Saturday, September 30, 2017

“Custom Indexes” or what we used to call “Matrix Selection”

The previous generation of dairy geneticists who gifted the world with the “selection index” must be rolling in their graves.    These were the fellows who actually told us “just breed on Net Merit ranking and all your other problems will go away.”    At that time “Net Merit” was based 70% on PD Milk and 30% of PD Butterfat—no protein, no type, no fertility, no health trait measurements.  All those things were added after the cow population began to suffer in all of those areas (some of which those same geneticists tried to claim were “management” traits rather than heritable behavior, as we now know them to be).

Consistent through all the formulation and recalculation and creation of new measurements (some of which are quite arcane, perhaps less than 5% heritable) – the advice was always, “don’t focus on some specific list of traits, just let the selection index do the job”.    Indexes were promoted as “more efficient” than a dairyman making his own list of desired traits and setting minimum levels of trait expression he would accept—a practice known as “matrix” selection.    

For the 55% of dairymen who still use a “matrix” approach, the latest advice – “calculate your own index” (according to the needs of your current herd) – is a vindication.   So as not to offend their old college profs, these new geneticists just avoid the word “matrix”.   But in fact they are now telling us, “composite index selection is obsolete” (even though these are the basis for all sire selection being done under Genomics, which are calculated purely to the various national index formulas).    

Just ask Nate Elzinga of Zeeland, MI, one of Michigan’s most milk productive dairymen, how he chooses his sires.   His office computer is programmed to recalculate the data from every sire AI offers him, to the weighting of traits he devised matched the heritable traits he wished to address in his herd of cows.   Or ask Josh DeHaan of Wayland, MI, how much he was able to accomplish in improving all fertility characteristics of their expanding herd by a focus on health and fertility traits alongside matings to create balanced physiques.   Many of your neighbors may be requiring plus bf% and pr% traits who wish to raise their milk price and find they are $2.00 per cwt above their breed average after only two generations.

The famous Wally Lindskoog of Arlinda Farms, Turlock, CA shortly before his passing told an interviewer that he could see the future of AI developing many specialty AI companies, whose sire selection would not be based on an ”index” but on the genetic preferences of like- minded dairymen of similar geography or facility design and milk market.    We have seen this process occurring ever since Alta Genetics purchased Landmark Genetics.

How do you design your own herd index?

First, you look at your own economic and management data.    What elements of cow care and management are costing you the most?   Focus on whatever heritable measures may have an impact on those issues.    For example, if conception rates are an issue, then establish a minimum trait value for daughter pregnancy rate (not semen conception rates, which have no impact on your cows’ natural fertility capability).    If you lose too many calves at birth look at stillbirth rate; if you lose too many heifers to hard calvings, look at both sire direct and daughter calving ease.    Establishing dollar values for each of these types of financial loss helps to put all of your herd data in perspective of where genetic change could help.

Wednesday, September 27, 2017

Facing facts about fertility

AI systems today sell twice as many straws per calf born as they did in the 1970s, in spite of all the advances in technologies and near-universal adoption of “production medicine” approaches by veterinarians.    For many dairymen the cost of each cow pregnancy has grown to several hundred dollars (ultrasounding, pre synch shots, Ov Synch, multiple services per cow, sexed semen on heifers) as traditional fertility management (breeding on observed natural heats) has gone out the window for these operations.

What role did decades of ignoring genetic fertility play in this development?   We think the answer is simple—it is Darwinian to assume that “genes not exercised in the current environment will be lost to future generations”.    If we ignore fertility genes, they do not stay the same—selection for anything else (especially if negatively correlated to fertility) will result in a declining “genetic base’ for that gene expression.

Want to improve the fertility in your herd by genetics?    Use the tools already available; health and fitness traits, maternal pedigree screening for longevity, physical balancing of matings from the “aAa” breeding guide.     Your progress will be measurable. 

Monday, September 25, 2017

What does the statistical “heritability” of each PTA trait really mean?

Dairymen have a right to be confused about the so-called “health and fitness” traits, which faced a great deal of resistance from breeders and AI stud personnel who were trained to believe “genetics” was about PRODUCTION and TYPE.     Select for PTA milk and you get more milk: Select for PTA type and you get sounder type.     PTA Milk would make milk checks, and PTA Type would lower the herd turnover rates, reducing replacement costs.     Then along came “management traits” (so called by nay-sayers) to confuse the genetic selection and the index ranking calculations.    

The statistical measures of “heritability” indicate how powerful a selection response you get from each trait.     Traits are not equal:   “h2” for milk, butterfat and protein yield (pounds) is estimated 25%- 30%.
“h2” for butterfat % and protein % (density) is estimated 55%- 60% (twice that of yield volume).    You can feed for “more milk” but you have to breed for a “higher milk price” from bf% and pr%  selection.

In other words, the higher the “h2” [heritability%] of the trait, the less you can effect change by feeding and cow comfort and better milking procedures.      Linear type traits have a similar pattern of as high as 40% h2 for stature, 25%  to 35% on udder traits, generally 10% to 20% on feet and legs and frame traits.   

By comparison, the “health” and “fitness” traits (SCS = Somatic Cell score, DPR = daughter Pregnancy rate, PL = Productive life, LIV = livability, plus the calving ease and stillbirth PTAs) began life with a lower scale of “heritability” (5% to 20%).    Thus, in the opinion of those pedigree/type and index/milk breeders, these should remain secondary considerations.

Heritabilities vary with the calculation and the geography

Our experience with New Zealand genetics among grazing-based dairymen indicates that “heritability”  is not fixed in stone: it is an accumulation of the consistency of selection within a cow population.   In a seasonal breeding system, “fertility” is the key genetic trait, and multiple generations of selection in its favor appears to improve the heritability (NZ genetics sets “h2” of calving interval at twice the level we have observed in the USA).    

The data from our friends’ herd would certainly suggest a clear linear result between DPR selection and resulting days open—and it should, as this is the basis of the DPR calculation anyway.     We were told for decades that, if cows are to milk more, we must expect conception rates to be lower:  however, once dairymen quit accepting that line, and forced geneticists to study the data closer, they found some cattle are just a bit more fertile than others, and this could be tracked by family lines.

Body condition ability:  a key “environmental” variant in the search for fertility

Inside the dairy genetics mainstream, “body condition” is something for nutritionists to manage.   It has not been considered “genetic”, except as the linear type system (devised in the 1970s to identify young cows who would respond to more grain fed with more milk produced) actually preferred the cow that would delay body conditioning.     In other words, to 1960-70s geneticists, cows who gained weight if fed more grain were undesirable cows.  Today, with higher forage utilization, these genes are needed.

In the “aAa” (Weeks Analysis) system, we recognize what all other biologists recognize, that ability to maintain healthy body condition (a key indicator of positive nutrient energy utilization) is heritable.   It is not hard to figure out that always mating cows to be more angular will inhibit expression of + DPR.     

Friday, September 22, 2017

Anecdotal evidence of the heritability of fertility

All of us are aware of the relentless pace of new technology adapted to dairy management.    Within my lifetime we have seen the development of “OvSynch” hormones for heat synchronization, and then there came the radio pedometer system for natural heat detection.    There are signs that radio pedometers may already make “OvSynch” obsolete as the more effective reproduction management tool (as well as the way to avoid future issues with consumer concerns over synthetic hormones in the food supply)..

One of the farms where I have analyzed for 22 years made the switch from Ov Synch to pedometer heat detection on 400 cows.   Radio pedometers now provide an every-milking milk weight and conductivity (mastitis) score.   Cows in heat are not only identified, but an optimum time of breeding calculated. 

This farm has been selecting service sires on both maternal pedigree longevity and sire DPR rankings for several years, at least three generations for new heifers calving.    The herd manager walking pens would constantly see cows in heat, and found veterinary advice to “just breed on O/S” counterintuitive.  
He had an epiphany:  I have been selecting for fertility but my management system is not testing to see if that selection had any impact.     When their milking equipment dealer presented the radio pedometer option, he was ready to give it a try.

Comparing the up-front costs of radio pedometers and computer links to the ongoing costs of Ov-Synch, the initial calculations showed a four year payback.  ( Dropping once a month DHIA for daily real-time milk weight downloads made it 3.5 years. )   20% savings in semen used per pregnancy made it a 2.5 year payback.      As suspected, genetic selection for fertility had made the Ov-Synch program obsolete. 

More evidence of the heritability of fertility

One of our customers recently proactively assembled their veterinarian, nutritionist, DHIA consultant and major semen supplier for a conference to review the farm’s data and trouble shoot why conception rates are consistently below the goals of the owners (unchanged for several years).    I was invited to sit in as having recently analyzed all the milking herd (after ten years of random mating during expansion).

This farm milks 500 cows, which are housed as six groups in three free stall barns and fed by TMR. 
Production (which was at 90 pounds with 250 cows prior to ten years of expansion) is hovering a bit above 80 pounds, with higher than breed average components, but below the goal of the nutritionists.    Three individuals (two owners plus a key herdsman) do all the AI.    

After a general discussion to familiarize all these advisors with the veterinary, farming, feeding and milking practices, the three who inseminate had some practice with repro tracts and the AI rep made some pointers as to proper site of semen deposition.     (Avoid going too deep into any uterine horn.) 

No one questioned the role of genetics in large herd fertility.    The veterinarian figured they were doing everything “right” as far as vaccinations and herd health protocols.   The nutritionist found the feed quality to be equivalent to other high production herds.    Discussions eventually focused on how long cows stand in the (partially uncovered) holding area for milking, which (especially in summer heat) is a critical factor in retaining early pregnancies (body temps above 105F in sun can cause abortion of early stage pregnancies, undetected because the cow is able to recycle on her normal interval).   Major building modification (and maybe a faster parlor some day?) was the only real solution to this issue.

But if nothing is “wrong” in the daily routine, why do the cows not get bred?    It is exactly at that point that prior genetic choices must be considered.    The DHIA consultant agreed to run a profile on the sire stacks behind these cows, to see if there is a pattern between sire DPR and cow conception.

As of the latest DHIA test day, this farm had 112 cows confirmed as pregnant, whose sires were known.   Of those 112 cows (roughly 25% of the total herd, half of the sire ID herd) the data fell into four groups:

Bottom 25%:    sires’ PTA for DPR (- 1.725 or lower)      cows averaged 157 days open
The next 25%: sires’ PTA for DPR (- 0.35 to – 1.724)      cows averaged 166 days open
The next 25%:  sires’ PTA for DPR (+ 1.04 to – 0.35)      cows averaged 143 days open
The best 25%:  sires’ PTA for DPR (+ 1.05 or higher)      cows averaged 125 days open

Further examination (cows with known sire and grandsire recorded by DHIA) to compare “pedigree index” for DPR vs realized days open had 55 cows confirmed pregnant, as follows:

Bottom 25%: pedigree index DPR –0.865 or lower:         cows averaged 155 days open
Next 25%:     pedigree index DPR –0.35 to –0.864           cows averaged 206 days open
Next 25%:     pedigree index DPR –0.34 to + 0.59           cows averaged 156 days open
Top 25%:      pedigree index DPR + 0.60 or higher          cows averaged 121 days open

The real point of this data (supported by comparison of average DPRs for sires by birth year) is that until 2015 (when a change was made in who purchased semen) no consideration was given to the DPR values of sires purchased.   The breeding selection was random and based on how much PTA milk could be had for a special price.  Until 2015, the average PTA DPR for all sires was negative three years out of four

Sunday, September 17, 2017

Recognizing this, conformation (“type”) standards developed before milk weights.

Cattle breeds were first sorted between dairy and beef types, and then evolved into breeds by regional segregation and closed population mate selection.    Recognition that the geophysical environment was the primary determinant of which gene combinations were successful, breeds all developed their identity as bundles of traits that adapted them to their formative environment.    Physical qualities were the basis of heritable characteristics.    Bloodlines emphasized individual aspects of total breed expression.    

In North America, we work exclusively with animals imported from their native regions, adapted here to the world’s first specialized dairy industry to develop economically.    We began to weigh milk and keep records of yields, tested for butter content, formed breed associations to publish records and promote the heavier milkers as breeding cows.    The AI industry began in 1940 to spread these concepts, under their promotion of the herd health and human safety aspects of AI over keeping bulls on the farm.

For all our modern breeds, the leading cattle of the 1960s (more widely disseminated as a result of the new process of freezing semen) are known to be the progenitors of today’s cattle.    We exchanged the formative purebred bloodlines for the dominating AI sire lines (Ayrshire—Bettys Commander; Brown Swiss—Stretch; Guernsey—Royal Nance and May Rose Prince; Jersey— Secret Signal Observer; Holstein—Ivanhoe, Arlinda Chief and Elevation.)     Dairy extension and AI worked together to spread the “genetic value” gospel replacing all prior methods of pedigree screening, trait selection and compensatory mating.    All those efforts read us to Genomics as the culmination of what has been a “single trait” focus on composite trait index ranking.

The most profitable herds still utilize all the tools

It is just this simple.

You milk a physical cow that consumes physical volumes of feed, water and air, in a physically defined environment.    You must have a multi-functional and adaptable cow physique.    The most reliable and consistent method to produce uniformly functional cow physiques is “aAa Breeding Guide” (also known as Weeks’ Analysis after its discoverer Bill Weeks).

You face an economically competitive environment in commercial milk production and within what is known from statistical evaluation of the dairy macro-environment, genetic trait values will approximate the more currently successful sire lines.     This is the function of PTA values, and the latest realization is that (rather than depend on the ranking indexes used for genetic marketing) you should determine the traits most needed in your current herd and focus your sire selection around those specific traits.   Do not assume that your herd will need these same traits forever; re-evaluate each new generation to detect if (a) prior selection solved the old problems, (b) a new selection focus addresses any new problems.

Given that the mature cow that remains functional is your highest milk producer and will give you the most calves, longevity in the maternal line of sires you select cannot be overemphasized.    It is known by biologists that the best way to a long life is long-life parents; the best way to a healthy life is healthy parent lifetimes; the most profitable dairy herds are based on reproduction as precursor to production.
No cow gets old who is not fertile, no cow stays in the herd who is not competitive in productivity.  The heritability of maternal pedigree selection for multi-generational “longevity” exceeds the heritability of all the “fitness” traits (which are better used to screen out less fertile, shorter herdlife sires).

Above all, avoid popular “one size fits all” simplifications of the breeding process.   The ever-feared “inbreeding depression” is always a consequence of “single trait” [single index] selection.

Wednesday, September 13, 2017

The breeding program that maximizes cow life productivity

The average Holstein cow today produces milk for 29 months.    She calves the first time at 23 months of age, milks for 13 months, is dry 50 days, calves the second time at 38 months of age, milks for 15 months, is dry 60 days, calves the third time at 55 months, has metabolic disease, a failed udder or is chronically lame, and is sold (or dies) 1 month after calving…  milked a total of 29 months spread over a 33 month time period from a 56 month lifetime.   Thus the average cow is only in production 51.75% of her total lifetime… but she was eating your feed for 100% of that lifetime.

Statistically she produces 2.75 live calves, 54% bulls and 46% heifers, thus 1.25 heifers in her lifetime.
12% of all heifers never make it to a first calving, thus your net harvest is 1.1 bred heifer per cow life.   This heifer will average 17 months of age (six months shy of first calving) at the time of her death, so the average Holstein cow has not fully replaced herself at the time she leaves your herd.    This is the single most important reason why “gender selected” (sexed) semen, in spite of higher prices and lower conception rates, is so popular in the high production, technology-adapted dairy world— cow turnover rates force us to raise and freshen increased numbers of heifers.

Genetic “value” is imputed on the sire stack, and on that basis when using “ranked” mating sires, this heifer is “genetically superior” to her momma (with her now obsolete pedigree, no great loss?)   BUT I would beg to ask a simple question:  How can I do genetic selection among my heifers if I must calve every one to keep the barn full?    This is why genetic value is just an “imputed” (potential) value, only realized if we have surplus animals available that can be sorted for the improvement of our production profitability.                    

Profitability is not in genetic “value” but in gene-derived heritable value transmission

All cows and bulls possess a genetic blueprint in every body cell called the DNA which is a bundle of the gene pairs arranged on chromosome chains.   As this DNA blueprint interacts with its environment (first the womb, then the calf pen, then the heifer groups, then the breeding group, then the milking barn and at every step, the nutritional input, the weather input, the facility space, contemporary competition and the human input) and the result of that DNA/environmental interaction we call the phenotype… in other words, the realized cow as a physical living organism (rather than enzyme microcosm).

In Genomic theory as applied today, out of the three billion base pairs of genes, with 22,000 different gene types arranged on 60 chromosomes within each cell of our cow, 64,000 gene “haplotypes” are referenced to determine “genetic value” for one or some of the three conception traits, eight fitness traits, thirteen linear type traits, and five production traits now published by CDCI.   Thus the genetic valuation of your cow economically is based on a small fraction of her total gene pair possession.

Given 80% of her genes are “in common” with all other mammals, this is not as reductionist as it sounds initially.  These “marker” genes are the ones with the highest association with measured traits.  However there is no proof that these marker genes are causative.    Thus production traits are only 70% Reliable, type traits 55% Reliable, fitness traits 40% Reliable after Genomic calculations (which still include the “parent average” pedigree input we used to use, at 40% of the total value imputed, for “stability”).

In traditional breeding programs, the physical mating effect and the genetic trait selection were known to be different heritable gene-derived effects.    In other words, the genes that dictate realized skeletal and organic genesis and development are separate from the genes that dictate potential relative performance within a production management system.   

Sunday, September 10, 2017


From the November December 2016 Dairy Newsletter

In the early AI days, 1950s and 1960s, before the generation that expanded from stancion barns to open corrals and milking parlors, it was a typical breeding practice to service yearling heifers with beef bulls.

The reasons:   heifers were in surplus.    No one needed more heifers per year than their cows produced.  
Matured cows gave more milk than first calf heifers, so dairymen tried to keep old cow numbers higher.
Deacon beef calves brought a premium price over deacon dairy calves, a valued second income.

The herd expansion years of the 1970s and the cattle export years of the 1980s changed this greatly, as a market developed for all the dairy heifers we could raise.    These decades corresponded with the ascent of “index” philosophies in genetic selection, seeking faster maturing milk production and adaptation to a corn-based ensiled feeding regimen.   An unintended consequence of this was losses in cow fertility that took another decade to identify as genetic in origin (industry blamed hotter feeds, higher production and younger cow ages until large numbers of dairymen just abandoned purebreds for dairy crossbreeding).

Now we have processor choppers, TMR feeding concepts returning fiber to cow rations, also Ov-Synch reproduction and Gender-selected semen to keep cows bred and heifers coming.    Finally, we have this Genomic testing to tell us earlier in an animal’s life if they possess the genetic background to compete.

So we are back to breeding dairy cows to beef bulls…

It is the same scenario (create second commodity income streams) but applied differently, as everyone now wants to milk first calf heifers, and any cow who remains productive into maturity is nonetheless assumed “genetically obsolete” (although they milk 30% more than heifers)-- so get bred to beef bulls.
Meanwhile, we are to Genomic test every heifer (approx $50 cost) and breed the “better ranked half” to elite sexed semen (approx $100+ cost) to produce the majority of future heifers from the latest genetics.
The “lesser half” we are supposed to sell to unconcerned heifer growers for sale barn replacements.

Applied technology is producing all the dairy heifers the industry needs to meet milk consumption, but at a cost that may now be $300 greater than the cow auction market recovers.    Breeding less desirable cows to beef sires to create premium market calves, and only raising the dairy heifers you expect to need from your most profitable cows will have a positive effect on your cashflows.   

So do you wish to make those decisions on Genomics alone, or on the actual lifetime performance from your “best” cows on a more traditional basis of (a) do they breed on time, (b) do they stay healthy, (c) do they fit my stalls and parlor, and (d) did their production levels climb as they matured, avoiding the “fast maturity” genetics’ “faster aging” syndrome?    This has been the more profitable approach for decades

The latest in genome technologies is now available

By now, you have realized that Genomics offered nothing we did not already have—it just accelerated the turnover rate of sires available in most AI systems.    Because of its heavy (40%) reliance on parent averages, the pedigree pathways in genomic breeds are getting narrower, full sisters to ranking bulls are now the preferred bull mommas rather than pedigree outliers.    Phenotypic variation is much reduced, raising worries over the issue of inbreeding depression (canceling out the potential for genetic gain).

Then enters Zoetis (Genomic division of Pfizer) with something that does offer us new, useful information on the relative (genetic) incidence of six costly cow afflictions whose annual cost to dairying is in the hundreds of millions of dollars—dollars the current price of milk does not recover.     The best defense against inbreeding effects is to select among the healthiest and most fertile breeding stock and linebreed desirable behavior.    “aAa” will protect against inadvertent mating of similar genotypes, while positive selection for production, reproduction, feed efficiency and health will minimize failures.

Mich Livestock Service, Inc  “for the best in bulls”  

Wednesday, September 6, 2017

“DAIRY WELLNESS PROFIT INDEX” (DWP$) -The latest composite

You may be aware that Pfizer Company’s ZOETIS division is deeply into Genomics and has been researching “wellness” traits with the assistance of associate dairy herds (all the way from Michigan to Florida) that have generated reams of data on cows that have all been DNA-mapped.

Dr Dan Weigel (working from Zoetis Labs in Kalamazoo, MI) heads up this effort, which has special significance for us (Dan is the breeder of 99HO7070 Jehosophat at International Protein Sires).    He made a presentation to explain DWP$ and its supporting Genomic traits at the recent IPS Distributor conference in Wisconsin.    Their Genomic service is named Clarifide Plus.

Zoetis offers the following evaluations:  Mastitis (32% culling risk), Lameness (16% culling risk), Metritis (17% culling risk), Retained Placenta (31% culling risk), Displaced Abomasum (27% culling risk), Ketosis (32% culling risk).    Their research indicates costs of $117 to $494 per incidence for treatment of these various dairy herd afflictions.    Thus Zoetis assigns dollar values to the genomic possession of markers for resistance to these various issues.    This adds up eventually to the DWP$ once added to or subtracted from CDCB’s “Net Merit” genetic index values.

For the individual genomic traits, breed average is expressed as 100.   A sire with superior DNA markers will have a trait score above 100; a sire lacking those markers will have a trait score below 100.   Across the Holstein population, these scores range from a low of 69 to a high of 116 (the individual traits have individual ranges).    The Reliability % of these traits is currently from 49% to 51%.

Examples of enhanced sire data incorporating “Wellness Traits” (International Protein Sires)

Progeny evaluated sires:
566H 1199 Cambridge  Mast 108   Lame 104   Met 103   RP 104   Ket  106   DA 102   DWP$ 532
compare this to his calculated Net Merit of $299, and we find him to be an exceptional bull!           
099H 7070 Jehosophat Mast   95   Lame 101   Met 107   RP 101   Ket  108   DA  105   DWP$ 493
compare this to his calculated net Merit of $399, provides added value in five of six wellness traits.
006H 1157 Made Right Mast 106   Lame  99   Met 101   RP    96   Ket   99   DA  103   DWP$ 490
low SCS of 2.86, high PL of +4.6, now with LIV +1.7, low stillbirth 6.7%, clearly a “health” bull
566H 0588 Gilby           Mast   97   Lame 100   Met 110   RP  104  Ket  110   DA   99   DWP$ 486
exceeds his calculated Net Merit of $381, and in the top percentiles for Metritis and Ketosis resistance
566H 1247 Galt             Mast 101   Lame 101   Met 101   RP   95   Ket  105  DA  103   DWP$ 458
compare this to his calculated Net Merit of $341, and we find him to be a significantly better bull.
566H 1180 Rollag         Mast 102   Lame   95   Met 103   RP 107   Ket  105   DA 101   DWP$ 429
compare this to his calculated Net Merit of $330, and we find him to be a significantly better bull.

Genomic estimated sires:
566H 1265 Jenner         Mast 101   Lame 112   Met 111   RP 104   Ket 111   DA 106   DWP$ 1075
in the top five of all sires tested for “wellness traits”—compare to Net Merit of $778, a true outlier!
566H 1261 Jo Dandy     Mast   98   Lame 101   Met 103   RP 108   Ket  96   DA 106   DWP$ 1020
might he be the highest DWP$ choice for those also seeking the consumer-health A2A2 Beta casein?
566H 1267 Fix It            Mast 111   Lame  90   Met 104   RP   95   Ket   98   DA 107   DWP$ 1015
starting from an elite $801 NM, still a good boost to a sire whose +2.42 G Type draws attention.   
566H 1260 Storm Proof Mast 105   Lame 100   Met 100  RP 106   Ket 100   DA 106   DWP$  993
a significant bump from Net Merit $790, and pretty good for an elite +2680 GTPI cow family sire  
Genomic estimated sires:    (continued)
566H 1262 Diverse        Mast 105   Lame 105   Met 102   RP   99   Ket   95   DA 102   DWP$  970
who says four generations of “EX” dams with outstanding mature records cannot transmit something?
566H 1237 Milton         Mast 106   Lame 100   Met 104   RP 102   Ket 104   DA 103   DWP$  948
Michigan-bred from Powell’s best cow family, compare to Net Merit of $751-- realize hidden value.
566H 1263 Malcolm      Mast 100   Lame 101   Met 103   RP 100   Ket 106   DA 103   DWP$  927
all this health with exceptional +.17% +86 fat and +.08% +55 protein and low 2.79 SCS ($779 NM)
566H 1244 Ethics          Mast 103   Lame 100   Met 101   RP   96   Ket 106   DA 104   DWP$  915
compare to estimated Net Merit of $785, shows he has extra value in metabolic and udder health
566H 1251 Net Worth   Mast 101   Lame 101   Met 105   RP   93   Ket 111   DA 105   DWP$  888
gets five out of six right from a Michigan-bred cow line that shows consistency every generation

Some observations on interpretation

You will note that the range of IPS’ best Genomic sires is twice the $ value of IPS’ better progeny evaluated sires.    This is simply because DWP$ is a recalculation of Net Merit enhanced by Zoetis’ added insights into the genotype for those health characteristics that are major cost issues for dairy.
Higher-ranking Genomic sires are assumed to be a “generation ahead” of the better progeny data evaluated sires.     Thus it is best to remember that Genomic traits top out at 75% Reliability while the verification of milking and classified progeny is still needed to reach the most reliable 95%-99% level.

How does “Clarified Plus” compare to the patented AI stud health indicators?   

Being the first to go public with any new technology is usually to offer an incomplete solution to the perceived problem.  “Immunity Plus” for example neither grades bulls on the relative levels of their
gene possession nor covers as much trait territory as does the Zoetis “Clarifide Plus” technology.

I expect you will observe that the major AI systems will all gravitate toward Clarifide Plus rather than attempt to develop their own, more limited versions.    Pfizer’s great resources dwarf those available to any individual AI system, and anything related to interpretation of the Genotype demands resources in computing power usually only available to government or university research collaborations.   Mostly, Zoetis’ novel approach to ranking the economic values imputed to avoiding these various cow problems helps us sort among bulls where it soon becomes apparent that there is no “perfect” bull—you have to make some decisions that prioritize the traits most important to your herd at this generation of cows.

The biggest disadvantage to any single-stud proprietary system is that  it compares against that stud’s average, NOT the attained breed average.    We have already seen the disparity from sampling to 99% distribution on type proofs, for example—bulls who begin at +2.00 and end up –1.50 once they face the rest of their contemporaries, not just the “in house” populations held captive by full-service contracts.  
The Zoetis data comes from herds that offer a full cross-section of the competing genetic AI programs and involves millions of fully documented health episodes, and is an ongoing research today.

At no extra cost

At this point it appears we will eventually have Clarifide Plus “wellness” data on Genomic tested sires from all our major sire sources.    Currently, this technology is limited to Holsteins.   (Zoetis does make this technology available on farm for testing your cows and heifers, should you wish to pre-select which heifers you raise for replacements (allowing early sale of those surplus to your needs).) 

Sunday, September 3, 2017

CDCB introduces PTA “Cow Livability” to the mix of dairy evaluation traits

From the September October 2016 Dairy Newsletter

In July, just before the August release of the latest Genetic progeny evaluations (Genomic imputations are calculated monthly) AIPL announced the addition of “Cow Livability” to the list of PTAs they are calculating for Dairy sire genetic evaluations (this is not as yet calculated for cows, just their sires).

“Cow Livability” [PTA- LIV]  is defined as the ability of a cow to stay alive.    It seems that on average 7% of all dairy cows in DHIA herds die annually (including cows euthanized as “downers”).    Over the average of three calvings per cow, this leads to 20% of all cows leaving our herds will not produce any “salvage” value (cull cow income).    Death loss therefore currently averages $200+ per cow milked.

Prior to calculation of “Livability” we have had 21 years of “Productive Life” PTA measurements, that tell us the relative number of months cows lactate in our herds compared to herdmate averages.    Data shows that the inclusion of PL in genetic reports reversed a five-decade trend in which average herdlife lost 16% (canceling much of the gain in production levels from genetic selection).    As a related trait, Somatic Cell Score (PTA- SCS) also quit rising, and is now part of the estimation formula for PL for Genomic and newly progeny-proven sires.

When a cow must leave, culling generates income whereas death generates expense.   The salvage value for culled cows that walk on a truck over a year’s time is significant to all dairymen.    LIV is an attempt to sort this out, and will eventually be incorporated into $NM (Lifetime Net Merit).

Our perspective is that LIV might be more pertinent to the prediction of “longevity” than was ever true of Productive Life (PL).    All PL tells you is the sires mostly likely to produce short herdlife cows, and (because there is a link between high SCS and shorter herdlife) this has its own value—but for those of us seeking to generate increased herd production (from mature cow capability) and a second cash flow from surplus cows (beyond culls), longevity involves making physically balanced matings and seeking bulls from cows lines of proven lifetime capability.    Such cattle are more likely to look good on LIV.

I recently enjoyed a presentation by Don Bennink, the owner of North Florida Dairies (4000+ purebred Holsteins milking) who documented from his herd records that healthy mature (3rd and later) cows are producing 30% percent more pounds of milk than first calf heifers.    He is one of the leading breeders in favor of selection on fertility and health measures with balanced matings—his herd is now closing in on a 30,000 pound herd average (note- we’re talking Florida, heat, humidity and lignified forages!!)
Many of the No-Fla prefix sires found in AI systems descend from a 375,000-pound lifetime “Rudolph” (found as a young cow in Pennsylvania) that has generated a cow family from her female descendants.
LIV is among the measures Don is now using to screen future mating sires.