Tuesday, December 30, 2014

It was probably inevitable

From May 2010 Route Letter

USDA’s Animal Improvement Programs Laboratory (AIPL) over the past two years has developed AI conception rate summaries for sires, assuming calculations previously done by regional Dairy Records Processing Centers (DRPCs) such as Provo, UT and Raleigh, NC.

Now it appears the Sire Conception Rate data will not be updated for April 2010 summaries—it seems that one of the larger midwest DHI programs (owned by an AI cooperative) only chose to report data on sires with “their” stud code!        (AIPL’s website indicates they will address these problems.)

Sire summaries for production, health and fitness (fertility) traits are only as good as the data collection and on-farm sire ID procedures used by DHIA.    Nationally, almost half of DHI data arrives at AIPL in a condition that indicates errors, thus throwing it out for sire and cow indexes.      

If you are on test, do not take shortcuts with the data you submit to testers who are not being paid extra for getting the paperwork correct.    If you need our help with sire registration numbers (simple format errors in the number of zeros in a stud code will get sire IDs thrown out) let us know.   Also do not let testers determine your culling reasons for why cows leave—all this information has genetic value only when it presents causes accurately, rather than a pre-conceived (thus historically biased) picture.

Monday, December 22, 2014

Net Merit? TPI? Type? Pedigree? How should we pick bulls today ???

The next USDA “base change” is going to occur in 2010.     This means the range of PTA yield values will be slightly reduced.    This change usually subtracts 500 pounds of PTA milk from historical sires, and readjusts downward all current sires according to the relative performance of most recent offspring.

Dairymen today pay less attention to sire evaluation changes than was true ten+ years ago—today it is mostly a concern of purebred breeders trying to compete in the “numbers” game.    But many AI sales people try to inject excitement back into sire selection by making a big deal of base changes—the time when “old” bulls get culled, and “new” bulls show up at the top of indexing lists.

Given we have had +2000m sires for four decades, at the top of AI offerings, and frozen semen to make them more easily available, why is the average base change only +500m per generation?

Is it that we are not able to manage that rate of production gain within basically “fixed” environments, feeding technology our only way to “upgrade” facilities to higher genetic potential?    Or is it, as many commentators always suggest, “we place too much emphasis on ‘secondary’ traits like type”??

Indexing formulas change while no one is looking

In a recent conversation with a fairly aware young Holstein breeder, I was surprised to learn he did not know that, in the current version of “Lifetime Net Merit” (USDAs primary sire ranking index), pounds of Milk carries a zero $ value.        That’s right—times have changed since Clint Meadows taught us all that “PD Milk is the primary selection trait”.     Today, when you analyze milk checks, gross milk yield is equated with the water left after you remove all the Butterfat, Protein and Mineral solids… those milk components that make milk unique and marketable.

Likewise, every couple of years, Holstein’s TPI formula, or Jersey’s JPI formula, will go through some massive recalculation, usually because breeders become dissatisfied with the cumulative impact of the trait preferences of the prior version of the formula.     As casual semen buyers, we see the same term of “TPI” or “JPI” so we assume using it for sire selection keeps us consistent.    In fact, it is pushing your herd from one fad to another, and may not be helping you solve problems unique to your herd a bit.

When you challenge the orthodoxy of “ranking index”, everyone thinks you are crazy—but on any level of biology related to gene pairing, trait heritability, or physical adaptation, the Rel% of an index is zero.   
Indexes were designed to sell semen and embryos—not to guarantee cattle improve from matings.

What kind of cows do you wish to milk??

There is a common sense reason why people today select on more than just PTA Milk.   They wish the increases in milk production to be sustainable, they wish the increases to be cost effective, and they wish to avoid a loss in milk price per cwt as the volume of milk produced increases.

The only way to look at “more genetic milk” is to first determine what changes in milk production will produce the most income gain on your dairy.    For anyone whose SCCs are too high or whose blended bf% and pr% are too low, the more important become pounds and percent butterfat, pounds and percent protein, and lowering the SCC selection level (3.00 is standardized breed average).     Higher bf% and pr% will raise milk price, both on the attained “management” herd average, and the genetic gain if any. 

How important is type?

The less “type” you have, the more important it is.    Why?    Because improving “type” has more impact on reducing the incidence of short herdlife cows, than it really has on gaining cow longevity.  

Weak traits (shallow feet in combination with refined bones, loosely attached udders in combination with weak ligament supports, bad teat placement with strutting teats, shallow and/or narrow chests) can indicate a short herdlife.    When the overall animal just looks “frail” to the classifier, the net result will also be a lower final score.     The highest correlation among bulls with type problems and a negative Productive Life (PTA- PL) is that daughter score averages below 76 indicate “below average” type even if the bull is plus PTA Type (his daughters are bad, but the herdmates were worse= “plus” type).

Type data would correlate higher with PL ratings if the scoring system would (a) quit comparing the new heifers to contemporaries, instead compare them to a minimum standard of functional traits; (b) give the wider bodied heifers more credit for “dairyness” [reduce the weighting of ‘angularity”].

What really drives longevity?

No single trait has more impact on longevity than cow fertility.     Think about your own herd and be honest--   (1)  If an “ugly” heifer breeds back on time, you will keep her; (2)  If a “pretty” heifer does not breed back, you will sell her.      Likewise, no matter how much a heifer milks, if she does not breed on time, and drops below x pounds per day, you will sell her to make room for the next fresh heifer.   Thus all other traits being equal, Fertility determines how long a cow stays in a dairy herd.

Next to “fertility” we also need “health”.    In a broad sense, as an unhealthy cow cannot sustain a level of production profitable to the dairy, only healthy cows are retained for future production.    One of the most important health researches was the Canadian study in which it was found that higher SCC heifers  do not sustain predicted higher levels of production in second or later lactations thus indicates a faster aging, shorter herdlife, and a lower lifetime milk yield.     [The exceptions will be really high bf% and pr% sires—due to inexact methods of SCC testing in use.    “SCC” is not specific to mastitis infection; heel warts and foot rot are more likely to send a cow’s SCC through the roof.]

Foot and Leg problems will cull cows quicker than poor udder traits.    Poor mobility will cause a cow to spend less time at the bunk eating—more time lying in her stall (or in the alley).    Poor udder shapes we put up with as long as lots of milk can be pried from that udder.     Unfortunately, the two most primary type determinants of good mobility—(1) Thurl position, (2) Front leg position—are not measured in any linear type scoring system.     [The “aAa” breeding guide does analyze Thurls and Front Legs.]

Create your own trait selection matrix – then mate cows for physical balance

The lesson in all this is—approach sire selection additively, seeking sires strong in those traits costing you the most in your present herd; approach mating physically, matching sires to cows to produce more structural balance, as well as more uniform expression of growth rates, size and dairy capacity.

Selecting for more PTA Milk than the current frame capacity of your cows (and energy density of your forages) can sustain, is a wasted genetic opportunity.    Mating cows randomly, believing a higher index on paper is going to produce a more lifetime productive cow on the hoof, misunderstands a primary fact of biology: you can only breed a cow to a single bull, not to an “average” of his breed, or the index rank

A sire selection based on longevity of production produces a second income—
                                                                                  From surplus reproduction.

This is part of the message that has always sustained independent AI distribution, and made a good income for its many customers—the understanding that genetic selection can accomplish a multiple of goals simultaneously.

There never was much sense in the “if you want the most milk, you can’t select for type” line—that is a result of obsolete single trait selection concepts.    What has been overlooked is that “index” ranking was really just a continuation of the “single trait” preference of armchair geneticists who could get excited on which bull has the highest (PD Milk) and later the highest (Net Merit).

Single trait selection has been proven to be a failure at sustaining both genetic gains and profitability.    If you wish a sustainable approach to dairy productivity, you need a different, sustainable process for genetic selection, mating and reproductive efficiency.    

Friday, December 12, 2014

Tired of alfalfa weevil? Try higher energy mixed seedings

This will sound pretty simple, because it is.     The majority of insects (like alfalfa weevil) do not like to eat “sweet” plants.    They attack low sugar content plants (like alfalfa).     If you are having trouble with alfalfa weevil, it has two causes: (1) low sulfur soils inhibit the “energy” value of alfalfa, (2) alfalfa even in its optimal state is not that high a “sugar” forage.     The biological solution to scaring away weevil is: plant it with “high energy” grass varieties.    Straight alfalfa is really an obsolete forage concept.

Your cows’genetic encoding is to eat grass.     As we switched her to corn-based diets we had to find the forage that would produce lots of protein to balance, and alfalfa (plus soybean meal) became the focus…  but as costs of corn/soybean culture have risen, the energy superiority of grass (also a protein source) is coming into play.     BUT—you have to select grass genetics just like you select corn and alfalfa, for the total nutrient package they bring.    This is why Byron Seeds offers a different perspective on forages. 

Ants, on the other hand, like sugar.    If you want to tell whether a corn has the sugar content needed to give you more complete fermentation and higher digestibility as a silage, lay fresh cut stalks next to an anthill—and see which corn variety the ants pick first.    In most cases, it will be Masters Choice corn, the independent corn company that won the World Dairy Expo corn superbowl this fall (2009).

Wednesday, December 10, 2014

Tired of the variables of Euro Red crosses? Try LIC New Zealand sires

Research after research from around the world is beginning to show a consistent message:  Sires from LIC New Zealand out compete any Euro Red breeds tried in crossbreeding trials.     Beyond that, there is a recent study from Switzerland, in which pure “Holstein” (75% New Zealand Friesian x 25% North American Holstein) heifers from Ireland were raised and milked in Switzerland, competing with their native Fleckveih, Montbeliarde and Braunveih cattle.   New Zealand Friesians produced more milk and milk solids yields per acre, and reproductive rates were better.

I visit many herds in which Swedish Red and Montbeliarde sires have been tried, in an attempt to gain on health and reproductive traits (compared to Holstein contemporaries).     While some feel the traits they desired were acquired, the inconsistent milk yields have been disappointing—and in many cases, bad disposition issues increased.    Based on the visual type, I do not see long-term udder traits either.  

I think anyone who has tried crossbreeding needs to consider the LIC New Zealand Friesian option – sires chosen from a larger sampling pool and evaluated both by Genomics and large progeny data sets.
NZ Friesian sires compete and succeed on “Net Merit” directly against the US Holstein base, and their semen is more competitively priced.              

Saturday, December 6, 2014

The Process of Mating and Selection for an on-site Herd Sire

                 (December 2009)             by   Greg Palen                 Netherhall (polled, grazing) Jerseys

Why Raise any Bull?

Artificial Insemination was first organized in the USA during the 1940s, to accomplish several goals of dairy cattlemen:  (a)  Make dairying safer  (bulls can be dangerous, both to people and cows);  (b)  Eradicate venereal diseases (bulls can spread trouble, like brucellosis, vibriosis, and trichinosis, all causing infectious abortion);  (c)  Improved herd management  (have more exact dates for breeding, thus dry off and due dates);  (d) Put a productive cow in the bull’s space (incremental income gain, lower net reproductive expenses);  (e)  Provide genetic variety (avoid having all your “eggs” in one “basket” of unknown genetic value).

After six decades of commercial AI activity, however, many dairy farms continue to use herd bulls, or have reverted to their use after trying AI and not always succeeding.     Problems that lead to natural service reproduction include:  (a)  No one on the dairy has good insemination skills,  (b)  Commercial AI service is not available in that area,  (c)  Personnel lack the skill for effective heat detection,  (d)  Facility design does not acccomodate AI easily,  (e)   Preferred breed of cattle is not available within any AI system,  (f)  Selection traits of interest to herdowner are not considered important by those in AI who are selecting which bulls enter AI service,  (g)  Dairy suffers under a skilled labor shortage,  (h)  Herdowner has a passion for genetic selection and wishes to develop his own bloodline(s).

While many of these problems can be solved, not all herdowners wish to invest the time and money, or have elected to defer the introduction of AI to a later time, after more immediate needs are met.   It is also not uncommon for many dairies to use AI in tandem with natural service, for example:

Seasonal calving windows under grazing management

In this scenario, where animals live in paddocks (rather than barns) and calving is not desired all year long, progressive graziers will focus AI on two to three cow cycles, first introducing the service bull to the virgin heifers, and then moving him with the cows to “clean up” any still open after 4-6 weeks’ AI.
This program focuses heat detection on cows being milked twice daily and thus closely observed, and gets heifers (under less observation) to calve in the same season as the cows.

High group – Low group feeding in confinement

In this scenario, the AI activity is focused on the fresher cows, who are grouped in the same pens and thus are all “open”, most are cycling, and will be more likely to exhibit detectable heats (known as the “dormitory effect”) from a consequence of “gang” cycling activity.

Pregnant cows are moved from the “fresh” group to a “bred” [low, ie, not as fresh] group, thus hardly any cycling activity is going to be detected.    Putting a bull in such a group insures “someone” is still doing heat detection, to catch cows that reabsorb, or who are moved there after repeated AI attempts.

Gang bull breeding
Some very large herds will insert multiple bulls into large cow groups to stimulate earlier repro.
Why not buy such bulls from a higher-profile breeder?

In most cases, this is what we do, and it comprises a steady source of added income to the purebred breeders in dairy communities.    As these are guys investing a lot of time and money into the type classification and official milk testing of their cows, maintaining accurate ancestral identity, perhaps utilizing some added repro technology (embryo transfer, cloning, genomic testing, etc) and focusing their semen purchases on the “elite” ranked sires of their breed, we just assume their cattle have more transmitting ability (capability of genetic improvement) than our own.    After all, these are the herds producing bulls for the various AI systems, who promote higher “genetic value” sires.

The dairyman not utilizing AI but who believes the AI sires are clearly superior, is highly likely to do just that—in fact many ET full brothers to AI sires end up as “jumper” bulls in dairy herds.   This is a natural economic consequence of the propogative technologies (super ovulation and embryo transfer) as well as the further level of screening AI systems now do from the availability of Genomic testing (DNA mapping) which is reducing the number of “full brothers” being sampled by AI studs.    While more pedigree (sire x dam) combinations are resulting from Genomic screening, this also means more surplus sires are being propogated.     [Studs expecting to sample 240 young sires annually are writing 1200 sire contracts, but only taking one out of five bull calves produced, based upon which one has the highest Genomic estimates of “genetic value”.]

The addition of Genomic testing to the sorting of ET sires may imply the bulls left for natural service do not possess the desired DNA markers.    This should give us pause—do we wish to use a “reject”?

Reasons you may prefer to raise your own herd sire

First, there is the herd health issue.    You do not have a “closed” herd (closed to any possible disease exposure that could come from new animal contact) if you keep bringing in bulls from other farms, in which the health status and disease exposure is different from yours.    Raising your own herd sires is a way to more fully reach a “closed” herd health status.

Next, there is the issue of “selection trait focus”.    You may not agree with the trait selection priorities of those breeders accessible to you and raising jumper bulls.     This is an issue that is growing bigger each year.    For example:

Organic dairy production.    Certified organic producers need “healthy” (disease resistant) and self- reliant cattle.     Some of the higher genetic value animals, bred to more extreme performance levels, demand a higher level of feed supplementation and daily labor care to maintain their productivity, or in more cases, their reproductivity.   In an organic production model, where antibiotics and hormone therapies are not allowed, such genetics may result in higher than desirable cull rates.

Polled heads.    Dehorning as a dairy farm practice is already an “animal rights” issue in Europe, thus an increasing veterinary expense for EEC producers.    Likewise, in subtropical dairy areas, where no winter occurs to break parasite cycles, polled heads avoid a lot of wound infections and growth rate setbacks.    Graziers calving outside in tight seasonal windows, raising spring calves in paddocks, find the dehorning job to be onerous, and occurring in the “fly season”.    Thus, demand for polled cattle increases, while the supply of polled AI sires grows very slowly (and is mostly heterozygous polled, ie, still producing 50% horned calves in horned herds). 

Specialty milk production.     One of the developing market niches is for “A2A2 Beta Casein” milk, a genetically-determined milk quality claimed to have health benefits to those recovering from cancer.

Likewise, a dairyman who has entered on-farm artisan cheese production for retail marketing of his milk, may wish to select for “BB Kappa Casein” milk, a genetically-determined milk quality that will raise cheese yields 10% to 15% over conventional blend milk at the same levels of bf% and pr%.

Why are premium gene traits for milk composition mostly ignored by AI?

While most AI systems test for Beta Casein and Kappa Casein genotypes as part of the screening tests for Genomic evaluation, the data is neither routinely published nor does it have much impact on which sires are chosen to enter AI service.    Likewise, sires rarely get the nod for AI due to being polled, as long as some other bull has a higher ranking on some screening index.    Commercial AI selection is driven on “ranking indexes” rather than trait selection matrixes, virtually worldwide.    

The justification for ignoring unique selection traits is mostly driven by the commodity focus of milk cooperative marketing, where milk from different (and unique) farms is “pooled” – first by the milk haulers, next in the silos of the receiving plant--  any market demand for a specialty milk composition is only provided if it can be accomplished at the balancing plant by separation and reconstitution.   As local AI systems merged into regional and national entities, their interest in providing all sires for all local tastes (breeds) (bloodlines) (trait mixes) has declined, looking only at broad market statistics to make decisions as to future sire selection preferences.

Most purebred breeders raising bulls are thinking about the AI market, not you

Purebred breeders using OvSynch, superovulation and embryo transfer, Genomic testing their cows, are focused on the AI sire paradigm.    They wish to recover those costs from premium bull sales to AI studs and premium embryo sales to other breeders wishing to enter this “index” driven market.

Thus, buying a bull from them to breed your cows is like using year from certified bank-run seed to plant a wheat crop.    You did not get the “best” genetics but you got a close approximation of those genetics.    Thus the question is as follows:   Do I want to breed cows just like the commercial AI cows for my herd?    If so, save time and buy your purebred neighbor’s left over ET bulls.

If, on the other hand, you have more specific selection goals, or a more unique focus in milk quality production, and your management environment and/or milk marketing differs from the commercial, commodity definition, you either have to raise your own herd sire  or  seek breeders who already are focused on producing the sort of genetic mix you wish to gain.

In saying this, I am firmly identifying myself as a dairy industry contrarian, in that I do not have a blanket belief that AI sires are automatically superior to what you could raise.    I remain a firm believer in AI as a useful tool that can help you become a better stockman, as well as a more profitable businessman.   When all the costs are accounted, basic AI technology saves you money over average natural service results.     We sometimes just have trouble recognizing what those costs are.

The large number of custom semen collection businesses (and not just in areas driven by beef breed cattle breeders) suggests that many today are utilizing AI, but from their “own” stable of sires.
You really have to have sound reasons for raising your own herd sires, to bear the added costs.   In some cases, specific (unique) genetic goals justify the added costs.    In other cases, the opportunity to develop a niche market for bulls from your farm can justify the added costs.    In either case, you may still find that you still wish to have access to AI technology as well as sires you can source via AI, to get all of your genetic “bases” covered.      

Where do I start to produce a useful herd sire?

Dairymen milk cows.     98% of all dairymen produce an income stream based entirely on what cows produce (milk, replacement heifers, deacon bull calves, and cull salvage).     Only 2% of all dairymen generate meaningful farm income from breeding bulls, and only a fraction of that 2% are able to sell bulls into AI systems on a regular basis.

A useful herd sire thus has to be produced from the perspective of what is a useful cow.    (This should be the first point at which you start to question the current market fixation over “sire index” rankings.)  

What do you mean by a “useful” cow?     Simply put, a cow is “useful” if she can successfully do all the functions you ask of her each season.    Can she calve a live calf?   Does she get up and get going as a milk producing cow after calving?    Will she rebreed at the time your calendar prefers?    Does she avoid added costs that reduce the profitability of her production (vet assisted births, milk fever, metritis, ketosis, displacements, hoof trimming, chronic lameness, mastitis, induced repro after failure of natural heat insemination, long dry periods, fatty liver post-calving)?    Are her calves vigorous or prone to pneumonia, scours, finicky eating habits, poor at making transitions?     Does she have the type to enhance your herd equity and make daily milking easier?    Does she have the physique and behavior to adapt to seasonal or structural or nutritional changes in her environment?

It should be evident from such a list, that our traditional measures of cows—DHIA milk test records and Breed Society type scoring—only scratch the surface of answering the “useful” question.   But a good on-farm record keeping system designed to observe and record “usefulness” will make a sound basis for the selection of cows who can produce “useful” herd sires.

Analyze your “useful” cows from a “lifetime performance” basis

The dairyman just starting out can have difficulty determining whom his most “useful” cows are, as it takes more than a single lactation to answer all those questions posed above.   It is for this reason that many traditional stock breeders preferred the oldest successful cows to be “bull mothers”.    This flies in the face of the “newest generation is best” fast turnover of pedigrees in commercial AI selection, a market that routinely buys bull calves from first lactation cows.   But bear with me on this.

Each year is different.    Different weather produces differences in forage qualities and quantities, can impact on daily comfort of cows, can affect the prices we are receiving for milk and produce years in which we tighten our belts and reduce input uses to those we can produce internally.     If you judge a cow on a single year of performance, you will overlook factors of adaptability—was it a good year to be a cow at your place, or a tough year?      Basically, analyzing cows over an accumulating lifetime of performance is a better guide to answering all the questions posed regarding usefulness, even if you are not convinced of the economic advantage many of us assume for cows with longevity.

If you find you are only saving bulls in years where performance came easily, you will not be putting enough selection pressure on adaptive and longevity characteristics.    Such bulls will produce milky heifers but may not possess the genetic qualities to make them equally useful in difficult years.   This is ultimately why we sometimes see most of our mature cows culling out in a single year—we did not produce them from selections (and matings) that took longevity and adaptability into full account, and they could not survive all the challenges thrown at them in that year.    Lesson one:  Save bull calves from “survivors” – not just from pretty heifers.

Cow families develop around more useful cows.

For the dairyman who has had his herd awhile, has thought about breeding quality and done some trait selection, a symptom of success will be the existence of cow families in the herd.    A “cow family” is an extended line of maternal relationships.    It can be a multiple generation of cows descending from a single older cow; it can be a group of cows all descendent from maternal siblings.    The point that we need to see is this—a cow who has successful fertility genes and normal herdife survival will produce more heifers in her lifetime than a cow of mediocre fertility and average herdlife.   These heifers in turn, if bred to the same or higher level of ability, will also produce more heifers.    “Cow families” accumulate in soundly managed dairy herds as a result of superior genetic fertility and longevity.   In the experience of those breeders who were concerned about this, it is consistent that these “maternal” traits would follow cow lines directly, and thus sire lines indirectly (as cow fertility genes are easier to verify from the maternal side of pedigrees).

Bull fertility is pretty simple compared to cow fertility.    All the bull has to do is develop a healthy set of testicles, not be overconditioned when young to avoid fatty tissue in the testes, learn to jump-mount and have enough libido to either serve cows or collect semen.   In the case of AI, his ejaculate must have the volume of sperm cells, and those sperm cells must have the vigor to survive the freezing and thawing process under conventional (1/2 cc straw) packaging.    These are the relatively simple factors of bull fertility.    AI studs feed high energy rations to bulls on full collection schedules so as to keep a stable level of body condition as a support to their libido, and restrict their collection to a two or three day per week schedule determined by the volume of sperm production.

Cow fertility is more complex.    Cows, on the other hand, have to fit their reproduction around cycles of ovarian activity that are driven by hormones produced in various glands.   Cows do not “produce” eggs like bulls produce sperm cells—they are born with a lifetime supply in their ovaries, and instead their cycles are designed to mature and then release an egg according to their body schedules.   All of this has to occur around the physiologic demands of milk production and the post-calving recovery of the uterus.    Periodic calving alters and ultimately ages the cow’s body in ways that sperm production never could for any bull.     This is true for all mammals, as the fetus is incubated within the body of the mother of the species.   (The father is just a passive spectator by comparison).

Natural service bull fertility is different in execution from AI service fertility.    Over decades of the advancing technology for semen collection and sperm preservation, we have advanced from chilled, liquid semen (good for a few days) to frozen semen (storable indefinitely)—we have advanced in the freezing knowledge from fat ampules (that killed a majority of sperm cells) to thin straws (that save a slim majority of sperm cells), with two consequences:  (1)  Straw technology enhanced the conception rates of marginal sperm quality sires;  (2)  Volume semen production created a preference for sires who will serve the same animal repeatedly and deplete their semen reserves at collection frequency.
In a natural service environment, the preferred bull behavior would be to serve the cow in heat  once and then walk away, seeking the next cow in heat.    This means the bull holds semen in reserve for a potentially next cow in heat the same day, and does not expend his systemic energy in those repeated mounts that, in a herd setting, lead to a loss of body condition followed by a loss of libido.

AI is not fond of such sires, because they do not want bulls that have to be collected daily to harvest all the semen they can produce.    This interferes with their full schedule of collection and processing of a larger stable of bulls.    Has this had negative fertility consequences?     To date, no one knows.    But the documentable fact is that sire conception rate (SCR=  bull semen fertility) and daughter pregnancy rate (DPR= cow fertility) are not very highly correlated.     
Are such bull behaviors genetically linked?      Yes, because to some extent all points of deviation (measurable difference) among animals within a herd are definable as genetic differences.    But as these differences were not important to AI success, they have never been summarized and evaluated.   Thus they remain within the realm of observational knowledge—the sort of data scientists distrust on the basis of limited sampling sizes (most people are not making useful observations of their cattle, or at least fail to write them down for future collation, or fail to submit them to an “official” summary).

The beef breeding industry routinely tests bull behavior by summarizing the percentage of cows each bull “covers” in a specific time period when turned out for range service.    Generally, we know that beef breeds seem to have more fertility than dairy cattle.    Part of the real reason would be that more attention is placed on fertility as a desirable selection trait, and that a multiple of measures both male and female are collated to estimate genetic fertility ability.

Successful fertility implies a living calf.     The beef guy knows this, as his income is based on the size of his calf crop first, how it grows after birth is a secondary level of income stimulation.    Likewise it is true for the pig farmer (litter size, livability of the piglets, sow acceptance of piglets for nursing) and for the sheep farmer (live lambs, even when twinning, means more income than dead lambs).    But for some perverse reason, an earlier generation of dairy geneticists (active in the formative era of AI and the key promoters of composite index ranking) seemed to have overlooked the link from reproduction to production—choosing to focus purely on comparative lactation production.   This is where most of our issues with unsuccessful fertility in modern dairy cows originated.

Thus ease of calving in an indirect sense, as it correlates to both cow survival and calf survival, is also linked to cow fertility.     You now have several points from which to decide how “useful” your cows are in a genetic sense of potential transmitting ability.    I would not save a bull from any cow who has a history of difficulty in calving or of presenting stillborn calves.    In all of animal agriculture, income derives from reproduction, as the precursor to measured production.      Keep that in your focus.

Successful fertility is positively linked to production profitability.     This is where the statistical data on which sires have been ranked leads us astray.     Think about your own dairy operation: is it actual pounds per cow per day that determines your milk check income, or is it predicted lactation pounds in 305 days?      You might think the two are essentially the same—but they are not.

I have a friend with purebred Jerseys whose selection focus has consistently sought two things: higher component %s (butterfat and protein) to drive his income, and annual calving intervals over multiple lactations (cow lifetime totals) to drive his profitability.    We will analyze his results:

He currently has a herd average just shy of 17,000 pounds of milk with 5.6%bf and 4.0%pr—thus 950 pounds fat and 680 pounds protein (on an ECM basis, this matches a 26,000# Holstein herd).   But the amazing thing is he averages nearly a 12 month calving interval on sixty milking cows at this level of nutrient energy conversion—a truly “elite” level of performance, as we will demonstrate.

He has a neighbor milking 120 Jerseys, with a 20,000 pound DHIA herd average, whose annual milk shipments are nearly exactly twice what Phil ships.     Why, if Phil’s cows are producing at the same level as a 20,000-pound herd, is he only getting lactation credit for a 17,000-pound herd?

The difference is—his neighbor accepts a 14 month calving interval as a consequence of a preference for “high peak day” genetics over “persistency” genetics.     He not only uses AI sires, he uses those of the “high PTA milk” persuasion—those who daughters are predicted at higher lactation pounds in 305 measured days, but whose reproduction is delayed (thus total lactation is 365 days).

17,000 pounds of milk in 305 days equals  55.74  pounds of milk actual per day.
20,000 pounds of milk in 365 days equals  54.79  pounds of milk actual per day.

For three decades we have been taught the rolling herd average was your measure of success in dairy. 
RHA is calculated as average test day pounds times a 365 day year.    But we kept on calculating bull evaluations on a 305 day lactation value – and in Mature Equivalent, not actual pounds.

This created a selection preference for a higher peak lactation curve (in which that peak could extend as a consequence of slow or defective fertility) over a flatter, more persistent lactation curve (which is ultimately the most profitable, ie, persistency of production meant fewer below-cost stale days at the end of the lactation, thus a controlled-length dry period).    

Earlier feeding approaches also expressed a preference for delayed fertility.    In the 1970s and into the 1980s (a very important transition period in genetic evaluation concepts) the standard nutritionist’s   approach to feeding cows was to “challenge feed” fresh cows—an added pound of grain for each three pounds of milk, and see how high she will “peak”, on the assumption that a higher peak will then carry her steadily declining daily yield further into the end of the lactation, when actual production did not always cover total feed costs.    We were taught that a “good” cow makes half her total lactation in the first 130 days, and that pregnancy would make her yields drop, eventually into a “loss” column, at which point you dry them up (no matter how many days until the next calving).

This was a strategy designed to sell more grain (and grain was cheap and plentiful in those days, so why not?   The grain ration could make up for a deficient forage base).     The sort of cow that makes milk out of grain, of course, had to be sorted from the cow that gains weight from added grain.   Thus in genetic selection, we redesigned type standards to prefer the more “angular” cow over the easier conditioning cow—and along with that, accepted a longer period of “negative energy deficit” in the early months of lactation, thus delaying the reproductive response.    These changes in cow structure and performance began slowly (usually masked over by a steep decline in bf% tests, not considered important in that time period as “fluid” milk was preferred over “manufactured” milk products in a society obsessed by “low fat” —the loss in bf% a consequence of internal energy rationing by cows).

On the genetic side, while thinking in PD pounds, we were actually selecting genes that regulate the conversion of energy intake into four bodily uses:  production, reproduction and health maintenance.
The genetic anchor to fertility was lost when the high-indexing young heifer replaced the long-lifetime production cow as the “bull mother” of choice.    Long lifetimes were not possible without fertility – but a “hot” first lactation is more easily made in the absence of reproduction.    Thus, if reproduction is no longer a drag on energy intake, then we could select for higher levels of protein %, and still have an increasing volume yield plane.     As long as we introduced OvSynch, we could continue to get at least some cows rebred, and stay focused on pushing the envelope for individual cow yield volume.

The purebred sector focused on producing AI sires uniformly adopted “induced” fertility—ie, super ovulation and embryo transfer.    The natural fertility of these “hot” young first lactation cows was never tested, because “induced” fertility could produce more than a lifetime of calves within two years of embryo marketability.     (No one ever considered this may not be the fertility preference of typical dairymen—as usual with newer technologies, we assumed they rendered traditional ways “obsolete”.)

For too long, the genetic community patted itself on the back for increasing the “base change” for milk yield in every breed (every five years, as adjusted by USDA) – until it was clear that dairymen were not always happy with the higher costs of reproduction, slower success of reproduction, producing a faster herd turnover, and in many cases a shortage of replacements.    Some tried crossbreeding as the “solution” to restoring “vigor”—others just quit AI and reverted to natural service.    Neither of these have to date altered the overall cost of production, thus milk production profitability remains marginal.

Genes truly lost can never be replaced.     One of the consequences of the “index” era has been a rapid destruction of bloodlines, followed by a decline in sireline variety.     All AI sires today are related to each other on a passive level, but the “linebreeding” of any sire line to develop a more homozygous pattern in trait transmission is avoided due to phobias over “inbreeding”.    Thus it is more difficult to create heterozygous variation within a purebred population, otherwise known as “hybrid vigor”—and it is more difficult to sustain “hybrid vigor” within a crossbreeding scheme, due to the lack of patterns of homozygosity unrelated to other breeds (able to produce heterozygous variation) when crossed.

Basically, “genes” are either present or absent in the DNA.    Genes do not “dilute”.     If the cow lines most superior for fertility or health maintenance have been culled from the population (on the basis of being “noncompetitive” under prior single-trait index rankings, as bull mothers) (on the basis of plain old “old age” culling them form the breeding herds) – their genes are lost.     Thus the blithely stated assumptions that “all you need are plus DPR and plus PL sires to restore prior levels of fertility” both overstates the genetic ability of current AI sire lines and understates the time and culling rates needed to recapture prior levels of performance in these traits.

But the lesson of my friend Phil’s Jersey herd—in which homebred sires comprise half of the ongoing sire selection and their selection is based upon rigorous adherence to desired trait levels—proves that it can be done…  IF you stay focused.