2791
11HO11778AltaROBSON2789
11HO12188AltaCUCHILLO2785
11HO12287AltaEDIFY2784
11HO12270AltaMANOR2783
Average2800

Currently, our top daughter-proven sires average a solid 2594 TPI. Yet, the top, readily-available genomic-proven group offers a much more enticing 2800 TPI average. That’s a 206-point advantage over the daughter-proven choices!

It’s inevitable that some bulls will gain points and some bulls will lose points between their genomic proof and daughter proof – the data show us that. Yet we can also see genomic proofs continue to improve. Keep in mind that your odds are essentially zero that every single bull atop the genomic-proven list would drop to rank lower than the current list of daughter-proven sires.

With your genetic choices, keep these points mind:

  1. Genomic proofs are still slightly inflated. Yet, we see less change from genomic to daughter-proven TPI and NM$ over time because of model adjustments made along the way.
  2. Despite an average drop for TPI and NM$ from a bull’s genomic to daughter proof, you will make much faster genetic progress using a group of genomic-proven sires than a group of daughter-proven sires.
  3. Make sure the genetic progress you make is in the direction of your goals. Select a group of genomic-proven sires based on your farm’s customized genetic plan. Emphasize only on the production, health or conformation traits that matter most to you to boost your farm’s future progress and profitability.

 

 Proof analysis and graphs provided by Ashley Mikshowsky, PEAK Geneticist

For a PDF of this article please Click HERE.

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Haplotypes vs. genetic mutations

With August proofs, we saw a new and unique situation with two Alta sires: newly released sexed-only 11HO12240 AltaMILESTONE and G-STAR sire, 11HO11740 AltaFACET.

AltaMILESTONE’s initial genomic test told us he was free from the HH5 haplotype. However, the more extensive gene test for the causative mutation told us he is, in fact, an HH5-carrier. Similarly, AltaFACET was initially coded as free from the HH3 haplotype, but a later gene test revealed he is an HH3-carrier.

Traditionally, haplotypes are identified when animals have the same extended sequence of about 100 SNPs. Because we know there is more to this than the currently identified haplotypes, researchers are working to identify the exact causative mutations that cause early embryonic death1,2. This causative mutation is located in between two of the 100 SNPs used in the haplotype identification, but prior to finding the true causative mutation the exact location was unknown.

Over time, crossover events that occur in the DNA during sperm and egg creation can breakup and reassemble parts of an animal’s genome. That’s why we often see so much diversity in the progeny from a single mating pair.

These crossover events can also breakup that sequence of the 100 SNPs that we traditionally use to identify the haplotypes. If this happens, an animal could still have the causative mutation, but only have 40 of the 100 SNPs that would identify them as a haplotype carrier.

As researchers continue to identify the causative mutations for negative haplotypes, the specific gene tests will eventually replace the current haplotype tests used by the CDCB.

Although crossover events frequently happen in gamete formation, this process rarely occurs within the lethal haplotypes. In fact, these are the first instances of inconsistent haplotype results for Alta marketed sires.

For full disclosure, it’s important to remember that AltaMILESTONE (HH5) and AltaFACET (HH3) both have the causative mutation for their respective haplotypes and will therefore be labeled as carriers on Alta’s proof materials and website.

 

1Shutz et al. 2016. The Holstein Friesian Lethal Haplotype 5 (HH5) Results from a Complete Deletion of TBF1M and Cholesterol Deficiency (CDH) from an ERV-(LTR) Insertion into the Coding Region of APOB. PLoS ONE 11:e0154602.

2McClure et al. 2014. Bovine Exome Sequence Analysis and Targeted SNP Genotyping of Recessive Fertility Defects BH1, HH2, and HH3 Reveal a Putative Causative Mutation in SMC2 for HH3. PLoS One 9(3):e92769.

 

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The NM$ index has new weights

The CDCB health traits will be added to the Lifetime Net Merit (NM$) formula starting in August. They will be combined into a health trait sub-index called HTH$, which will not be published separately.

You can find the relative value (%) for the traits in HTH$ in Table 1. DA, MAST, and METR represent over 80% of the index, due mainly to the higher costs and heritabilities associated with those traits.

Table 1. HTH$ sub-index relative values

TRAITABBREVRELATIVE VALUE in HTH$
MastitisMAST32.9
MetritisMETR26.5
Displaced abomasumDA23.3
Retained placentaRETP10.3
KetosisKETO4.7
Milk feverMFEV2.3

HTH$ Correlations

The correlations between HTH$ and the other traits in the NM$ formula are in Table 2. HTH$ is moderately to highly correlated with the health traits that were already included in the formula (PL, DPR, SCS, HCR, CCR, and LIV).  The heritability of HTH$ is low (0.01) as are many of the health traits.

Table 2. Genetic correlations between HTH$ and other NM$ traits

TraitMilkFatProtPLDPRSCSHCRCCRLIVCA$UdderF&LBWC
HTH$0.030.080.040.560.42−0.440.180.360.550.33−0.010.02−0.26

The new NM$ Index

A comparison of the 2017 and 2018 NM$ formulas is in Table 3 below.  The addition of HTH$ to NM$ results in slightly less weight on some of the traits already in the formula. In addition to new health traits in the index, NM$ now puts slightly more emphasis on the yield traits. SCS emphasis decreases because indirect correlated health costs are now allocated directly to HTH$.

The Fat to Protein ratio shifts to favor fat more, as the price paid for Fat is increasing and the price paid for Protein is decreasing (see Table 4 below).

Emphasis on SCS decreases since MAST is now directly included through the HTH$ index. PL emphasis also decreases slightly because later lactations are less valuable now that replacement heifer prices are lower.

Table 3. Net Merit $ Relative Values

Trait2017 NM$2018 NM$
Milk-0.7-0.7
Fat23.726.8
Protein18.316.9
PL13.412.1
SCS-6.5-4.0
DPR6.76.7
HCR1.41.4
CCR1.61.6
CA$4.84.8
LIV7.47.3
HTH$-2.3
UDC7.47.4
FLC2.72.7
BWC-5.9-5.3

NM$ 2017 versus NM$ 2018

An illustration to compare the index weights on production, health and conformation of Net Merit $ 2017 versus Net Merit $ 2018

Table 4. Component prices used to calculate Net Merit

YearFat ($/lb)Protein ($/lb)F:P ratio
20172.611.871.4
20162.312.101.1
20152.302.241.0
20142.383.390.7

Genetic Progress

Table 5 shows the expected genetic progress per trait for the 2017 and 2018 NM$ formulas.

The new 2018 formula will result in more progress for Fat, Protein, and FLC, and less progress for PL, DPR, CA$, and HCR.

The correlation between the 2017 and 2018 NM$ indexes are very high. For current industry genomic Holstein bulls the correlation is 0.998, and for current active, proven Holstein bulls, the correlation is 0.999.

Of the current top 100 NM$ genomic bulls, 88 remain in the top 100 NM$ using the 2018 formula.

Of the current top 100 NM$ active, proven bulls, 95 remain in the top 100 with the new formula.

Table 5. Expected genetic progress from NM$

Trait2017 NM$ (PTA change per year)2018 NM$ (PTA change per year)
Milk104104
Fat5.55.9
Protein3.73.8
PL0.540.51
SCS-0.02-0.02
DPR0.180.16
CA$3.53.4
HCR0.210.20
CCR0.420.42
LIV0.380.38
HTH$0.90.9
BWC-0.08-0.08
UDC0.050.05
FLC0.020.03

Customize your genetic plan

Ever-changing industry indexes serve as a reminder that your own farm’s customized genetic plan is as important as ever. When you set your emphasis on the production, health, and conformation traits that matter to your own bottom line – and stick to the plan you set – you’ll continue to maximize the progress you make in the direction of your own farm’s goals – even when other indexes change.

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Explore the new health traits

The Council on Dairy Cattle Breeding (CDCB) will release these six new direct health traits during April proofs. Click on each individual trait to learn more details about its benefits, reliability and heritability, directly from CDCB.

For a quick, one-page overview on all six health traits, please Click HERE.

The traits will be presented as disease resistance. A higher positive value is best – it means an animal is more resistant to the disease. A lower negative value will mean an animal is more susceptible, less resistant to the disease.

For example, let’s take a herd with an average mastitis incidence of 10%. If that herd uses a bull with a PTA of +3.0 for mastitis, we would expect the daughters of this bull to average 7% incidence rate for mastitis. That’s 3% less than the herd average.

Disease incidence rates range from 1.3% for milk fever to 10.2% for mastitis. Economic impact per case of each health event was also estimated, and ranged from $28 cost for ketosis to $197 for a displaced abomasum.

The heritability of these traits is still relatively low, but that doesn’t mean that you cannot make progress by selecting for these traits (read more about the high value of low heritability traits)

Mastitis resistance is also very favorably correlated with somatic cell score. Furthermore, the new health traits show no significant correlations to yield traits, meaning selection for fat or protein yield will not necessarily cause a decrease in health.

As the newly developed health traits are correlated to previously available traits, we have already been making progress in these traits, which you can learn about by reading the genetic guide to healthier cows. The data showed correlations up to 0.39 with productive life, correlations up to 0.47 with livability, and correlations up to 0.59 with DPR.

The data used to evaluate the health traits was collected from producer reported data in US herds, and underwent rigorous data testing to ensure accuracy.

With all this new information, it’s important to maintain focus on your customized genetic plan to make sure you keep making progress in the direction of your goals.

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New repro research presented at DCRC

More than 250 progressive dairy producers, academia, and industry personnel gathered in Reno, Nevada November 8-10, 2017 for the Dairy Cattle Reproduction Council (DCRC) annual meeting. While there, guests discussed new and advanced practices to achieve outstanding reproductive performance.

During the annual meeting, the DCRC invites speakers from around North America to present cutting-edge research and discuss hot-topics impacting today’s dairy reproductive performance. Topics covered this year included hormone use in dairy cattle, the importance of cow health on fertility, effects of heat stress during late gestation, heifer rearing, use of in vitro embryos and genomics, decision-making with sexed semen, and many more. Here is a quick summary of some of the talks:

Transition cow health and fertility

Dr. Eduardo Ribeiro with the University of Guelph, presented the “Impact of Transition Cow Health on Fertility.” Dr. Ribeiro showed data highlighting early pregnancy loss as a major factor impairing reproductive efficiency of dairy cattle.

In addition to early pregnancy loss, Dr. Ribeiro also demonstrated how diseases such as metritis, mastitis, lameness, and digestive and respiratory problems during the early postpartum period decreased the likelihood of cows to become pregnant after artificial insemination (AI), and increased the risk of pregnancy loss after 45 days of gestation.

Recent research of Dr. Ribeiro’s laboratory in Canada has demonstrated that the timing of disease has a negative effect on fertility of dairy cows. Disease that occurs before the end of the voluntary waiting period (VWP) has a similar, negative effect as disease that happens during the time of breeding and early pregnancy.

These findings confirm that disease has a negative carryover effect on fertility, with consequences still observed three months after the disease had subsided. Dr. Ribeiro concluded that prevention of postpartum disease is the best approach to reduce these negative effects on fertility. However, complete prevention is nearly impossible.

Future research is required to investigate the effects of minimizing inflammation of clinical diseases and how that could potentially mitigate some of the negative effects on reproduction.

Voluntary waiting period and first service repro strategies

Dr. Julio Giordano, from Cornell University, presented another great talk on the “Impact of the VWP, first-service management strategies, and how these decisions can alter profitability.” Research has demonstrated that extending the VWP from 50 or 60 to 88 days in milk (DIM) may increase conception rates at first service.

When extending the VWP, the greatest increase in conception rate is observed in first lactation cows. Dr. Giordano suggested that extending the VWP may lead to greater profitability in those first lactation cows but not in cows in their second and greater lactation.

Several factors influence profitability when changing the VWP, but the two major factors are:

  • differences in replacement costs
  • income over feed costs

Furthermore, when extending the VWP from 60 to 88 DIM the increase in first-service conception rate must be 10 to 11 percentage points greater for first lactation cows and 7 to 12 percentage points greater for multiparous cows to generate the same number of pregnancies by 90 DIM.

Dr. Giordano concluded that the duration of the VWP and how that affects herd performance and profitability depends upon complex interactions between reproductive performance, culling dynamics, lactation performance, and the economic market.

Recognizing reproductive excellence

Every year DCRC recognizes dairy farms that exude excellence in reproductive efficiency, fertility, and reproductive management. Dr. Glaucio Lopes from Alta Genetics, examined the records of the 2017 DCRC award winners to show similarities and differences among the 24 award recipients in his presentation “Digging Deep into Records of DCRC Award Winners.

Pregnancy rate is one of the most common metrics to evaluate the success of reproductive programs. So it should be no surprise that the average pregnancy rate of winning herds has steadily increased throughout the years of the award program. In fact, all award winners from 2017’s contest had over 30% pregnancy rate throughout 2016. However, Dr. Lopes was emphatic on highlighting that pregnancy rate is not the only metric used by the awards committee to select the winners.

Though reproductive management strategies differed among award winners, most farms used some form of fixed timed-AI program as part of their management system, in combination with estrus detection and AI. Despite practices that were common in the beginning of this decade, no farms used 100% fixed timed-AI, nor 100% estrus detection to select cows for all services.

Of the 24 winners, 13 dairies use some form of a presynch-ovsynch program, with a combination of synchronization and estrus detection for AI on all services. Eleven of the award-winning dairies use a 100% timed AI program for first service, followed by a combination of re-synchronization and estrus detection for subsequent services.

The range in VWP among the award winners was vast, ranging from 41 to 76 DIM. First service conception rates were outstanding, even for the dairies using sexed-semen on lactating cows, ranging from 37% – 66%.

An interesting observation presented was that disease incidence of the award-winning dairies was extremely low. Though the incidence of disease could be underreported in the computer records, this observation agrees with the presentation and conclusions of Dr. Ribeiro.

In conclusion, maximizing reproductive efficiency and performance is important to a successful and profitable year ahead. The annual meeting hosted by DCRC provided valuable information to dairy professionals that will benefit the dairy industry this year, and the years ahead.

Please visit http://www.dcrcouncil.org/ to learn more about this great organization, and the benefits of becoming a member.

DCRC is a proactive organization with long-term interest in raising awareness of issues critical to reproductive performance. Through information and communication, it strives to deliver the latest in technology and resources.

Article written by Dr. Benjamin Voelz, Premier Account Manager and Dr. Glaucio Lopes, Vice-President of DCRC and Alta University Manager, Alta Genetics.

For more details on the DCRC annual meeting, or with follow-up questions on this article, please contact: Benjamin Voelz (ben.voelz@altagenetics.com) or Glaucio Lopes (glaucio.lopes@altagenetics.com).

Dairy Cattle Reproduction Council logo
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Understand the new TPI changes

With August 2017 proofs Holstein Association USA (HA USA) will make updates to TPI, Udder Composite (UDC) and Foot & Leg Composite (FLC). The following information will help you understand these changes and how they may affect sire ranks.

As with any index changes, sires will re-rank. We can attribute most of the re-ranking to the fact that stature is being added to the calculations for UDC and FLC.

Industry standard index changes remind us how important it is to set your own customized genetic plan. While we review the changes being made to Udder Composite and TPI for the upcoming proof round, keep your own genetic plan in mind to ensure it continues to match your farm’s current goals and future plans.

Udder Composite changes

The biggest change that will take place within UDC is that stature is now incorporated with a negative emphasis to promote a more moderate sized frame on Holstein cows of the future. While all individual trait weights within UDC will adjust slightly, stature will now have a relative weight of 17% of UDC. This change comes mostly from the reduced emphasis on udder depth.

A comparison between the previous and new versions of UDC is shown in Table 1 below, with major changes in bold.

TABLE 1Previous percent weight within UDCAugust 2017 percent weight within UDC% Change
Fore udder16%13%-3%
Rear udder height16%19%3%
Rear udder width12%16%4%
Udder cleft9%7%-2%
Udder depth35%17%-18%
Front teat placement5%3%-2%
Rear teat placement (now called Rear teat optimum)7%4%-3%
Teat length (now called Teat length optimum)-4%4%
Stature--17%17%

The other change taking place with udder traits is that both rear teat placement and teat length will now be two-way traits, and be called rear teat optimum and teat length optimum, respectively.

The rear teat length and placement of the Holstein breed has evolved to a shorter and closer average. By adjusting to an intermediate optimum, rather than a close and short ideal, is intended to help get the breed back to a more desirable norm.

The new Foot & Leg Composite

As with UDC, the main difference in the new FLC comes from the addition of stature to the index. Table 2 shows that stature is added mostly from the reduced weight now placed on foot angle and rear leg side view.

TABLE 2Previous percent weight within FLCAugust 2017 percent weight within FLC% Change
Foot angle24%7.5%-17%
Rear legs rear view19%17.5%-1%
Foot and leg score50%58%8%
Stature--17%17%
Rear leg side view8%--8%

TPI updates

In addition to the UDC and FLC updates, the TPI formula will also be revamped. While the weights within the production, health and conformation categories remain the same, the individual trait weights within the production and health buckets will change.

The biggest change to the new TPI formula is found within the production category as a new protein to fat ratio. You can see all changes in Table 3 below.

TABLE 3Previous weight within TPIAugust 2017 weight within TPI
Protein2721
Fat1617
Feed Efficiency38
PRODUCTION TOTAL46%46%
Fertility Index1313
Productive Life74
Livability-3
Somatic Cell Score-5-5
Daughter Calving Ease22
Daughter Stillbirth11
HEALTH TOTAL28%28%
Udder Composite1111
PTA Type88
Foot & Leg Composite66
Dairy Form-1-1
CONFORMATION TOTAL26%26%

HA USA reweighted protein, fat and feed efficiency, and therefore adjusted the fat to protein ratio. Starting in August, there will be 6% less emphasis directly on protein, 5% emphasis added to feed efficiency and 1% more emphasis on pounds of fat.

For your reference, feed efficiency is calculated as follows. Please note that Body Weight Composite within this formula is the new calculation to replace Body Size Composite.

Feed Efficiency = (-0.0187 x Milk) + (1.28 x Fat) + (1.95 x Protein) – (12.4 x Body Weight Composite)

In addition to the adjustment on the production bucket, HA USA will now incorporate livability as part of the TPI formula. The 3% weight on livability will come directly from that same reduction in emphasis on productive life.

What do these changes mean?

The new addition of stature to Udder Composite and Foot & Leg Composite, along with the TPI updates, are in place with an overarching goal to aid producers in creating more moderate sized, efficient and profitable cows.

Industry standard indexes can change at any point. These changes reinforce the importance of setting your own customized genetic plan. Work with your trusted Alta advisor to review the weights you place on each individual production, health and conformation trait. We want to help you ensure your plan always aligns with your farms current situation and future goals.

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Gestation length added as new trait

The Council on Dairy Cattle Breeding (CDCB) is adding gestation length as a new trait to be released with August 2017 proofs.

Gestation length can be most useful as a genetic tool for herds that implement seasonal calving. These herds will have the option of choosing service sires with shorter gestations for cows that didn’t settle to the first breeding.

Gestation length can also be a useful predictor of a cow’s calving date, which allows for more efficient management of close-up and maternity pen moves.

As of now, gestation length will not be included in TPI or the Net Merit index.

As new traits like gestation length are released, it’s important to keep your farm’s current situation and future goals front of mind. Work with your trusted Alta advisor to review your customized genetic plan. Only incorporate new traits like gestation length into your plan when they aid your farm’s goals and bottom line.

Learn more information about the research, heritability, and correlations behind gestation length, as presented by Wright, Van Raden and Hutchison at the 2017 ADSA meetings.

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Cow livability added to the NM$ formula

Starting in April 2017, the CDCB will include Cow livability into the Net Merit $ formula.

Cow livability (LIV) was introduced as a new trait in August 2016. It measures a cow’s ability to stay alive on the farm, and has a high (0.70) correlation with Productive Life (PL). The difference between LIV and PL is that PL measures a cow’s ability to be productive on the farm. It does not distinguish between death and culling as the reason for leaving the herd.

Cows that die on the farm are a great expense. In fact, based on cull prices, farmers could earn $1,200 less profit for each cow that dies on farm and cannot be sold for beef.

LIV is also correlated to DPR by 0.45 and to SCS by -0.25.

Net Merit changes

Net Merit (NM$) is an estimate of a cow’s lifetime profit to the farm. CDCB updated the formula for April 2017 proofs. It now includes new traits and revisions of traits using current incomes and expenses.

New changes include:

  • LIV is now part of the NM$ formula
  • Economic values are updated and current
  • Body weight composite (BWC) will replace Body size composite (BSC)

Relative values for most other traits included in the formula decreased slightly. The 2017 NM$ formula correlates by 0.989 to the previous NM$ from 2014. The table below shows the differences in the relative value of trait weights between the NM$ formula in 2014 and 2017.

TRAIT2014 NM$ TRAIT WEIGHT2017 NM$ TRAIT WEIGHT
Fat2223.7
Protein2018.3
Milk-1-0.7
Productive life1913.4
Cow livability7.4
Somatic cell score-7-6.5
Daughter pregnancy rate76.7
Calving ability $54.8
Cow conception rate11.6
Heifer conception rate21.4
Udder87.4
Feet & legs32.7
Body size composite-5
Body weight composite-5.9

The relative value of weight on PL decreases now that LIV is part of the NM$ formula. This adjustment will not hinder genetic progress for PL. Instead, it will increase the progress for LIV.

Body weight replaces body size

Since BWC is more closely related to the actual body weight of the cow than BSC, this change results in less selection against stature, body depth, and dairy form.

Finally, to account for updated milk component prices, the new NM$ formula increases emphasis on fat while decreasing emphasis on protein slightly.

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Introducing JPI 2017

With April proofs comes the introduction of JPI 2017 to replace the previous JPI 2015.

Jersey Performance Index™ (JPI™) is the American Jersey Cattle Association’s (AJCA) strategy for increasing lifetime net income.

The AJCA took into account the following three key fundamentals for Jersey sustainability while determining JPI 2017. These fundamentals were determined by a Capper and Cady 2012 study comparing the environmental impact of Jersey and Holstein milk for cheese production.

  • Increase production
  • Maintain body size
  • Maintain or improve components

What is the purpose of the new JPI 2017?

  • Increase milk production
  • Improve the density of milk
  • Moderate body weight
  • Improve herd life, fertility, udder health, and functional conformation

What new traits have been added to the formula? 

  • CFP Milk
    • Every 100 pounds of PTA milk needs 8.8 pounds combined fat and protein
    • Pounds of Milk = CFP/0.088
    • CFP Milk = PTA Milk – Pounds of Milk
    • If CFP Milk is positive, the JPI™ value is negative because there is more water than components
  • Body Weight Composite (BWC)
    • Proxy for feed efficiency, and replaces body size composite
  • PTA Cow Livability
    • Measures a cow’s ability to stay alive on the farm

What is the impact of JPI 2017? 
  • Significant drops in JPI for all industry sires.
    • The upper JPI threshold will drop from about 300 JPI to 230 JPI, and all industry bulls will drop in their JPI value.
  • Significant rescaling, similar to a base change.
    • We see genomic sires JPI™ values fall 38 points on average
  • Some re-ranking – in both directions
    • Some minor and some significant

Here is a full breakdown of the new JPI 2017. In the simplest terms, JPI 2017 has five percent less weight on production and five percent more weight on type traits as compared to JPI 2015. But there’s more to it than that. The following traits are new additions to the JPI 2017 formula.

Image comparing the genetic index weights on production, health and type traits for JPI 2015 versus JPI 2017

JPI 2015JPI 2017
Protein4330
Fat1515
CFP Milk-8
PRODUCTION TOTAL WEIGHT5853
Productive life106
Cow livability-4
Somatic cell score66
Daughter pregnancy rate77
Cow conception rate22
Heifer conception rate22
HEALTH TOTAL WEIGHT2727
Stature-0.6-0.9
Strength-0.1-3.4
Dairy form2.0
Rump angle-0.1
Rump width0.2-0.7
Rear Legs -0.1-0.1
Foot angle0.10.1
Fore udder2.62.4
Rear udder height1.91.8
Rear udder width0.10.1
Udder cleft2.11.9
Udder depth5.14.7
Teat placement1.00.9
Teat length-1.0-0.9
TYPE TOTAL WEIGHT1520
No time is better than now to sit down and review your genetic plan and strategy. When you set your own unique herd index, you will maximize genetic gains in the areas that most impact your farm’s profitability.
Focus on your goals and work with your trusted Alta advisor to create a customized index as an investment in your future.
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