August 2018 CDCB Sire Summary and New Lifetime Net Merit

Dr Marjorie Faust

Dr. Marjorie Faust

Annually the American Dairy Science Association holds a convention at which many of the latest research papers on a wide variety of topics on dairy management and dairy foods are presented.  This year’s convention was held June 24 – 27 in Knoxville, Tenn.   Our columnist Dr. Marj Faust coordinated and chaired a  session also supported by Interbull.  Here she presents summaries of the papers on dairy genetics and genomic topics. Click here

The release of the August 2018 Council on Dairy Cattle Breeding (CDCB) Sire Summary on Tuesday (August 7, 2018) comes with several notable changes.  These changes include revised calculations for Daughter Pregnancy Rate (DPR) and Cow Conception Rate (CCR), and updated and expanded calculations for the lifetime profit indexes – Net Merit (NM$), Cheese Merit (CM$), Fluid Merit (FM$), and Grazing Merit (GM$).

Revised calculations for Daughter Pregnancy Rate (DPR) and Cow Conception Rate (CCR)


After extensive research and testing, revised genetic models were put in place to improve and stabilize DPR and CCR for Holsteins and Jerseys.  Improvements are expected to have the greatest impact for younger animals.  As a result of the revisions, in the August evaluation data we expect to see DPR for younger Jerseys and Holsteins and CCR for younger Holsteins that are higher and more closely aligned with December 2017 results as opposed to their unusually low April 2018 results.  The revised calculations and August 2018 fertility trait results also will confirm what most herd owners see and experience in their herds – females born today will generally be noticeably more fertile than those born 5 to 8 years ago,.  The more accurate August 2018 genetic evaluation results illustrate that as an industry we’ve made significant genetic progress in improving female fertility.

Six Health Traits incorporated in the CDCB lifetime profit indexes – Net Merit (NM$), Cheese Merit (CM$), Fluid Merit (FM$), and Grazing Merit (GM$)

In April 2018, the Council on Dairy Cattle Breeding (CDCB) released official genomic evaluations for six health traits for Holsteins.  These six health traits evaluate genetics for resistance to Milk Fever (MFEV), Displaced Abomasum (DA), Ketosis (KO), Mastitis (MAST), Metritis (METR), and Retained Placenta (RETP).  For the August 2018 evaluations, calculations for the CDCB lifetime profit indexes have been expanded to include these economically important health traits.  As a result of these important additions, NM$, CM$, FM$, and GM$ now incorporate income and cost drivers accounting for genetic information from 36 traits using a lifetime profit function approach:

lifetime profit = milk value + cull value + value of calves

– milk harvest & sales cost – rearing cost – feed cost – health cost  – breeding cost.

Table 1 includes descriptions of the many economic factors accounted for in building the CDCB indexes and the associated economic effects from selection response for the 36 constituent traits.



Table 1. Lifetime profit indexes (NM$, CM$, FM$, GM$) account economically for predicted genetic differences in progeny.
Lifetime Profit Drivers How genetic differences in traits are accounted for in NM$, CM$, FM$, and GM$.
Income Generating Factors
Milk Value        As revenue for additional yield based on larger PTAs for Milk, Fat, Protein, and associated premiums for low Somatic Cell Score (SCS).

As additional milk sales due to optimal lactation lengths for cows with higher DPR; greater disease resistance (Milk Fever, Displaced Abomasum, Ketosis, Mastitis, Metritis, and Retained Placenta); and lower calving difficulty (Sire Calving Ease – SCE).

Cull Value        Larger revenue from cull cows sold for beef when Cow Livability (LIV) is higher meaning that fewer cows are prone to die, and when animals are larger/heavier (Body Weight Composite based on 5 Linear Type Traits).

Revenue from cull cow sales also is larger when fewer cows are lost during calving (Daughter Calving Ease – DCE, Sire Calving Ease – SCE).

Calf Value        Additional value of calves when Sire and Daughter Stillbirth rates (SSB, DSB) are lower, and when fertility rates via DPR are higher.
Cost Factors
Milk Harvest and Sales Costs        More Milk, Fat, and Protein mean that greater hauling, cooling, and storage costs are charged back against the values of Milk Fat, and Protein.

Superior genetics for Udder Composite (Fore Udder – FU, Rear Udder Height – RUH, Rear Udder Width – RUW, Udder Cleft – UC, Udder Depth – UD, Teat Placement – TP, and Teat Length – TL) and smaller Stature (ST) are associated with lower labor costs during milking.

Rearing Costs        More months of Productive Life (PL) are associated with lower overall costs for replacements.

Lower replacement costs also are associated with fewer reproductive culls resulting with higher Heifer Conception Rates (HCR).

Costs to raise replacements are lower for heifers that are genetically smaller (ST, Strength – SR, Body Depth – BD, Rump Width – RW) with more Dairy Form (DF).

Feed Costs        Additional Milk, Fat, and Protein require larger expenditures for feed – forage, energy, and protein.

Feed costs for maintenance are lower for genetically smaller cows (ST, SR, BD, RW) and cows with more DF.

Health Costs        Lifetime treatment costs are lower for animals that are genetically more resistant to Milk Fever (MFEV), Displaced Abomasum (DA), Ketosis (KO), Mastitis (MAST), Metritis (METR), and Retained Placenta (RETP).

Veterinary and labor costs also are lower when cows are genetically superior for DPR and are less prone to calving difficulty (Daughter Calving Ease – DCE, SCE).

Lower foot care and labor costs are associated with higher genetic merit for Rear Legs Side and Rear views (RLS, RLR), Foot Angle (FA), and Feet & Legs Score (FLS), and smaller Stature.

Breeding Costs        Savings from lower costs for breeding, heat detection, pregnancy check, and the associated labor are captured when fertility (HCR and Cow Conception Rates – CCR) is higher.

Additional cost savings from improved fertility are realized when calving difficulty is lower via SCE.

The CDCB genetic-economic indexes (NM$, CM$, FM$, and GM$) are extremely thorough in accounting for revenues and costs (direct, indirect, and opportunity costs), as well as the genetic responsiveness of this diverse mix of traits.  Today, this means that these indexes are powerful and comprehensive genetic decision making tools for dairies to select and breed more profitable generations of replacements.


Figure 1. illustrates the relative value of each trait or trait composite for each of the four CDCB lifetime profit indexes.

Additionally, it may be helpful to evaluate the different indexes based on grouping individual traits as:  yield traits (Milk, Fat, Protein), conformation traits (UDC, FLC), reproduction related (DPR, HCR, CCR, 4 calving related traits), health and fitness (PL SCS, BWC, LIV, Health Trait composite).

  • Net Merit $ – 44.4% yield traits, 10.1% conformation traits, 14.5% reproduction related, and 31% health and fitness (2.3% health trait composite)
  • Cheese Merit $ – 51.6% yield traits, 8.6% conformation traits, 12.4% reproduction related, and 27.3% health and fitness (1.9% health trait composite)
  • Fluid Merit $ – 45.5% yield traits, 10.3% conformation traits, 14.7% reproduction related, and 29.5% health and fitness (2.3% health trait composite)
  • Grazing Merit $ – 38.0% yield traits, 10.2% conformation traits, 29.0% reproduction related, and 22.9% health and fitness (2.1% health trait composite)


  • Who can benefit from using these new CDCB genetic-economic indexes?

Dairy managers who desire to breed more profitable cattle that are robust and that can work across a range of systems in the U.S. as well as around the world can benefit from using one of the revised indexes – NM$, CM$, FM$, or GM$.

  • My input costs and sales prices for milk and cull cows differ from those used to compute the CDCB indexes. Will our herd see benefits from using NM$, CM$, FM$, or GM$?

This is an extremely important question and so will be considered in some detail.

  • Prices need to reflect market conditions in the future. It is important to clarify that input costs and prices used in selection indexes should not necessarily look like prices today.  Instead, values used for genetic indexes need to reflect prices and conditions experienced by future generations of progeny, so 5 years from today and beyond.  The researchers who built NM$, CM$, FM$, and GM$ have incorporated future-looking pricing information into the indexes.
  • Scientists also have asked this question about how useful indexes are when prices differ, because of the volatility in prices experienced across time by dairy operations.
  • Price differences are not a significant factor. When studying prices, researchers have found that indexes are quite robust to price differences.  In practice, notable differences in the way two indexes rank the same group of animals occur primarily when the relationship between prices for different traits (milk:feed costs, as an example) are dramatically different.  For U.S. dairies, market situations where such atypical price relationships exist tend to be the rare exceptions.
  • The key research finding is that indexes are moderately insensitive to most scenarios of price deviations.
  • For NM$ for example, this means that it will correctly rank sires and dams for different NM$-appropriate herds regardless of differences in their feed costs, labor costs, electricity costs, etc. differ.
  • Based on research results, a majority of herds can be confident in seeing benefits from using the most herd-relevant CDCB genetic-economic index – NM$, CM$, FM$, or GM$.


  • If normal price variability is not a significant factor influencing the real world performance of indexes, is there a factor that is more important?
    • Traits included. A significant factor in the resulting profitability delivered by using a given index is whether all of the economically important traits have been incorporated.
    • On the other hand, when an important trait is omitted, and especially omitting those with undesirable genetic correlations, profit gains resulting from using this index will be suboptimal.
    • With the incorporation of these 6 health traits, dairies can expect to see greater effectiveness of NM$, CM$, FM$, and GM$ in identifying sires and dams for creating progeny that are profitable in the future.


  • Which of the indexes is best for our production situation and milk market?


  • Net Merit $ will be a good tool for most dairies.
  • Dairies that receive little or no premium for protein in milk are expected to benefit from using Fluid Merit $.
  • Cheese Merit $ is a good choice for dairies in markets with large premiums for milk protein and true cheese yield formula pricing which places a negative value on the non-solids fluid portion of milk.
  • With a sizable emphasis on DPR, Grazing Merit $ will be most relevant to herds with limited breeding periods such those using seasonal grazing.

In a follow up column, we’ll look at these indexes (NM$, CM$, FM$, GM$) and other more proprietary ones that are available in our industry.

This article by Dr. Marj Faust is part of a series of regular columns on breeding and genetics she’ll be preparing for DairyBusiness Digital magazine.

She was an R&D executive at ABS Global and Genus plc, served on the faculty at Iowa State University, and provided consulting services in regulatory sciences to Novartis/Syngenta Seeds and FASS. 

 Based in Madison, Wis. area, she is a founder and principal of Agri Innova LLC and Data Driven Genetics, where she and her team partner with established and emerging organizations as well as farming businesses globally to build strategy and deliver innovation. 

Readers may contact her with questions or suggestions at [email protected]