Saturday, March 28, 2015

Discovering lethal recessive genes by Genomic testing

This is from the 2011 September Diary Route letter

In a technology version of the Ellery Queen detective story, AIPL scientists took the Genomic data set (covering Holsteins, Jerseys and Brown Swiss) and went looking for gene pairings that never show up in a living animal.    The assumption is that such a “haplotyte” (Genomic marker) must always be lethal in a homozygous pairing—either conception fails or embryonic death occurs.   Five were found:

Gene ID    Source ancestor        Year born     Frequency      Effect on

                                                                        Within breed     Conception       
Pawnee Farm Arlinda Chief
Willowholme Mark Anthony
Glendell Arlinda Chief,
Gray View Skyliner

Observer Chocolate Soldier
West Lawn Stretch Improver

Of interest is Willowholme Mark Anthony who is the lone Canadian and the newest line to be identified.  The majority of HH2 descendants come through a single daughter, Elysa Anthony Lea, who was dam of Comestar Laurie Sheik and thus progenitor to every “Comestar” sire used in Canadian or European AI.

Also of interest is Glendell Arlinda Chief, avoiding the HH1 carried by his sire Pawnee Farm Arlinda Chief but picking up from the “Burke” breeding on his dam’s side the HH3 shared by a premier Burke line sire of previous generations, Gray View Skyliner.

The difference between these haplotytes and earlier lethal gene recessives

Many lethal recessives are expressed by a visually defective or stillborn calf.    A recent exception was DUMPS in Holsteins, which produced early term abortions (similar to the above Haplotytes).    Here is a list of lethal recessives for which AI sires are tested and noted when carriers:
Holstein     Brachyspina (BY), Cervical Vertebral Malformation (CV), Bovine Leucocyte Adhesion Deficiency (BL), Mulefoot (MF), Pinktooth (PT), Bulldog, Hairless, Prolonged Gestation.
Jersey         Rectal Vaginal Constriction (RVC), Limber Leg (LL).
Brown Swiss  “Weaver” (W), Spinal Muscular Atrophy (SMA).

But there are other recessive effects, for example in Ayrshire (thus also Swedish Red) you have the “fishy milk” gene—a recessive that gives the milk an oily consistency and an off flavor.   

Red hair color in Holsteins, White spots in Jerseys—these are “benign” recessive genes.    Horns are in fact a recessive that everyone experiences (the Polled gene is the single-allele “dominant” vs. horns).

Can we truly avoid all lethal recessives?

Yes, we can—if we want to do so.     In earlier eras, we did it by never sampling “carrier” sons of the higher ranking carrier parents.     Thus when “Wayne” had Mulefoot, only his MF “free” descendants (like the dam of ToMar Blackstar) were considered for AI.      Likewise if a sire line had been widely dispersed, as was true with “Bell” (and thus BLAD), most dairymen just decided they had enough of that line, and the market for sons/grandsons dried up.     

However, if you are the Jersey breed and have 23.4% (nearly a quarter) of your genes tied up in that single “Chocolate Soldier” sire line (which means Top Brass— Brook—Montana—Jace) (which means Soldier Boy—Sooner—Berretta and Hallmark—Paramount) (which means the dams behind Duncan—Lester—Lemvig and QS Royal—Alf and Judds Admiral) the temptation will be great to just ignore this and drive on, even if it means putting the breed’s high fertility reputation somewhat in jeopardy.

Fertility is the basis of all Productivity

The beginnings of the AI industry were not a competition over who had the best genetics—it was a test of whether the AI conception rate would be superior to natural service fertility.     Most dairymen in that era had multiple animal species, and understood that “reproduction” came first before any “production” that followed it—no calf, no milk thus no milk check.     Our industry has played with substitutes for a regular reproductive rate, like rBST, and covers up lower reproductive rates with OvSynch and sexed semen, but the increased demand for cows with “longevity” and ‘strength” are an indication that more dairymen still recognize sound fertility as a primary selection criteria both in genetics and herdsmanship.

Single trait genetic selection began to chip away at fertility quality

ABS (in its pre-Grace days) advertised “every sire proved great” and from its base of the largest network of inseminators nationwide, began promoting “genetics” as the basis for AI utility.    They believed, and were supported by most extension dairymen, that “milk” was the first (if not the only) trait worth buying and belittled the “type” and “cow family” emphasis of organizations like Curtiss and Carnation.

Unknown to anyone however, was the internal insemination data reports, indicating a steady 1% decline in conception rate each year.    ABS sires were selected on “milk” first, and even though their veterinary staff routinely culled sires at the bottom of their ERCR reports, the overall average kept declining. Why?
No one knew, because USDA only summarized 305 day ME lactations, with no adjustments for calving interval, and Breed Associations only summarized type scores.    The data was there to link fertility to genetic selection, but no one bothered to look at it until it started to impact on AI semen sales.

Composite indexes to “rank” sires remain a “single trait selection” method

The purebred sector fought the scientific sector for decades in promoting a multiple-trait approach to the breeding of superior cattle, with more of an emphasis on lifetime performance.    To draw the purebred sector under the technocrats’ wings, the concept of multi trait indexing (weighting production and type traits by a formula into a single TPI or $NM value) was borrowed from the terminal cross poultry and swine species and sold to us as applicable to dairy sire and cow selection.
At the beginnings of this effort, lots of data was collated to “prove” that the higher indexing sires would outperform average indexing sires by a ton of milk per lactation.    Over time, once the indexing concept had taken over, the need for comparisons died away… but on the last genetic base change, it was noted that “proven” sires now only had a $125 Lifetime “Net Merit” advantage over jumper sires.

Why all indexes fail over time

Today we have Genomic testing as the latest fad in “indexing”—an attempt to save a generation of selection by skipping the sire sampling process and calculate sire rank from DNA haplotytes.    This method has been tried twice in New Zealand (and has failed twice to identify the “top” sires even as it succeeds as here in screening out the least likely prospects).     Expectations remain unreasonably high.

The obvious inference not being made is this:  genes can be identified as causal to individual traits, as that is a biological function of gene transmission; however there is no “genetic” link to any economic factors external to the biology of the cow on which all “ranking” indexes are based.

Put simply, we can rank animal performance in a current generation by any “index” reflecting current economic conditions; but we cannot predict future economic viability from any prior generation’s rank given the only genetic basis for improvement is in the synergy of biological traits in selection.

The single trait selection nature of indexing promotes a suppression of heterosis vigor

Here is a simple factoid:   Only four of the current “top twenty” progeny tested AI sires were part of the “top twenty” Genomic tested sires in the first year of G sire release to AI service.    Of the realized “top twenty” [Holstein] sires, the lowest initial rank under G estimation was 844 (out of 1015 G sires).

This should surprise no one.    The top five sires for PD Milk at AI levels of Rel% in the 1966 USDA sire summary are virtually unknown today—none of them produced a sire line that lasted more than three generations.    Today’s exceptional sires become the definition of “average” in three generations and in the past we would be seeking a new sire line by then.  

Because of this, we must recognize that “heterosis vigor” requires a periodic change in genes selected to produce the level of heterozygotic response in correlated groups of genes that impact on realizable milk type and health trait performance, with fertility the main prerequisite within health selection.

The formula for Productive Life estimation is a useful example

Buried within all the traits used in estimating PL values on sires too young to have “matured” daughters is an assumption that smaller cows last longer than big cows.   This is exactly the sort of trait weighting that becomes nonproductive over multiple generations, as lost size leads to lost productive capacity.

The underlying statistics indicate the shortest herdlife is experienced on the smaller “frail” cows.   The bias against “large” cows is more based in the general prejudice against “show cows” who tend to be in the highest score ranges for stature, exceeding the dimensions of typical freestall housing.     But those cows who reach maturity and excel in lifetime productivity will be larger than average in weight (size) and average to slightly above in stature (upstandingness).      Lots of data supports this.

A good example of how assumptions can trump reality is the famous Regancrest Elton Durham CV.
His progeny data set has been as high as +4.0 for PL on matured daughters, but his tendency to sire a “large” cow regressed his PTA- PL values to +2.0 before Genomics, and he is now –0.2 PTA- PL as a result of being tested for Genomics (and possessing all the haplotytes for “size” than are currently under official discrimination).    This negative assumption is weighted into descendants like “Barbie”.

“Narrow” young cows are the surest route to “frail” cows that never get old enough.   Keep that in mind.

Inbreeding is not pedigree based—it is index based

Think the Kiwi BW is better than the German RZG or the US $Net Merit is better than the Canadian LPI?    Think again.    None of them produce more than three generations of improvement without the support of a 40% cull rate to sustain their data.

Three generations exchanges 87.5% of the initial gene possession.    At that point it is worth while to consider how many limiting homozygous gene pairings were created.

Rotating sire generational focus avoids the true inbreeding effect, allowing in new sires that can produce a “hybrid vigor” effect—a shift from milk yield to component %s, a shift from angularity to substance in physiques, a shift in favor of healthier fertility, as reflected in sires you choose to use.

Monday, March 23, 2015

How would you design a practical breeding program?

From the July 2011 Dairy Newsletter

Most AI systems and Breed Associations sell linear-based or index-based “mating programs”.    These are designed to match a couple sire choices to each cow.    They make the following assumptions:

(1)  All genetic gain comes from sires selected.     (Your cows are assumed to be “zero” for all traits.)
(2)   The focus in all matings is to raise udder, feet and legs, stature, and angularity scores.
(3)   Avoiding performance depression depends only on avoiding pedigree inbreeding.

The basic design of such mating programs goes back to the 1960s.    Dr Walton of ABS pioneered the “Genetic Mating Service” [calculating an index mating composite] while Ron Long of Select perfected the “Linear Mating Service” [basing mating on two worst linear faults].      Little has changed since.

Weaknesses of “genetic” [index] computerized mating schemes

In fact, within the computer, the calculated “mating formula” would always breed every cow to the bull with the highest “index” (traits considered according to the index weighting).     Thus in such programs you are always asked to “rank” your cows (usually their DHI milk deviations) and to provide their sire.
The computer will then assign the “high” bull to your “high” cows, to the limit allowed one bull; then assign the “second high” bull to your “next high” cows, to the limit allowed one bull…   Only kicking out the high bull to your high cow if they share close pedigree relationship.    

You expected the mating program to provide trait correction – but all it does is calculate matings that will generate the highest “pedigree index”.     All the trait data the evaluator collected just goes into the AI stud’s data bank to anticipate which sires (their own and competing) might go up or down on future type proofs, so they can anticipate changes in market demand for individual bulls.

Weaknesses of “linear based” [trait corrective] mating schemes

The advantage here is that the evaluators go beyond collecting trait data for a computer to make sire choices; they usually make the choices based on their visual of the cow and memory of sire patterns.
Their computer is only used to print out results they put in (and store collected data for market uses).

The problem is with the limited number of traits (insufficient to fully describe the cow’s physique as it relates to all physical functions) and the necessity to focus on a small number of traits (two or three) to expect any heritability of the results (the more traits included, the lower the composite heritability).

Thus—typically in linear mating, you gain in stature, angularity, rear udder height, and get straighter legs with steeper foot angles—but you lose width, capacity, and strength over time (due to a constant  trait selection bias in favor of angularity).      You trade off old faults for new faults each generation.

Ultimately the weakness in both computer and hand mate systems is that the level of heritability % in individual traits, while high enough to lead us to whom the better bulls appear to be, is insufficient to insure trait correction.   

AI studs and Breed associations continue to offer “mating programs” because many dairymen want them and they have aided AI studs in gaining 100% of individual dairy’s semen purchases.    However, there has never been a University genetic research that ever proved these systems work—which is why typical geneticists advise to just random breed to high rank sires and avoid inbreeding when possible.   

Define your goals first, before selecting programs to reach them

I asked an experienced, successful dairyman what he would want as goals of a “breeding program”.
His responses were:
** Match sires to cows so as to avoid replicating faults possessed by the cows in their offspring.
** Cover the total cow physique in the mating, so that new faults (not possessed by the cows) are avoided in the offspring produced.
** Produce a physique capable of harvesting all of the genetic value gain implied in sire selections.
** Produce a physique that remains healthy, reproductive and feed efficient within the capacity gain generated by genetic selection for higher production.
** Produce cows that can sustain competitive production over long enough lifetimes that the herd is able to multiply, allowing for a second income stream from surplus cow sales, and create an opportunity for   culling as genetic improvement (rather than a constant turnover of cows from involuntary losses).

Adding the “qualitative” to the “quantitative” makes the difference

Six decades of “aAa” research reinforces the observation that “causality” in trait faults is based in the “qualitative” (analysis of the physique as a whole) rather than in the “quantitative” (measurement of traits as discretely separate from the physique).

Thus to cover the development of physiques capable of thriving under increasing production, the focus of mating should be on the physical expression—not the genetic ranking.

Selection of optimal mates is the function of genetic evaluation.    But ranking all sires on a common list without regard to qualitative differences in physique, will always lead mating in “likes to likes” direction and this “single trait selection” has been known from research to be the true cause of dairy performance depression (loss of heterosis “vigor”) (misnaming linebreeding as “inbreeding effects”).

Putting it together in a practical way

(1)    Analyse your breeding cows on the “aAa” method.
(2)    Sort the cow results according to their heterozygotic physical mating need.
(3)    Sort among ranked sires to identify the optimal choices for each group of cows.   (This is a simple process, as all AI sires are “coded” to indicate their physical mating benefit.)
(4)    Stock semen as needed in each group to breed all cows.

Knowing your needs in sires in advance can allow you to pursue acquiring semen at prices advantageous to your breeding budget.    Thus the temptation to buy “specials” (and find afterwards the sires chosen do not provide improved offspring in your herd, keeping culling costs high) can be avoided.

Will “inbreeding” be avoided?    The “aAa” groupings will prevent you from mating “likes to likes”.   The phenotype differences (between cow and sire) represent broad genotype differences, thus each mating is “heterozygous” at the level where it really counts—the genotype produced in conception.

Different phenotypes also usually result from variation in pedigrees.   So the inbreeding coefficients in “aAa” analyzed herds generally go down over time, even if some sire relationships appear.           

Wednesday, March 18, 2015

North Florida Holsteins and Green Meadow Farms – kindred spirits

From the July 2011 Dairy Route Newsletter

54HO 480  No Fla Legend   (aAa 156324)  and  54HO 509 No Fla Perpetual  (aAa 342156)  are two of the sires we offer through International Protein Sires bred in the “North Florida” dairy of Don Bennick.
Don worked closely with the late Pete Blodgett (formerly of Landmark Genetics, then DMS) in devising large herd selection programs to improve cow fertility, health and fitness traits while gaining production.   

Pete worked in recent years with Green Meadow Farms in Elsie, MI to address these issues, and visitors to this 3600 cow herd are impressed by the higher level of uniformity compared to most large scale dairy herds.   The year of Pete’s passing they hosted a very successful 250 cow “production” sale that showed the multiple income stream possibilities from multi-trait sire selections and individual cow matings.

Pete encouraged use of some No-Fla young sires at GMF.    They recently calved three heifers sired by No Fla Perpetual that are catching the eye of visitors, raising our confidence in this newer sire.    He is a bull who sires “clean” thighs, bone and rib-- yet puts strong front ends, wide rumps, soft textured udders and deep feet fairly consistently on his daughters.     

Another successful experiment at Green Meadow (used on a few “Red” cows) appears to be  6H1124  Fitz Hill Tycoon Red   (aAa 456321)  who is our highest ranking “Red” sire for fertility/health/fitness  traits, and offers significant outcross to both B&W or R&W Holsteins.    

Sunday, March 15, 2015

The Ideal Mating Program Would

Match sires to cows so as to avoid replicating faults possessed by the cows in their offspring.

Follow a process that covers the total physique, such that new faults (not possessed by the cows) are not produced in their offspring.

Produce a physical cow fully capable of harvesting all of the genetic value involved in sire selections.

Produce cows more adaptable to any changes that may occur in her present or future environment.

Be focused equally on sustaining production over a full cow lifetime, rather than accelerating production at the expense of reproduction, health expenses, or total herdlife—thus producing a herd that is actually multiplying and thus allowing discretionary (genetic) rather than all involuntary culling.

Is there a program with such a goal, and does it have any proof it works?
Consider the “aAa” Breeding Guide -- added to your current emphasis on genetic selection.

Wednesday, March 11, 2015

What should we be learning from recent crossbreeding experiments?

From the May June 2011 Dairy Route Newsletter

Why does anyone crossbreed?       
     (1)   To gain added performance from “hybrid vigor” [heterosis].
What is “hybrid vigor”? 
(2)     The performance response we get from introducing some “warm”[outcross] genes into a “cold”[closed] gene population.
 Why do we wish to change the performance [related behavior] of our animals?     
(3)     Because current generations no longer respond as well as prior generations to trait selection as practiced within our breed.

Let’s stop right there.     “Crossbreeding” is tried when after several generations of gaining performance from standardized methods of selection [which today we call “index”] we no longer see any incremental financial gains—ie, either cow life gets too short, or milk yields no longer grow, or incremental costs are greater than incremental gains.

The problems that grow from believing “change” does not keep changing

The current fixation with “indexing” for commercial herd propogation is based on a “race memory”—the window in time that was the 1960s, when AI studs shifted from bloodline sire selection to progeny data sire selection.     While this was done in a “purebred” context, the net result was we began a mating process in which we “crossed” our herds—we bred “type” cows to “milk” bulls, we bred linebred cows to outcross bulls.   We saw large leaps in productivity from the cow to the heifer generation.   We gave the +1000 PDM figure 99% of the credit for this gain, and assumed this process would work forever.

The 1960s was when all the “single trait selection” ideas gained traction—ideas that later research have uniformly proven to be laden with weaknesses—yet here we are in 2011, and we remain more in love with “single trait selection” than ever, only instead of “PD Milk” we look at “Genomic Net Merit”.

What goes wrong with single trait selection

The problem with single-trait selection [any selection system in which you say, “no matter what, every sire I use must be plus x pounds of milk/fat/protein”] is that you tend to be going back to the same gene wells over multiple generations.    Over time, the underlying gene possession of your cows becomes the same as the gene possession of your mating sires.     For some limited desired genes, a “homozygous” [identical genes in each pairing] pattern is OK—as in gene pairings that stimulate milk yield.   But for too many genes, a “heterozygous” pairing [maintaining the basis for a “hybrid vigor” mating response] is more desirable—these being genes for traits that we need but are not naturally associated with “milk” genes in the mainstream of our breed.   

In other words, think of the typical experiences we have had for the “highest milk” bulls:
(1960) =  If he is +2000m he will be minus for udders and/or feet and legs.
(1970) =  If he is +2000m he will be minus three or four points on butterfat%.
(1980) =  If he is +2000m he will be calving ease and I will end up with small hard calving cows.
(1990) =  If he is +2000m he will be minus for Productive Life [sire short herdlife].
(2000) =  If he is +2000m he will be too high on expected future inbreeding.
(2010) =  If he is +2000m he will be minus for Daughter Pregnancy Rate [sire low natural fertility].

In each generation there would be an exception close to the top, but in our fixation with “number one” it was always possible to overlook him.    Then we would reap the negative effects of trusting only “rank”.

From generation to generation, the negative effects of focusing on one main performance trait tend to accumulate, and this accumulation reflects the trait weakness(es) of the ranking sire line dominant in that generation.     This accumulation is more dangerous if a certain physique is preferred, a further limiting of gene pools by qualitative as well as quantitative selection, leading to extreme frail physiques.

Thus, graziers (who felt they needed shorter, more mobile cows) and large confinement herd managers (who were looking for easier calving heifers, more fertile cows, physiques better adapted to the facility limitations, and more health in general) both pursued crossbreeding as solutions to different problems.

But in fact, if by crossbreeding the bull selected was defined merely by his breed, there is no guarantee of “heterosis” [many Jersey bulls are just smaller, brown Holstein gene accretions] [most Euro Red bulls are proven in single trait ranking “index” systems very similar to our own].   

Whether crossbreeding or outcrossing, the principles remain the same

In any multiple generation analysis, the conclusions remain the same – there is no sustainable shortcut for the full breeding process, IF your goal is to gain on both herd equity and herd net income.

The insurmountable weakness of crossbreeding as most have practiced it is that over time, milk yields will decline.     “Milk” genes get replaced with “Beef” genes; “Cow capacity” genes get replaced with “small” genes; Uniformity for adaptation to group feeding and handling is lost in random variation.    
Basically, because we are not taught that the complexity of gene selection is manageable, and that any short cut method (index selection) (crossbreeding) (linear mating) has declining effectiveness after only three cow generations, we overlook some simple alternatives.

What could have been done (but usually was not):

  We could limit our breed inclusions to one or two breeds, rotating back to our “base” performance breed every second or third generation.    This avoids the loss of productivity, but if we also focus our outcross selection on sires in breed #2 and/or #3 on changing the weaker traits of our base breed, there will be more of a true “heterosis” response than if we pick the crossbreeding sires “the same way” as we pick our performance breed sires.      You have to break the cycle of “likes to likes” matings.

We could stick with our “pure” breed, but open up to using the very sires we usually turned down, the “not enough milk” sires others found desirable—due to their possession of the very traits we had been giving up consistently in our pursuit of “single trait” [milk] selection.    Treat these as an “outcross”, ie, return to your “line” in the following generation.    This is how you find heterosis within any breed.   It is your only way to avoid “inbreeding” today within any breed.

We could go beyond the simply statistical (quantitative) level of bull “proofs” and include a process for managing the physical (qualitative) level of mating— as we do with the “aAa” breeding guide.   If you are unwilling to give up the index ranking selection (“likes to likes”) the qualitative mating process still will impact on exactly those areas of physical adaptation that lead so many to crossbreed initially.

The more successful crossbreeders I know have usually found that at a certain point, saving their own bulls representing the more successful crossed combinations, is more effective than to continue to add new breeds.     [Look at the Kiwicross sires in the latest LIC New Zealand sire directory for examples.]



Crossbreeding assumes we get hybrid vigor because different breeds means different genes.    In fact, under parallel selection systems, all breeds share many gene patterns in common.    The composite (Euro Red) breeds actually offer less heterosis.

Outcrossing within a breed assumes we get hybrid vigor because different bloodlines mean different genes.     In fact, within most breeds, even more gene patterns are in common than is true in crossbreeding, as a result of highly focused trait selection.

“Hybrid vigor” today is thus a result of knowing how to avoid “likes to likes” mating, whether within a breed or crossbreeding.    More heterosis is available when we add in the qualitative level of [physique-related] gene activity in our mating process, and give up arbitrary selection levels on a “primary” trait to acquire higher levels of performance in all our “secondary” traits—leading us to the “different” bulls.

Friday, March 6, 2015

Genomic news from New Zealand – OK for traits, useless for index ranking

From the May-June 2011 Dairy Route Newsletter

This press release came from NZAEL (New Zealand Animal Evaluations Ltd) in April:

“The NZAEL has decided to suspend genomic data from BW estimates  [Breeding Worth= their equivalent to $Net Merit]  until it is better able to provide comparability between estimates of merit of young sires” quoting Bill Montgomerie, head of NZAEL’s dairy evaluation team.     Sire proving of the first genomic bulls proved that their real BW was not what had been estimated by genomics.      Genomic bull data has now been removed from calculations of the national (NZ) breeding index.

The Kiwi’s had the first operating Genomic estimation system, and the Oceanic AI systems were using this data for young sire selection six years ahead of its release in Europe and North America.   However, on their first try, it was found that the average overestimation at “elite” levels was 25-30% depending on breed.    They were the ones who recommended to USDA to use a larger number of SNPs to gain on the accuracy—yet the above announcement suggests even that solution is not working for them.

The US and Canadian AI systems are deeply immersed in Genomic theory as the preferred way to select the next generations of young sires for AI.   Yet experiences from NZ, and to a lesser extent Europe, are still suggesting dairymen need to be cautious in their selection of young sires on G index rank alone.

Progeny proven sires at high levels of Rel%-- and basing selection on more than just a ranking index—remains the “gold standard” for herd improvement.     Population genetics’ methods remain more adept at predicting the behavior of populations than of individual animals.

Wednesday, March 4, 2015

Dairying under the influence

From the March-April 2011 Dairy Route Newsletter

“Dairying under the influence”   of   $ 6.50 corn  (and $13.00 soybeans, etc…)

Let us face facts.    It will take a higher milk price than we currently receive to make milk profitably at the volume of corn for which we currently balance rations.     Nor was the 1990s answer “get bigger or get out of the way” proof against the current and future reality of higher corn prices, thus more farmers  competing for available farmland.    (Nor is it safe to expect milk prices will go so high as to allow us to avoid making any structural changes—all those emptied “expansion barns” might just fill back up with surplus cows and put us right back where we were in 2009.)

Under the “old math”, most feed conversion experts said you could put $2.50 (then $3.00) corn through a dairy cow and at $20.00 per hundredweight, be getting $4.50 for your corn.    So we all got convinced to focus on corn as our key milk making crop—even though the cow’s basic nature as a ruminant always implied she was better off (and more efficient) eating cellulosic forages.    DHIA helped to reinforce this by giving all the trophies to those who fed the most corn (ie, produced the most milk volume) rather than those who produced more valuable (more nutrient dense forage-derived) milk or more per-cow profit.

But feeding $6.50 corn tomorrow to produce $4.50 worth of milk will never make sense.    Thus today’s strategy must be getting more digestible fiber energy from higher quality forages, thus needing less corn to “balance” rations to cows’ total nutrient requirements.

There always was an alternative way

Europe has always been a major player in dairy, exporting cheese worldwide, and Oceana grew quickly on an emphasis as a low cost producer of milk proteins and butterfat products.    Neither of these regions of the world became dependent on corn—they stuck with the breeding and propogation of higher energy grass forages.    95% of the cows in New Zealand milk, breed back, and stay healthy on “no corn” grass based rations.    In seeking higher performing genetics from North America, they often found Canadian genetics of the 1970s-80s (slightly less milk but higher component %s, fed more hay and less corn) more applicable to their needs and more adaptable to their environments.     The lessons in this were lost on us in the USA; we had cheap fuel and grew cheap corn and didn’t care what went on anywhere else, always able to coax the US Congress into a bigger subsidy as the costs of this strategy began to increase.

It is time to create some alternatives of our own

Remember barley?    Bushel for bushel it more than replaces corn (same energy, 50% more protein and useful minerals).    It is simple to grow, handles cold weather better than corn, and you get some added straw.    Some spring barley varieties can hit 100 bushel/acre at one third the input cost of growing corn.
It can be overseeded for a following forage crop of summer annuals or grass hays in the same season.
Remember grass?         ( “grass is not a weed”  except when in a row crop )

Grass is nature’s answer to covering any erodable earth surface.    Ruminants (like cows, sheep, goats, alpacas, llamas, water buffalos, bison)  evolved to eat that grass as their total diet.   Grandpa’s hay had grass in it and his cows liked it.    Today we often observe that when a sick cow won’t eat anything else, she will still eat nice soft grass hay.    But after WWII, Dad was told to kill the grass, pure alfalfa was a better (higher volume yield) forage that could combine with corn to make a new way to get more milk.

It was simple—starch energy (but not much protein) from corn, high ammonia protein (but not much energy) from alfalfa.    Scratch factor from some baled hay (the less the better, given how fast wilting alfalfa loses nutrients).   If short protein, add soybean meal; if short energy, add molasses.      Get 18-25 tons of corn silage and 4-6 tons of alfalfa hay per acre, roughly equal in value given protein always cost three-four times what energy cost per volume.       Spread manure on the corn ground and it uses it up.

But today’s facts no longer support this as the “ideal” ration.    We have too much blood urea nitrogen on pure alfalfa diets, we lose too much butterfat% and protein% on high corn diets.    Metabolic disease rates are too high; lameness is too frequent; reproductive rates are too low.    Cows wear out too fast.

Modern grass genetics produce a forage superior to pure alfalfa

Think about it.    Your nutritionist is always trying to create a ration with 16.5% protein at 78 or more megacals of energy to stimulate high milk production.    Good grass harvested at its optimum stage is nearly a perfect balance—16% to 18% protein and 76 to 80 megacals energy.    Your only trick is to get her to eat enough to hit your production target: it is already by nature a “balanced” ruminant feed.

Compare that to the typical GMO corn silage—7% to 8% protein and 78 to 83 megacals energy, maybe 20% of its volume actually undigestible lignins.     Compare that to the typical top alfalfa—18% to 24% protein and 72 to 76 megacals energy.        Neither is a “complete” feed, each adds an element of waste (excess non protein nitrogen in the alfalfa; too much nondigestible stalk and cob fiber in the silage).

Various tests from Wisconsin and elsewhere show that the “milk per acre” possible from an acre of the Barenbrug grasses— perennial Dutch ryegrass, perennial hybrid tall fescue, annual Italian ryegrass – equal or exceed the “milk per acre” from even the best GMO corn silages—at much lower per acre cost.
It is this lower cost per acre at the same milk value per acre that will make you more money—not being on the unending treadmill to get higher yields from crops lacking the same nutrient density and level of rumen digestibility.       

Modern grass genetics are compatible with alfalfa for maximum yields per acre

The new sales pitch for “Round Up Ready alfalfa” is just the opposite of the strategy a dairy farmer needs to follow.    Interseed high energy grass into existing alfalfa—you will gain both yield and feed value.     This has been repeatedly proven in the latest Wisconsin forage trials.     More feed and a lower per acre cost of seed over the field establishment lifetime—again, a cost benefit as well as higher yields.

Modern grass genetics helps lower your purchased nitrogen costs.     Italian ryegrass as plowdown is worth 250 units of nitrogen.     Grass will increase its yield and nutrient density just from 3-4 pounds of clover seed added per acre in the seeding.    Grass root structures will trap more rainfall than row crops.
Converting to grass based rations (corn silage, mixed hay, grasslage) can significantly lower grain cost.
 Forage based animal genetic selection

Today’s sire rankings are based more on “corn consumption” than “feed efficiency”.

This bold statement by a Holstein breeder I know who is very successful as a grazing dairyman, is a sentence worth pondering.

He selects his service sires on type—but specifically with an eye toward the wider, deeper, more open ribbed cow.     He likes big cows, because he expects them to get 80% of their dry matter intake from forages, only 20% from grains.      He likes vigorous cows, because he sends them outside in the green grass season to harvest their own feed (and spread their own manure).    

Example sires who fit this alternative paradigm

76HO 590  Wabash Way Thunder ET        (aAa 5 3 4 1 6 2)      Genomic young sire    (list $16)  $12

What is the chief complaint of the modern Holstein?   No width, no “guts”, no herdlife.    Her physique was designed to suck finely ground grain through a straw.    She is incapable of handling more than six pounds of hay in a day—she can’t chew it, her muzzle is so narrow; she can’t digest it, her body is both shallow and slabby ribbed, too inflexible for the rumen to “roll” when full of fiber.

“Thunder” is that rare bull—a widely sprung, open ribbed, deep physique from a high performance sire and cow line.    His dam is Gaige Outside Tootsie an “EX 94” Outside that is as wide as a bale of hay and at 4 yrs in 357 days made 34070m 4.9% 1674bf 3.3% 1127pr actual in Ohio.    Next dam is Gaige Highlite Tamara an “EX97 4E” Highlite who at 4 yrs in 365d had 33740m 3.9% 1229bf  3.0% 1007pr and now at 15 years of age has exceeded 300,000 pounds actual lifetime to date while also shown to All American status in the 125,000+ lifetime cow class.      

Characteristics of sires who will fit high forage ration programs

They are more likely to be plus than minus for butterfat % and protein %.     You want cattle exhibiting healthy rumen function.    Low bf% indicates a lack of cud chewing to buffer the rumen and capture the added energy from digestible fiber, low pr% indicates negative energy deficit inhibiting body condition.

They are more likely to be above average for fertility (DPR = daughter pregnancy rate) suggesting more of a “flat” than “peaked” lactation curve.     Strong natural fertility suggests more balanced genes when it is necessary for a cow to ‘ration” her feed energy intake vs. competing uses for milk, health and repro.

They are more likely to be below average (below 3.00) for somatic cell score (SCC) suggesting a more effective immune system.     SCC is not just about mastitis—it is about any body infection, which means heel warts as well.    Lower SCCs are a general indication of a healthy animal that will continue to milk well at mature size and ages.     (Higher SCC sires generally sire shorter herdlife cows.   The exceptions will be sires with extraordinarily high levels of butterfat% and mineral excretion.)

They will have “aAa” mating physiques that can add some dimension of capacity relative to size and scale.      Thus when mated to the typical tall/narrow/fine-boned commercial short life cow, their heifers will exhibit more in either chest depth/bone capacity OR chest width/rib capacity.
(Look at 54HO489 No Fla Legend  (aAa 156324)   and   76HO466 Ridgedale Escalate  (aAa 345126)

The kind of cows you will like are the kind of cows who add profit

Like the looks of this cow?   

We can make you this kind.
We know the bloodlines.
We know what sires do.
We understand matings.

She is the profitable kind.
Able to milk on forages.
Requiring less grain to milk.
Still able to breed on time.
Strong enough to live awhile.
Mostly takes care of herself.