National Hog Farmer is part of the Informa Markets Division of Informa PLC

This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them. Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 8860726.


Articles from 2008 In April

Industry Entrepreneur Passes Away at 56

Dennis W. Harms, 56, co-founder of Premium Standard Farms (PSF), died while on a business trip last week.

Harms, a native of Stanford, IL, had 30 years of experience in agricultural management positions.

He worked for 15 years as a grain salesman for Cargill and Central Soya. He founded PSF, a vertically integrated pork production company, in 1988 and served as company CEO for 10 years, until Continental Grain purchased it in 1998.

In 2002, Harms became president of PIC USA and PIC Canada.

In 2007, he co-founded Spectrum Agribusiness, a food and agriculture consulting service.

Harms is survived by his wife, Kathi, a daughter and a son.

Higher Prices Offer Little Relief

It is difficult to believe that spot market carcass prices of $67/cwt. and futures contract prices in the $70s (and $80s for the deferred contracts) can leave the pork industry in a serious financial situation. But that’s the pickle in which we find ourselves this spring. Decent hog prices have not, and apparently will not, keep up with higher corn and soybean meal prices and producer losses are, to say the least, serious.

In a meeting on Wednesday, leaders of the National Pork Producers Council requested that Secretary of Agriculture Ed Schafer take several actions that will ease the economic hardships facing U.S. pork producers. Their requests included:

  • A two-phase pork purchase program, the first entailing $50 million for pork produced from cull breeding stock. That would primarily involve ground pork and pork sausage from cull sows. This is not a sow buyout proposal similar to the program being initiated in Canada. It is simply a recognition that the primary impediment to a more rapid reduction of the U.S. sow herd is product movement, not slaughter capacity. NPPC says that the expenditure will remove just over 160,000 sows from the breeding herd.

  • Authorize another $50 million to purchase pork products through the remainder of the year. The fear is that high slaughter rates in the fourth quarter (analysts predict just short of 31 million head for commercial slaughter) will burden the market severely. Timing is essential in such cases, and USDA should be ready to act, not be ready to get ready to act (or worse – not act at all), when the time comes.

  • Be flexible in interpreting and implementing USDA emergency programs and loan guarantees to help producers purchase feed. NPPC (and many others) fear the situation where credit issues keep a producer from buying feed.

  • Support and defend U.S. pork exports.

  • Fully consider releasing Conservation Reserve Program acres that are not environmentally sensitive, without penalty, for the 2009 crop year.

  • Fully implement the interdepartmental livestock task force.
To my knowledge, there has been no response to the letter, but the requests are certainly reasonable and they entail actions that are appropriate and doable.

Cold Storage Highest – Ever!
Monday’s Cold Storage report was quite a shock for most industry observers. Frozen meat and poultry supplies were 23% higher than last year and the largest ever recorded. Frozen pork stocks led the way at +33% for the year. Over 657 million pounds of pork were in freezers on March 31. The largest increase was in pork belly inventories, which were nearly 99 million pounds or 79% higher than last year and 25% higher than last month. Every category except variety meats showed a year-on-year increase.

The question is whether this increase in freezer inventories is product backing up due to large slaughter and production levels or product being staged for export. At present, the markets would suggest the latter.

If this were a product backup, one would expect cutout values and hog values to be falling, especially when slaughter totals are record large for the weeks in question and are much larger than the March Hogs and Pigs Report would suggest. But that is not the case. Cutout values have gained $10/cwt. (to just over $66/cwt. last week) and negotiated base hog prices have increased nearly $9/cwt. (to $61.44/cwt) in the past two weeks – and have kept going up this week. I heard of a live weight bid over $55 (that’s $73/cwt. carcass) this morning.

Another piece of evidence supporting the “staging” argument is that cold storage as a percent of production is not out of line. Figure 2 shows historical data for both actual cold storage and the percentage of monthly production in cold storage. Note that the spike in actual inventories has not driven the percentage in cold storage beyond the historical range. In addition, the peak in cold storage percentage nearly always occurs in February, March or April, so the timing of this increase is very logical as well.

The biggest storm cloud looming over this situation is the very real shortage of shipping containers for export. That story has become hotter this past week with several popular press articles appearing. It is a complex situation that is driven by the weak U.S. dollar, robust exports, falling imports (due to the weak dollar and a weakening U.S. economy), better-paying alternatives for shipping countries, high fuel costs and many other factors. The impact on U.S. pork exports is anything but clear right now, but it is certainly cause for some concern given that February saw over 20% of total U.S. production exported.

Canadian Pig Crop Report
The final piece of information relevant to the cause this week is the Canadian Hog Statistics Report. Some highlights:
  • Canada’s breeding herd is 4.6% smaller than one year ago and the January breeding herd was revised downward from -1.9% to -3.3%. That fits better with anecdotal evidence back in January. The Q1 Canadian-U.S. (March in U.S. and April in Canada) breeding herd is smaller than it was one year ago.

  • Total hog numbers declined by 11.7% with market hog inventories seeing the largest drop. This reflects large market hog shipments early in the year.
  • The number of pigs under 44 lb. (20kg) is 9.8% lower than last year, reflecting higher shipments of pigs coming south.

  • Lower – but not much lower -- farrowings and farrowing intentions. Q1 farrowings were 2.8% lower and Q2 intentions were only 1.6% lower. I expect the lower breeding herd to put more downward pressure on farrowings as the year progresses.

Click to view graphs.

Steve R. Meyer, Ph.D.
Paragon Economics, Inc.
e-mail: [email protected]

NPPC Asks USDA To Address Pork Industry Crisis

The National Pork Producers Council (NPPC) has asked the U.S. Department of Agriculture to help bail out the pork industry buffeted by rising feed costs and tightening credit markets.

NPPC officers and staff met Wednesday (April 23) with Agriculture Secretary Ed Schafer to urge him to take immediate action to address what is now being called a hog industry economic crisis which is expected to also affect the broader U.S. economy.

In the last seven months, the pork industry has lost more than $1.2 billion. Due almost entirely to a doubling of feed prices, producers now are losing $30-50 on each hog marketed. Lenders are estimating that some producers could lose half or more of the equity in their operations by the end of the year.

Economists suggest the industry will need to reduce production by at least 10% – or a reduction of 600,000 sows – to restore profitability. But that cutback could prove costly, resulting in less-efficient packing plants closing; less manure for crop fertilizer; and forcing a need for more commercial, foreign-produced fertilizer; a jump in retail pork prices due to a smaller supply; and lost pork industry jobs. Allied industries that gain from pork production, such as Main Street businesses, feedmills and trucking companies would also suffer. Agricultural credit problems would rise as some producers default on bank loans.

NPPC President Bryan Black, a pork producer from Canal Winchester, OH, requested that USDA purchase an additional 50.5 million pounds of pork for various federal food programs. This would effectively reduce the U.S. sow herd by 163,600 animals.

Black also requested USDA implement emergency programs and loan guarantees to help producers buy feed, consider allowing early release without penalty of non-environmentally sensitive Conservation Reserve Program acres back into crop production and support pork exports through USDA’s Market Access Program and Foreign Market Development Program.

Why Heavyweight Hogs, Now?

Big question of the day: Why are pork producers selling such heavy hogs when feed costs so much and profits are so awful? See Figure 1 for the evidence of continued high weights.

Answer: There are lots of reasons.

First, waiting to sell pigs will almost always get you a higher price at this time of year. National negotiated net prices have gained $7.50/cwt. carcass, since April 1, so the strategy seems to be working.

Second, producers generally consider feed to be about the only component of marginal cost, the amount added to total costs by the last pound of gain. Only recently have feed costs gotten so high and hog prices so low that marginal revenue (i.e. the price/lb.) has not exceeded marginal cost. So, the incentive to feed pigs longer has been strong. Even if pigs are shipped a bit earlier, someone still has to tend to the barn and the barn may have to be heated. In fact, that latter factor has worked against earlier marketing, especially during the cold winter we just had.

Third, the circovirus vaccines, which are largely responsible for the huge slaughter runs since last fall, are also responsible for pigs growing faster than most people believed possible. In a time-denominated business, faster growth rate means higher end weights, even if you are trying to get them moved.

Finally, there just isn’t room in our slaughter facilities to speed up the slaughter rates to pull marketings forward and pull weights down. Daily slaughter rates have been consistently above 430,000 head. To pull weights down 2 lb. or so, one of those days has to disappear. But about all we could possibly do is add 10,000 head on weekdays and 50,000 or so on Saturday. That’s 100,000 head per week, meaning that it would take four weeks to get that 2-lb. reduction.

Weights will come down. They always do as spring progresses. But I believe we will be hard-pressed to push weights below year-ago levels given large supplies and fast-growing pigs.

Will Anyone Take Weaned Pigs?
There have been some reports of plans to euthanize pigs in Canada due to high feed costs and the fear that mandatory country-of-origin labeling (COOL) will mean there will be no market for them next fall. I have also had reports that this idea is sensationalism. I really hope it is.

Pig prices have plummeted in recent weeks (see Figure 2), indicating plenty of supply and, given feed costs and expectations for cash hog prices this fall, not much demand.

Returning to my soap box now, I encourage feeders to look at the futures market for pricing opportunities. Figure 3 shows the forecasts for quarterly cash hog prices from me and three other market analysts. They are pretty dismal given projected cost levels. It also shows Lean Hogs futures prices as of Thursday. Even allowing for a $3-$4/cwt. basis, Q4 Lean Hogs futures imply that these weaned pigs can be priced at about $140/head.

Will that provide a profit? Probably, as long as there is, in fact, a cash market for the pigs this fall. Let’s hope we can get the COOL issues clearly and quickly established. No one will benefit from the alternative.

Click to view graphs.

Steve R. Meyer, Ph.D.
Paragon Economics, Inc.
e-mail: [email protected]

Pork Plant Workers Suffer From New Malady

U.S. researchers and scientists confirmed April 16 that 18 pork plant workers in Minnesota, at least five in Indiana and one in Nebraska have contracted a newly identified neurological condition while reportedly removing brains from slaughtered pigs.

Experts said the illness is a new disorder that produces a number of signs from inflammation of the spinal cord to mild weakness, fatigue, numbness and tingling in the arms and legs.

“As far as we are aware, it is a brand new disorder,” says Daniel Lachance, MD, of the Mayo Clinic in Rochester, who presented his findings at the American Academy of Neurology meeting in Chicago.

Lachance says all 18 Minnesota patients he has been closely following have evidence of nerve involvement, typically affecting the legs.

Research indicates this damage extends to the nerves at the root level near the spinal cord, and at the extremities of their motor nerves, where the nerves connect with muscle.

The first cases of the condition were reported in late November in some workers at Quality Pork Processors in Austin, MN. These workers were using compressed air to blow pork brains out of the skull cavity.

This process apparently produces some sort of inflammatory response, says Lachance.

No infectious agent has been found, and researchers don’t believe this condition can be passed from worker to worker.

The U.S. Centers for Disease Control have surveyed 25 of the largest pork processing in the United States, and have found only these three plants in three states where the process is used and the problem has occurred.

All three plants have suspended the process as a precaution.

Most patients have mild conditions, which are being treated with drugs. But none of the affected workers has completely recovered.

Top Health Produces Consistent Throughput

Top Health Produces Consistent Throughput

Throughput, defined in terms of pork production, is the number of pigs or pounds of pork “put through” any given system, farm or facility.

Efficiency of throughput is the ratio of useful output in relationship to the total inputs that are devoted to a given system.

Productivity is the marriage of the two — throughput and efficiency — as an indicator of how wealth and value are captured and added to the producer's bottom line. It is folly to focus on either throughput or efficiency at the exclusion of the other. They must be pursued together to create productivity.

The number of weaned pigs out the door is the measure of a farm's throughput, but this number does not indicate anything about the inputs required to produce these pigs. More importantly, the throughput number alone does not provide an indication of the productivity or profitability of the farm.

Maintaining top health is essential for maximizing throughput and optimizing productivity. When disease enters a population of pigs, it can affect productivity in many negative, decisive ways, such as increasing mortalities or reducing average daily gains.

But sometimes, in less obvious ways, disease can increase variability and cause a wide range of production challenges that increase the number of undervalued pigs, reduce overall efficiency and, thus, raise the cost of production.

For sow farms attempting to meet buyer specifications, such as batch size or weaning weight and average age, variability from week-to-week or within weekly batches of pigs can be devastating.

Variability is the range that a trait varies from the average of the rest of the group. For example, average daily gain or litter size traits are relatively easy traits to measure and compare.

Producers and veterinarians generally acknowledge that variability in production is bad. In most cases, wide variation in production measures will lower productivity and increase the number of “out of spec” pigs and groups.

Some variability is normal. Small ups and downs can be explained as normal biological inconsistencies.

Statistical Process Control charts are tools that help us understand variability and differentiate between normal biological variation and those fluctuations that require attention to a process that may be “out of control.”

The only time low variability would be undesirable is when the average of the trait is consistently poor.

Health Trumps Other Efficiency Robbers

Of the primary factors that affect throughput — efficiency and productivity — pig health is the trump card. Without top health:

  • Genetic potential will not be expressed or realized;

  • Optimum nutrition formulation will not produce top results;

  • The perfect environment will not allow top levels of production; and

  • The best management will not shine.

While all of these factors are interrelated, top herd health can help win the throughput game.

Top health has been defined many different ways. Most agree that health status can best be described by the absence of certain pathogens in the population.

For instance, we all know that some pathogens are much more important than others. The porcine reproductive and respiratory syndrome (PRRS) virus can be devastating to sow herd performance as well as in the growing phase of production. Other pathogens, such as porcine circovirus Type 2 (PCV2), are much worse in the grower phase than they are in the reproductive side of production.

But top health is not just the absence of the infamous pathogens. It is also the impact of overall disease pressure from common bugs such as Streptococcus suis, Echerichia coli and porcine parvovirus. These pathogens are called ubiquitous because they exist in nearly every herd.

When pigs are introduced to newly constructed buildings, or into facilities that have not housed pigs for some time, the disease pressure from even these ubiquitous bugs is less. This period of enhanced performance is often called the “honeymoon period.”

Pathogen challenge can also be managed through an effective, ongoing high hygiene program.

Health Variance is Broad

Across the industry, between systems, sites and groups, there remains wide variation in health status.

Herd health management strategies, such as depopulation/repopulation programs, segregated early weaning programs, parity segregation programs and all-in, all-out production have been an immense help in keeping production systems running efficiently.

In the last two decades, the swine industry has also benefitted from the use of many new tools for prevention and treatment of diseases that have allowed us to upgrade the health status of existing populations.

Disease elimination strategies have become commonplace. Some diseases that were once devastating, such as the pathogenic strains of Actinobacillus pleuropneumonia (APP), have been eliminated. Similar strategies have been used for the elimination of progressive atrophic rhinitis, Mycoplasmal pneumonia, swine dysentery, and mange and lice.

In addition, we've seen dramatic changes to genetics (leanness, market weights); nutrition and environmental management; weaning age; pig flows; group size and stocking density; biosecurity practices; refined diagnostic tests; targeted vaccines; and the judicious use of antibiotics.

Of course, the really big differences from two decades ago are in the diseases that we fight. Although some disease names have merely changed (such as APP), others are totally new, such as PRRS, PCVAD (Porcine Circovirus-Associated Disease) and PCV2.

Disease Drains Performance

Disease affects average daily gain, feed conversion, days to market and the number of culls or under-valued pigs. While none of these performance parameters are singly indicative of health, together they may indicate a health challenge exists — even when mortality is low.

Industry standards, targets and benchmarks provide a good place to begin a comparison, but they do not take into account differences or idiosyncrasies of a particular farm or system. Farm-specific records are necessary to begin to understand and analyze the effects of disease and the value of health to each farm or site.

Good farm records are necessary to begin to tease apart differences between groups of pigs, caretakers, sites, seasons, genetics and so on. Without good production records, guessing and supposition become the drivers of our decision-making, which make it impossible to know if a suspected problem is real and whether any intervention strategy will be beneficial.

Top Health Opportunities

If herd health is the trump card for winning the production game, there are some tools that will help stack the deck in your favor. Following is a list of ideas and concepts that are available to nearly every farm. Some are simple and easy to adopt, while others may require substantial investment. All have been used in some manner to increase throughput, reduce variation and improve overall productivity.

  • Implement benchmarking

    Benchmarking is simply a tool for comparison. (See SMS Production Index above.) Benchmarking your production against other farms or systems can help identify areas of opportunity. It can also be a tool to use within a system or farm. Comparing various production parameters will allow strengths and weaknesses to surface and help focus resources to the areas of greatest needs.

    Benchmarking is not limited to use with health-related measurements, but it can help identify health issues affecting production.

  • Establish a herd health plan

    Regardless of the current health status, the approach to addressing the impact a health problem is having on a population is essentially the same.

    First, you must identify the problem. Your veterinarian can help analyze production records, conduct postmortem examinations, collect and submit samples to a diagnostic laboratory or conduct serological surveys to get a snapshot of health status.

    Once a health baseline is established, your veterinarian can help establish a herd health plan to address disease and health-related issues. Vaccines, therapeutics and health management technologies are but a few of the tools available.

  • Identify and rapidly respond to health challenges

    Early detection and intervention is essential to reducing the impact a health challenge has on production, as well as reducing the suffering and loss of the pigs. Early detection may come in the form of clinical symptoms (coughing, sneezing, abortions, diarrhea) or a reduction in water or feed intake.

    When unusual or unexpected pig deaths occur, your veterinarian can compile a thorough history of the problem, conduct postmortem examinations and collect proper specimens for diagnostic laboratory analysis to determine the cause of death.

    As part of the herd health plan, your veterinarian can also design ongoing disease monitoring protocols that may include periodic serological monitoring and near real-time monitoring of important health parameters. Mortality rates and other production records can help identify problems in their early stages. Early detection and rapid response help lessen the severity of a health challenge and shorten the time to recovery.

  • Wean older, heavier pigs

    Several years ago, Rodger Main, DVM, and other researchers at Kansas State University conducted a large study comparing pigs weaned at various ages from 12 to 21 days of age. The results showed dramatic differences in postweaning performance across the various weaning ages. Besides dramatic improvements in average daily gain as weaning age increased, researchers also discovered profound reductions in mortality in the older pigs at weaning.

    The economic benefit of older weaning age is substantial. Some estimate the benefit is up to $1/head for each additional day of age. Another benefit to weaning older pigs came in the form of larger litters in subsequent farrowings from sows with longer lactation lengths.

    If you are purchasing pigs, make older weaning age and weight a part of the purchase specifications to improve throughput and average daily gain and reduce mortality. In the end, you will improve productivity and add to the bottom line.

  • Start pigs right

    Getting pigs off to a great start applies to newborn pigs as well as to newly weaned pigs.

    At birth, there is no substitute for ensuring every pig gets adequate colostrum, which provides the energy and antibodies needed to protect the pigs from diseases.

    At weaning, the first few days after weaning are essential as pigs transition from sow's milk to dry feed. Newly weaned pigs are stressed by being removed from their mothers and littermates, being transported and resorted into unfamiliar surroundings with new penmates.

    Managing this transition and identifying the pigs that fail to adjust in the first 24 to 48 hours is critical. Pigs that fall back at weaning are destined to do poorly and fall behind other pigs throughout the growing and finishing periods. A poor start contributes to a poor finish.

  • Evaluate pig flow

    Pig flow is movement of animals through a farm or system. Segregated production, such as all-in, all-out (AIAO) pig flow, is the practice of completely populating a site, barn or airspace, then at the end of that production period, completely emptying the site, barn or airspace before repeating the cycle. The purpose is to break the group-to-group disease transmission that routinely occurs with continuous-flow production.

    AIAO production is one of many health technologies that evolved in the 1980s to become a standard in today's industry. AIAO has gained almost universal acceptance in farrowing and nursery phases, and has gradually been adopted at the growing and finishing stages. The wean-to-finish concept helped advance this technology.

    Early adopters of segregated production realized as much as a 10% improvement in average daily gain and upwards of 7% improvement in feed efficiency. Diseases that were once endemic in a flow of pigs, such as APP and atrophic rhinitis, were rendered less harmful by segregating younger pigs from the disease-laden older pigs.

  • Adopt timely and humane euthanasia

    While it seems counterintuitive that euthanizing pigs would be an opportunity to improve throughput, from a health and welfare standpoint, it is very important.

    Every farm should have a written euthanasia protocol that describes methods and responsibilities. The most important responsibility producers have is to prevent animal suffering when the prospect of response to therapy is poor.

    Timely euthanasia improves throughput by quickly identifying and euthanizing sick pigs that have little or no chance of recovery. When handled properly, there will be less disease pressure and less potential for shedding pathogens to barnmates.

    Timely euthanasia allows the remaining pigs to perform better with less competition and lower stocking density. It also pays the largest benefits at closeout by reducing the variation and severe discounts that can affect the entire turn of pigs.

  • Tighten biosecurity

    The ultimate tool for disease prevention is to never allow the introduction of new infectious agents.

    The finishing phase of most operations is often considered to be at the bottom of the herd health pyramid. Consequently, the safeguards are usually fewer and less stringent than we see at sow sites and nurseries.

    Arguably, this is backwards thinking. Recent studies show that the majority of the cost of a PRRS outbreak in a farrow-to-finish operation is borne by the grow-finish stage of production. One study put the postweaning cost share of a PRRS break at 88%!

    The primary objective of any biosecurity protocol is to prevent the entry of new pathogens, regardless of the stage of production. While location of the site and proximity to other pigs are important biosecurity risks, there is usually little that can be done on these issues once a barn is sited. We can, however, work to reduce the risks associated with many other practices, vectors, and fomites that present biosecurity risks.

    Start by having your swine veterinarian perform a biosecurity audit of your farm. Your veterinarian will point out ways to reduce the disease risks and close holes in the biosecurity net. In the case of PRRS, small investments in biosecurity measures may prevent entry of a virus that can cost hundreds of thousands of dollars in production losses.

    Biosecurity does not come without some cost, but mostly it is investment in time, education and discipline. Some estimate the cost of a PRRS outbreak to a farrow-to-wean farm at $200/sow or half a million dollars for a 2,500-sow farm. That will buy a lot of biosecurity!

  • Weigh the value of lost opportunity

    Variation should be viewed as a “lost opportunity.” Every carcass that is “outside the box” results in unrealized revenue, even when that cost is spread across a truckload of pigs.

    Of course, each packer has a matrix that dictates the upper and lower limits for carcass weight. Some matrixes are tighter than others, and they vary by the degree of penalties assigned when carcasses land outside the box. Typically, the “sweet spot” of the matrix will range from 271 to 300 lb. live weight.

    A typical load of pigs weighing 285 lb. with normal variation could still have over a third of the pigs outside the box. Some studies have shown that the standard deviation of market weights (the weight above and below the average encompassing two-thirds of the set) is about 25 lb. Put another way, two-thirds of a set of pigs that average 285 lb. will fall between 260 and 310 lb. The farther away from the minimum and maximum weights, the higher the penalty will be for being outside the box.

    Again, depending on the packer, the penalty might be as little as $5/head for the first 10 lb. on either side of the box, but stepping up to nearly $40/head for those pigs under 230 lb. or over 310 lb.

    At current feed prices, it is foolish to send extremely heavy hogs to market. But, packer matrixes really tip the scale against light carcasses, which is where most of the opportunity lies.

  • Tools to lower variability

    We have many tools for lowering variability, especially when dealing with health issues.

    First, early detection and treatment with the appropriate antibiotic will reduce mortality and variation by lowering the days that the pigs are not eating or gaining weight.

    Certainly, accurate diagnosis, then prudent use of the antimicrobial that is most effective on the problem a farm is facing, are essential.

    Most veterinarians recommend hospital pens for disadvantaged pigs to reduce competition for food and water, allow them more space and provide the greatest chance for full recovery. The hospital pen allows for sorting off the pigs that fall back, as well as giving special attention to sick or injured pigs. To reduce variation at market time, these disadvantaged pigs must be identified early so their particular challenge can be addressed, which will help them to keep up with their healthy peers.

Economic Effects Of Variation

Economic Effects Of Variation

In 1986, I had a hole-in-one at the Ames (IA) Country Club. As I was carrying on like a kid, my golf partner sat quietly in the golf cart. I thought maybe the ball hadn't actually gone in, but I could see the entire green and the ball wasn't on it. I asked him, “Did you see that?! It went in the cup, didn't it?!”

“Yes,” he replied, “But what were you trying to do?”

It was a good point — but it took some of the fun out of it! And, of course, this golf story ends with a round of drinks at the clubhouse — so my perfection had its price!

This story of perfection is far from my normal golf game. Like most recreational golfers, my greatest struggle with the game is consistency — 3 pars followed by a double bogey (2 shots over par).

Golf can serve as an analogy with pork production. The hole in one in pork production is the full-valued pig — the one that receives no discounts and hits most of the production performance targets.

Like the hole-in-one, the upside of variation shows the potential of swine production, and we may think, “that's what we're trying to do” — but it can be costly.

Clearly the low end of variation — the double bogies — may be eliminated fairly easily by managing the golf round or pork production a bit more carefully.

What is Variation?

To discuss variation, we need a couple of statistical definitions:

A statistical population is a collection of all possible observations in a defined space. For example, a single barn has a population of 1,200 pigs.

A sample is a subset of the population. A pen in a barn or a truckload of pigs hauled out of a barn represents a sample of the pig population in the barn.

The individual pig on the truck is the observation within the sample of the truck, drawn from the population in the barn.

I often think of the “mean” or average as a sample level statistic. It tells us very little about the individual pig. In other words, they all look the same. They look like the mean.

In contrast, I think of variation as an observation-level statistic that gives us at least a fuzzy picture of what individual pigs look like.

Variation is a measure of dispersion of a variable's observations. Statistically, variation can be measured in several different ways:

  • Range is the distance from the high value to the low value of all observations.

  • Mean deviation is the average difference between repeated samples of two observations.

  • Standard deviation is a measure of the “deviation” around a “standard” observation — the standard usually being the mean or average of the observed values.

  • Coefficient of variation, or CV, is a unitless measure of variation (quantity without physical units) relative to the mean. It is the standard deviation divided by the mean, usually reported in terms of percentages.

Standard deviation is the most commonly used measure of variation. Its value has the same unit as the variable measured.

A large standard deviation implies a large dispersion of individual observations around the mean (a large range). A small standard deviation implies a small dispersion of individual observations around the mean.

The coefficient of variation is very useful for comparing the size of variation between two different samples.

For example, one finishing barn is closed out with an average weight of 275 lb. and a standard deviation of weights of 25 lb. A second barn closes out with an average weight of 260 lb. and a standard deviation of 24 lb. Which barn has more variable pigs? The 275-lb. finishing barn has a higher standard deviation, but its coefficient of variation (CV), standard deviation divided by mean, is 9.1%, while the CV for the 260-lb. barn is 9.23%.

So the barn with lighter average weights and a lower standard deviation actually has more relative variation than the other barn.

Production Variation

If you view the pigs in a barn, or pull a truckload of pigs from a barn, you will have a snapshot of the variability in that barn.

The truckload is the most common economic snapshot because it's when pigs are weighed and priced. It shows the impact of the production variation on revenue (price sold x quantity).

The only way to observe the true variability in a barn would be to dump the whole barn at once. When you pull truckloads over a period of time, or sort pigs going into the truck, you are changing the sampling of the barn's population with respect to time. Therefore, you do not observe a true cost of variation.

If you're good at sorting, your truckload will be less variable than your overall barn. And, if you pull loads, you're measuring the variation of the pigs left in the barn at a different time than the pigs marketed earlier. Consequently, you never see a real cost of variation in an operation unless you very carefully measure weights and feed intake of all pigs through time.

This analysis considers the impact of variation on profitability through time. It's more of a video clip of pig growth and value than a snapshot.

Modeling Variation in Growth

To demonstrate the economic value of reduced variation, a simulation model of pig growth and marketing is developed. The model requires only three components:

  • A pig growth function accounting for production variation.

  • Daily feed intake estimates for pigs to incorporate key variable costs.

  • A packer's pricing matrix to evaluate the revenue impacts of variation.

The pig growth function is adapted from data collected by Alan Schinckel in Purdue University research trials on lean growth and body composition. These data were used to estimate a model of variation in body weight and growth using mixed, non-linear regression methods. This equation is used to simulate the body weight of 180 pigs in the finishing stage — from 49 to 205 days of age — and allows each pig to be grown individually within the sample distribution.

Figures 1 and 2 show the growth and average daily gain curves for the range of lightweight, median and heavyweight pigs. Other pigs fall within this range.

The growth curves possess the stylized S-shaped growth curve. As the pigs grow, the range in the high and low pig weight for a given age increases. However, for the original simulation model, the coefficient of variation remains constant (CV = 8%). In other words, relative variability does not change in relation to the pigs' weight.

A daily feed intake equation was needed to estimate the feed costs for the gain achieved in the growth model. The feed intake of pigs over time is shown in Figure 3. On any given day, all pigs, regardless of their weight on that day, are assumed to have the same feed intake. All variation arising in costs originates only from the differing growth rates of the pigs.

The marginal cost of gain for a light pig is higher than the marginal cost of gain for a heavy pig. In reality, feed intake and growth are likely to be correlated. As feed intake increases, growth increases. It would be very interesting to consider what these covariate relationships might mean, but the complexity is beyond what is necessary for simulation purposes.

An equation relating backfat to bodyweight was used to estimate the lean composition of the pigs. The equation is very rudimentary and based on calibration to USDA Agricultural Marketing Service (AMS) reports of lean percent. As with the earlier example, quite a bit of work could be done on modeling the relationship of weight, age and lean percent or backfat.

The simulated model estimates that pigs average 265 lb. at 161 days of age for a lifetime average daily gain of approximately 1.65 lb./day. The backfat at this weight averages 0.71 in. For comparison, AMS reported (LH_HG201, 3/13/08) that negotiated pigs sold averaged 265 lb. and averaged 0.71 in. backfat.

Beyond the base model described above, which is the low-variation model (CV = 8%), two other models were simulated: a middle-variation model (CV = 10%) and a high-variation model (CV = 20%). Figure 4 shows the distribution of the pigs under the three levels of variation.

It's difficult to say which level of variation is most representative. Most CVs are reported for pigs marketed. It is safe to assume pigs marketed have already been sorted, thus lowering the CV to 8 or 10%.

However, Dewey, de Grau and Friendship, in an observation study of pig variation on commercial farms, reported at a 2001 London Swine Conference (Ontario, Canada) that over the life of pigs, the CV remains remarkably stable and varies between 20% and 31%, with 20% being the CV at 20 weeks of age (140 days).

This observed result is consistent with the growth function simulated with a CV of 20% for weights as the baseline of high variation. While nowhere near the complexity of the real world, the model will suffice to give some grainy video of the economic tradeoffs.

Simulating the Economic Impact of Variation

The primary economic impact of variation is the impact on revenue of the variation. This occurs through the combination of weight (pounds of pork sold), and price affected by packer premiums or discounts for weights and leanness of the pigs.

Figure 5 shows a representative packer grid. This is a surface plot that represents the revenue tradeoff in three dimensions — weight, backfat and premium level or price. To the left side, lightweight pigs are discounted; to the right side, heavy pigs are discounted. At the front edge of the box, pigs are discounted because of low backfat, and to the back of the box, pigs are discounted because of high backfat. The base hog price used is a $40/cwt., live equivalent price, and different values would affect absolute levels, but relative changes would be consistent.

The steps indicate where a premium/discount changes based on weight or backfat measures. You can market a pig anywhere on the surface or tread of the step and get the same price. The highest plateau is the highest possible value for a pig. Assuming costs are constant, ideally you would like to have all pigs priced at this plateau.

Figure 6 shows the high-variance pigs (CV = 20%) marketed through the packer grid, but not including feed costs or sort premiums. Notice how small the highest plateau is. Only 26% of the pigs meet the highest-revenue objective. Other pigs are discounted either because of weight or backfat measures. This is compared to Figure 7, which are the medium-variation pigs (CV = 10%). Not only are there more pigs on the plateau (37%), but 1.3% of pigs are now at the lowest possible price, whereas 2.7% of the higher-variance pigs are at the lowest value of $16.40/cwt.

Figures 8 and 9 take the analysis one step further to include feed costs. Feed costs are based on feed intake and growth described earlier and a corn price of $3.55/bu. and a soybean meal price of $275/ton.

Again, higher feed prices will affect the level of costs, but not the relative impacts of variation. These figures are shown as gross profit over feed costs/head. The distinguishing feature of these charts is the dark blue peak, which signifies pigs that are very near their “full value.”

At the lower left of Figure 8, a large number of high-variation pigs that are low weight and low backfat are actually sold at a loss. From an economic perspective, these pigs should simply be culled as not covering variable costs. With mid-variation (CV = 10%, Figure 9), there are no pigs sold at a loss; therefore, all pigs should be retained.

Now let's look at what's happening over time and levels of variation. Figures 10 and 11 show the gross profit over feed costs of marketing at the “optimum profit day/weight” for the medium- and high-variation examples. As a comparison to the surface charts, this chart is a slice of one day of a surface chart, and the day chosen is the day that the pigs, on average, have their highest value.

Figure 10 shows the value of each of the pigs marketed on Day 157 in a high-variance case (CV = 20%). Earlier, this was suggested as the variation one might observe in an unsorted barn or truckload sampled from that barn.

The pigs are marketed at an average weight of 258 lb. with an average value of $55.97/head. However, many pigs are marketed below this value and even in negative territory. The “full-valued pig” is marketed at 292 lb. and at a value of $86.37/head. The full-valued pig is the absolute best to hope for; it assumes no variation in weights, time or quality. But the difference between the full-valued pig and the average market pig is $30.40/head!

Achieving that optimum level for every pig is clearly not cost-effective. The only way I can imagine it is by selling each pig individually when it reaches that optimum — clearly beyond any reasonable management alternative. However, it does demonstrate the value of the “hole-in-one,” and we can improve by moving incrementally toward this full-value pig. Figure 11 demonstrates this.

Pigs in Figure 11 are drawn from a distribution of pigs with mid-variation (CV = 10%). This reduction in variation is similar to what is observed with sorting practices. The optimal date of marketing increases (164 vs. 157 days), average market weights are higher (271 vs. 258 lb.), and the average profitability increases ($68.37 vs. $55.97/head).

So reducing variation by approximately half results in an increase in profitability of about $12.40/head. The full-valued pig is still at 292 lb., but now its value is reduced to $82.52/head.

Why is the value reduced?

Because the full-value pig reaches market weight earlier with high variability, so it is reflected as having lower feed costs due to fewer days on feed. We would find a full-valued pig at Day 157 of marketing the medium-variance pigs, too, and it would have a value similar to the 157-day, full-valued pig for high-variation pigs.

The full-valued pig is showing that the heavier pigs pass through that point, and once they reach that point, the ideal would be to market them rather than reaching the point of decreasing returns as shown in these charts.

Figure 12 shows all three levels of variation, including the lowest variation sampled (CV = 8%). It is graphed on the day of the optimal marketing of the lowest-variation group, which is Day 167. The optimal marketing day is 10 days later than the high-variation pigs at 157 days, and the profit is much higher — $72.96/head vs. $55.97/head — a difference of nearly $17/head!

The full-value pig still exists. Its weight is remarkably similar to the other full-valued pigs, not surprisingly, and its value is close to the medium-variation pigs marketed at 164 days.

Although it is difficult to see, if you took the high-variation pigs to this marketing date from 157 days, then the average value of the high-variance pigs would be $54.73, a loss of another $1.20/head.

Finally, Figure 13 shows the “video” of pigs' values over time and growth. I included only the value of the low, average and high-weight pig for the low-variance case. Heavy pigs should be marketed as soon as possible because they are losing value both from a cost and revenue perspective. Similarly, light pigs represent a tradeoff between costs and the price/premium steps.

Notice that the “treads” on the steps are always sloping downward. Once you hit a premium level, the pig loses value every day beyond that point until it gets to the next step. This occurs because of the lightest pigs' higher cost of feed. If there were no costs to monitoring and sorting these pigs, you would get rid of them exactly when they hit the grid premium and not a day longer. You can also infer what happens with higher feed prices — the treads between the steps get steeper, suggesting even greater cost to holding low-weight pigs longer. In the extreme price event, the step up may not even compensate for the feed costs between steps — increasing the cost of these pigs that are hidden in the averages.


This analysis shows that the potential economic merits of reducing variation in pigs are significant. These benefits accrue for three fundamental reasons:

  • Marketing more pigs near the full-valued pig.

  • Increasing average weights possible at marketing, thus increasing total revenue by pushing more pounds through the system.

  • Reducing marginal feed costs for reaching higher-valued pigs.

The obvious, unanswered question is, what's the most cost-effective method to reduce variation to capture these profit opportunities?

A paper by J.F. Patience and A.D. Beaulieu at the 2006 Manitoba Swine Seminar reviewed research suggesting several possibilities to reduce or manage variation. They concluded, as most others have, that it is difficult to identify any single production practice — other than sorting — that consistently and significantly reduces variation because of the interplay of genetics and environment in production.

However, we may be asking the wrong question. Rather than asking which production methods could reduce variation, perhaps we should be asking what incentives can be put in place to reward practices that meet a target level of variation.

This is essentially what the packer grid in this analysis does. Packers don't say, “sort pigs to reduce the variation in the plant.” They provide a grid that gives rewards and penalties to reduce variation to meet their grid. It allows for flexibility and creativity in meeting that goal.

The same idea can be applied to swine production by rewarding reductions in variation. What would happen if, instead of making payments on a “per-pig-space basis” or a “pigs-out-the-door” basis,” the payments were allocated based on the number of “full-valued” pigs out the door? How much creativity would occur in finding ways to reduce variation in production, besides just sorting?

This paper suggests the value of reduced variation is there. Perhaps we should consider a new avenue to incentivize a reduction in production-based variation rather than prescribing methods. In the long run, the correct incentives may provide the most potential to truly reduce variation and capture that value.

Birth Weight Effects on Postnatal Growth

Birth Weight Effects on Postnatal Growth

In the existing commercial sow populations, variation in postnatal growth performance of their offspring may be already preprogrammed before birth. Because these limitations in postnatal growth may only become apparent in the late grower and finisher stages, sorting pigs by weight at the nursery and grower stages will not resolve variation in growth performance that appears at the finishing stage.

Prenatal programming affects muscle development early in gestation. A low number of muscle fibers in low-birth-weight pigs limit their muscle mass (lean yield) at market weight. However, gut development and health status of low-birth-weight pigs are also affected by prenatal programming and reduce survivability through lactation and the nursery stages.

We have increasing evidence that the changing dynamics of prenatal survival in mature sow populations are resulting in increasing variance in grow-finish performance. It is likely that this is partly due to prenatal programming problems.

The critical questions for producers are, how do we recognize the problem of prenatal programming at the production level, and what can be done about it?

Muscle Development Before Birth

The biphasic pattern of muscle fiber development (myogenesis) in the pig is illustrated in Figure 1.

In the first phase, Day 35 to Day 55 of gestation, a primary generation of so-called “primary myofibers” develops.

In the second phase, which lasts until Day 90 of gestation, the formation of secondary myofibers occurs. Over 20 secondary myofibers cluster around each primary myofiber. Considering the fact that an increase in muscle fiber number (muscle hyperplasia) ceases by around the 90th day of gestation, the number of primary and secondary muscle fibers formed by Day 90 ultimately determines the total number of muscle fibers at birth. Importantly, the total number of muscle fibers at birth is lower in smaller fetuses compared to larger fetuses.

In experimental studies, even modest levels of intrauterine crowding of embryos early in gestation have a negative impact on fetal muscle fiber development. Given the apparent imbalance in modern prolific sows between ovulation rate, early embryonic survival and uterine capacity — and consequences for fetal and postnatal development — the reproductive characteristics of prolific dam lines need careful consideration.

Although the primary goal of increasing the number of pigs born per litter may be achieved in prolific sow lines, associated adverse effects on prenatal programming are apparent. As a result, selection for increased litter size at birth has led to an increased between-litter variation in average piglet birth weight, as well as to an overall decrease in birth weight. In the extremes of high litter size born, the growth potential of the live born pigs that survive to weaning are seriously compromised by intrauterine competition with an increasing number of stillborn pigs that, obviously, never enter the nursery and grow-finish stages of production.

Birth Weight, Growth and Carcass Quality

Both the type and the total number of muscle fibers is fixed at birth and, between them, determine the lean growth potential of the pig. As the size and length of existing muscle fibers increases after birth, an increase in total muscle mass is apparent. Low-birth-weight pigs with low muscle fiber numbers, therefore, are expected to have impaired postnatal growth.

Experimental studies of within-litter variation in birth weight clearly demonstrate the associations among birth weight, carcass characteristics and meat quality traits.

For example, in the study shown in Table 1, pigs of low birth weight exhibited the lowest total number of muscle fibers, the largest muscle fiber size and the highest percentages of abnormal “giant” muscle fibers in the muscles investigated. These pigs also had the lowest percentages of muscle tissue, the lowest total protein and the lowest semitendinosus muscle weight, yet the percentages of internal organs, skin, bone and total water were highest, compared to their heavier littermates.

When slaughtered at a fixed age of 182 days, the pigs of low birth weight were lighter, had lower meat percentages and smaller loin eye area averages, although their omental (abdominal) fat percentages tended to be higher than pigs of high birth weight. With respect to meat quality, higher drip losses were determined in the longissimus muscle of low-birth-weight pigs.

Other studies confirm that low-birth- weight pigs required an extra 12 days to reach the same slaughter weight, and their feed conversion ratio was inferior. Of great importance to consumer satisfaction, the low-birth-weight pigs exhibited a lower score for loin meat tenderness compared with high-birth-weight pigs. Collectively, research indicates that pigs of low birth weight develop lower carcass and meat quality.

Birth Weight Variance

Comparisons between the largest pigs in a litter at birth and the smallest are most frequently used to study the impacts of birth weights on postnatal growth performance. However, if the limitations in functional uterine capacity in hyper-prolific sows results in prenatal programming of entire litters, we must also try to understand how the average birth weight variation between litters is a major cause of variance in postnatal performance.

Indeed, selection and production strategies that address the problem of between-litter variation in birth weight may be the most important aspect in addressing postnatal growth potential.

As Figure 2 shows, both the mean and the variance in birth weight decrease as litters get bigger. The birth weight of most pigs born in litters larger than 15 is relatively low. Likewise, between-litter variation in average birth weight is relatively low in these larger litters because the sow's limited uterine capacity is unable to support a higher birth weight. Furthermore, there appears to be a lower limit of average birth weight of around 2.2 lb., which is more or less independent of litter size.

At the other extreme, litters of less than 10 pigs should not have suffered from extreme intrauterine crowding in early gestation. The average litter birth weight tends to be higher in these litters.

Given these extreme effects on litter birth weight, the greatest likelihood of finding variation in average litter birth weight appears to be in litters of between 10 and 15 total born. When only these litters are taken into account, the overall impact of number born on average litter birth weight is relatively small (<40 g or 0.09 lb. for each additional pig born between 10 and 15).

In contrast, the difference in average birth weight between the heaviest and lightest litters in the range of 10 to 15 total born is over 2.2 lb. Clearly, some factor other than total born/litter is driving these major differences in average litter birth weight.

The fact that low-average birth weight litters have more pigs born dead and less piglets weaned is consistent with the notion that these litters are subjected to prenatal programming in the uterus. Also, the lower within-litter standard deviation of birth weight in the low-average-birth weight litters may be a consequence of the prenatal loss of the smaller and weaker pigs, thus already reducing the variation in litter birth weight at term.

In contrast, in litters not subjected to extremes of intrauterine crowding, pigs across a wider range of birth weights have the opportunity to survive to term, and this would explain the higher variance in birth weights we observed in the higher-average birth weight litters.

We conclude from these analyses that between-litter variance in birth weight is a major contributor to variation in postnatal growth performance.

A study of phenotypic data from 600 litters born to multiparous commercial sows suggests that low-average-birth weight is the result of intrauterine crowding earlier in gestation and prenatal programming.

Necropsy was performed on a subset of stillborn pigs that fell within the mid-weight range for their respective litters. In addition, data on organ weights were used to estimate “brain sparing effects” as a measure of prenatal programming (Figure 3).

Between-litter variation in average birth weight was again the biggest source of variation in birth weight in litters of 10 to 15 pigs born. More importantly, the stillborn pigs from lower average birth weight litters carried all the negative phenotypic characteristics associated with prenatal programming of poor postnatal performance.

These data further support the suggestion that one of the major causes of variation in postnatal growth performance will be between-litter variation in average birth weight. Linking back to the extensive data on the impact of birth weight on postnatal growth performance reviewed earlier, the postnatal growth potential of low-birth-weight litters should be a major concern for all pork producers.

Bottom Line for Better Production Systems

If prenatal development affects postnatal variation in growth performance, what are the practical resolutions to this problem?

The continued selection for increased litter size born, without understanding implications for variation in average litter birth weight in litters born to higher-parity sows, seems questionable. Feed costs to finish market hogs continue to rise, and the livestock industry will increasingly compete with other industries seeking to divert these feedstocks to other industrial processes — most notably ethanol production.

The efficiency of feed utilization, and minimal environmental impacts of food-animal production, will become increasingly important issues in our ability to sustain pork production. The net efficiency with which we can produce a pound of high-quality pork is critical to the competitiveness of our industry.

As intensive pork production systems continue to evolve, greater attention is being paid to the concept of segregated management systems. The reasons for adopting segregated production flows vary, but the underlying principle remains the same ? the net advantages that come from managing particular subpopulations of the pork production chain to achieve greater efficiency and consistency of production.

Segregation may be a spatial concept, in a geographic sense, to improve the control of disease transmission at different levels of the production pyramid. Increasingly, segregation involves separation of subpopulations on the basis of their susceptibility to disease challenges compared to, say, more mature animals, or because segregation allows specialized management to be applied in a cost-effective way to these segregated populations.

Segregation in this instance can be on-site within a farm, or even within-barn, depending on the situation and goals.

In light of the above discussion, we suggest that segregation of entire litters on the basis of average litter birth weight may do more to address variation in postnatal growth performance than existing programs of extensive crossfostering, irrespective of average litter birth weight, and the successive sorting of pigs by weight in the later stages of production. Neither of these strategies accepts the major inherent differences in postnatal growth potential that clearly exists between litters with high and low average birth weight.

Table 1. Association Between High and Low Birth Weights Within a Litter and Postnatal Growth, Carcass Characteristics and Pork Quality Traits*

Within-litter birth weight grouping

Low (2.0 lb.) >High (4.0 lb.)
Average daily gain, lb. 1.3 1.4
Live weight, lb. 233.4 255.2
Hot carcass weight, lb. 185.2 203.5
Drip loss, % 6.6 4.5
Myofiber* area, µm2 3,900 3,200
Myofiber number × 1,000 900 1,200
“Giant” myofibers, % 0.44 0.07
Myofibers are the muscle fibers making up the muscle mass in newborn pigs.
*from Rhefeldt et al., 2004

Variation: You Can Manage It, But You Can't Avoid It

Variation: You Can Manage It, But You Can&#039;t Avoid It

Prior to the widespread adoption of all-in, all-out (AIAO) production systems, variation in growth was largely a “hidden” cost. Pigs were sorted from pens when they reached market weight, and the fact that some took longer than others went largely unnoticed, or at least ignored.

Furthermore, in continuous-flow systems, downtime due to variable growth rates affects pen usage, while in AIAO systems it affects room or barn usage. Consequently, the economic impact of variation is much greater in AIAO systems.

Variation in market weights increases sort losses, a cost that goes straight to the bottom line. From a labor and management perspective, there is the annoyance factor of dealing with tail-end pigs in a room or barn, which is also greater than in pens.

The cost of variation has always been with us, but those costs are now much more obvious.

In the past, the industry's singular focus was on “average” growth rate. Today, while we continue to pay attention to growth rate averages, greater attention is being focused on the “range” in that growth ? the variability of growth.

Measuring Variation

Statistically, variation can be defined in a variety of ways. The most common terms used to express it are standard deviation (SD) and coefficient of variation (CV), although range may also be useful.

Most people are familiar with the “bell curve,” which shows the typical distribution of measurements within a specific group. Many measurements can be described using a bell curve (weight, height, etc.).

If the measurement of a group or population is made and, when plotted, displays a bell shape, it is called a “normal” distribution. If the plotted data do not follow the bell shape, the data are called “skewed.”

For example, when the body weights of 632 pigs, averaging 20 weeks of age, are charted (Figure 1), it shows a very typical distribution of body weights for pigs of that age. This distribution is almost “normal,” but is skewed slightly to the left, reflecting the exaggerated number of tail-enders in the group.

The shape of the bell curve reveals a great deal about a population or group. For example, if the bell shape is narrow, the population is relatively uniform because most of the measurements are closer to the average. If the bell shape is wide, the population is less uniform because more measurements are found further from the average.

One useful measure of the width of the bell curve is called the standard deviation (SD). The wider the bell shape, the larger the standard deviation, and the greater the variability of the group of animals.

Understanding the Terminology

Following are definitions of important statistics used to describe variation in a group of pigs.

  • Mean: The mean is the average of all weights within a group of pigs. It provides no indication of the variability of weights within the group.

  • Median: The median is determined by aligning all pig weights in order of magnitude (i.e., from smallest to largest or vice versa), then selecting the middle observation. If the distribution is “normal,” the median and the mean (average) will be very similar, if not identical.

  • Minimum, maximum and range: The minimum and maximum are self-evident; they are the lightest and heaviest weights within the group. The difference between the minimum and maximum is called the range. The wider the shape of the bell curve, thus, the less uniform the group of pigs, the larger will be the range.

  • Standard deviation (SD): The standard deviation is a measure of dispersion. The greater the variation in weight of a group of pigs, the larger will be the standard deviation.

In a “normal” distribution, statisticians have determined that one (1) standard deviation about the mean will include 68% of the pigs in the total group. Using the data in Table 1 for the 19-day-old pigs, and assuming the data is distributed normally, the standard deviation has been calculated to be 2.7 lb., with a mean of 11.9 lb. Thus, we can estimate that 68% of the pigs, or 863 pigs in this group, will be within one standard deviation of the mean and weigh between 9.2 lb. (11.9 - 2.7) and 14.6 lb. (11.9 + 2.7).

Two standard deviations take in 95% of the pigs. Therefore, 1,206 pigs weigh between 6.5 lb. and 17.3 lb.

Three standard deviations will include 99% of the pigs, so 1,261 pigs weigh between 3.8 lb. and 20.0 lb. Of course, these numbers are approximations because data might not be perfectly, normally distributed, as Figure 1 shows, or because insufficient numbers of animals were weighed to adequately estimate these parameters.

  • Coefficient of variation (CV): The coefficient of variation is calculated by dividing the standard deviation by the mean, then multiplying by 100.

Referring again to the example in Table 1, the standard deviation of 2.7 lb. can also be presented as a coefficient of variation of 22.7%. The standard deviation becomes larger as the pigs grow.

Therefore, in order to determine if relative variation is increasing or decreasing as pigs grow, the coefficient of variation is often used.

In Table 1, while the standard deviation increases as the pigs become heavier, the coefficient of variation decreases, indicating that relative variability among pigs under commercial conditions typically declines as they grow.

There is one danger in using CV to represent variation. Sometimes, within pigs of the same age, the CV changes not because the SD changes, but because the mean weight changes (i.e., weaning weight increases). One could misinterpret this as meaning variation is reduced, when in actuality the variation did not change at all.

Measuring Variation On the Farm

There is surprisingly little information on normal distributions of bodyweights on commercial farms. Because it requires the weighing of many animals in order to accurately estimate SD and CV, it is not commonly done on most farms.

Furthermore, most research data cannot be used as reference points because in most experiments, animals are pre-selected to obtain a uniform group to increase experimental precision.

Geneticists have this information because variation is essential in selection programs, but even that data is not widely available.

Still, it is important that we develop an understanding of “normal” or “typical” variation, because it helps us to develop strategies for dealing with problems on individual farms or systems.

Standards can be used to determine if a given farm is better advised to manage variation or to minimize it. The difference between these two choices represents a critical management decision. The limited amount of data on the subject suggests that much larger variation is seen in some circumstances. CVs of 20% to 35% in grow-finish pigs among commercial farms have been reported.

The minimum number of pigs that must be weighed in order to estimate a mean, a standard deviation or a coefficient of variation is not constant. Rather, the number depends on the intrinsic variability within the population.

At weaning, because variability is so high, weighing even 100 pigs provides a poor estimate of the CV. However, when pigs are removed from the nursery or at first pull in a finishing facility, randomly weighing as few as 50 pigs throughout the barn will provide satisfactory information.

Random selection for weighing is very important because weighing too many or too few of the lighter and heavier pigs within the group will skew the results. If too many “outliers” are weighed, variation will be overestimated; if too few are weighed, variation will be underestimated.

Using the weights of pigs at marketing does not provide an accurate estimate of variability because it represents a group of animals pre-selected according to their market weights. For this reason, we prefer to use the weights of pigs at first pull because all animals can be included. However, this is not a particularly convenient number to generate on most farms, so alternatives must be developed.

Causes of Variation

Many factors can affect the degree of variability observed on a given farm. Without question, a certain amount of variability is “programmed” at the time a pig is born. Pigs that are smaller at birth are compromised physiologically and socially, and their expected performance will fall short when compared to their heavier contemporaries.

In addition to these innate contributors to variability, there are many external forces that come into play as well, such as health status, access to resources (feed, water) and poor ventilation.

  • Prenatal influences: Variation begins on the day pigs are born. Studies of neonatal and weaned pig management have reported that even within a litter, the CV for birth weight is between 22% and 26%. As litter size increases, the average birth weight declines by about 0.1 lb. for every additional piglet in the litter.

    While differences in birth weight are obvious to any farrowing technician, what is less clear is the relationship between birth weight and physiological “competency” at birth.

    For example, differences associated with low birth weight have been observed in reduced number and height of intestinal villi, lactase and lipase activity, reduced muscle respiratory enzyme activity, fewer muscle thyroid hormone receptors, lower IGF-1 levels in the blood and fewer muscle fibers.

  • Postnatal influences: After birth, additional factors contribute to variability. For example, heavier birth weight piglets consume about 30% more milk than their lighter littermates. In addition, heavier birth weight piglets, or at least those that win the most fights early in life, tend to suckle the anterior teats on the sow, which are known to deliver higher milk volumes. In one study, pigs nursing the anterior teats were 3.3 lb. heavier at weaning than those adopting the posterior teats.

    Lower milk intake is not only associated with slower growth, but also reduced whole-body protein synthesis, according to research conducted in the United Kingdom. That research also reported that tripling milk intake during the first week of life quadrupled the pigs' protein deposition rate.

  • Postweaning influences: One of the most predictable contributors to variability in the postweaning period is the variability in weaning weight. For example, the correlation between weaning weight and nursery exit weight was found to be 0.73. Numerous authors have related weaning weight to nursery exit weight by suggesting that for every 1 lb. increase in weaning weight, nursery exit weights will increase by a given amount.

    At the Prairie Swine Center Elstow Research Farm, we have found that for every 1 lb. increase in weaning weight, there is a 1.9 lb. increase in nursery exit weight (56 days of age) and a 4.2 lb increase in market weight. This relationship varies widely among farms.

  • Herd health and pathogen exposure: While inherent factors such as birth weight, weaning weight and suckling habits affect variability in pigs, there are many other “external” forces at play as well.

    Perhaps the most important external force on variability is the disease status of the herd. Because the extent of disease exposure differs among animals, and because the impact of that exposure on animal health and performance also differs among individuals, it is not surprising to observe that herd health status can have a major impact on variability.

  • Feed and water: Access to resources, such as feed and water, is also a potential contributor to variability.

    If feed or water access is limiting, dominant pigs in a pen will have an advantage over subordinate pigs, which results in greater growth disparity.

Social Behavior Model

There is a very interesting social behavior model for describing variability where one considers the average performance of a group of pigs along with the magnitude of the variation about this mean.

If average performance is very good and the degree of variation is low, one can assume that the conditions in which the pig are being reared are good and there is no depression in growth due to aggressive behaviors. Conversely, where performance is suboptimal and variation is high, one can assume there is competition for resources, such as food and water.

Overcrowding is not a likely issue in this scenario, because space is not a resource that pigs can hoard away from other pigs in the pen. However, pigs can prevent others from eating or drinking. The resultant uneven distribution of feed and water does lead to increased variability.

In the third scenario, performance is poor but variability is low, indicating an overall impairment due to a poor environment. Crowding could be the problem in this scenario, because crowding, unless severe, will uniformly depress growth, but not increase variability.

Addressing Variability

The challenge of variability can be addressed in two ways ? reducing variability and managing variability.

If variability within a barn is already quite low, producers are more likely to achieve success by seeking ways to manage variability. But if variability is high, then clearly there are deficiencies within the barn that are impairing performance and should be addressed. In this instance, it should be possible to reduce variability.

Reasonable targets for variability in a barn can be based on CV as described above. Although information on “normal” variability is admittedly limited, I would offer the following thresholds for CV:

  • 20% of weaning weights;

  • 12 to 15% for nursery exit weights; and

  • 8 to 12% for weight at first pull from the finishing barn.

In other words, if the CV for body weight at weaning is around 20%, at nursery exit is 12-15%, or at first pull is 8-12%, then it makes sense for barn managers to seek ways to manage variability rather than reduce it because it is already close to the lower practical limit.

These targets may change in the future as we develop more information on CVs under commercial conditions.

Topic of Interest

Variability is becoming a topic of increased interest in the pig industry due to its substantive impact on net income. This has become more obvious in all-in, all-out systems, where tail-end pigs are more obvious than they would be in a continuous-flow system.

Although variability has earned extra attention, there is much to learn, such as how much variability is inherent and must therefore be accepted, and how much is excessive and therefore, at least theoretically, can be reduced.

Poor herd health, itself a poorly defined term, is believed to be a major contributor to variability. But we also know that inadequate access to feed and water can contribute.

Managing variability will be the focus of most farms, requiring imaginative strategies based on facts and not specious logic to be successful.

Unfortunately, many procedures known to effectively manage variation require either changes in physical facilities or increased labor, neither of which is viewed with much enthusiasm at this point in the pork production cycle.

Nonetheless, there are substantial rewards to producers who reduce or manage variability effectively, because the costs of not doing so are also substantial.

Table 1. Example Variation in Body Weight of Pigs at Three Ages1

Average age, days

19 68 140
No. of pigs 1,264 700 632M
Weight, lb.

Mean 11.9 64.1 228.2

Median 11.9 64.0 229.7

Minimum 5.3 52.4 163.7

Maximum 20.2 90.0 274.8

Range 14.9 37.6 111.1

Range, % of mean 121 59 48
Standard deviation, lb. 2.7 8.2 18.3
Coefficient of variation, % 22.4 12.82 8.02
1Body weights were determined on whole groups of animals without pre-selection at weaning (19 days), nursery exit (68 days of age) and at 20 weeks of age before the first market pull. All were collected at the Prairie Swine Centre Elstow Research Farm. The weights were collected at different times, so the three groups of pigs are not related to each other. The ages represent means, although the range in ages would be plus/minus three or four days.

Consistent, Targeted Nutrition Improves Efficiency

Consistent, Targeted Nutrition Improves Efficiency

Nutritional programs can certainly play a major role in the amount of weight variation within a common group of pigs. The ability to minimize this variation involves many management, nutritional and health decisions.

From a nutritional standpoint, there are numerous ways to minimize the variation within a common group of pigs by providing consistent, nutritionally adequate diets formulated for specific genders and weights. Historically, this has been accomplished by feeding simple cereal grain-soybean meal-based diets throughout the various production stages.

However, with current feed ingredient prices at record highs, any and all options to determine optimum use of alternative ingredients, as well as the most economical nutrient levels of various diets, are being explored.

As feed alternatives or lower-quality (less digestible) replacements for lactose, protein and energy are utilized in diets, the potential for increased variation in a common pig group is more likely.

The effect of increased variation generally is not evaluated when diet decisions are made. The decision to lower feed cost is commonly the overriding factor.

While limited research data has evaluated the impacts of different alternatives and lower-quality ingredients on total group weight variation, the effects can be pronounced if feed ingredients are of poor quality.

It is important to remember that increasing the growth rate of the entire group of pigs will not reduce variation in the group or the need to sort pigs at market. Increasing growth rate will, however, increase the weight of the slow-growing pigs, which is the main marketing issue.

Following are eight areas that producers should focus on as they attempt to increase the growth rate of an entire group of pigs:

  1. Use genetics capable of high growth rate in commercial conditions.

  2. Maintain high health status.

  3. Identify and use sows with high milk production.

  4. Aim for high lactation feed intake to increase weaning weight.

  5. Increase age at weaning.

  6. Increase energy density of the diet to increase growth rate.

  7. Feed correct amino acid levels.

  8. Optimize feeding of ractopamine (Paylean from Elanco Animal Health).

While this list provides a basis for improving the growth rate of an entire group, following are several areas where nutrition may have direct implications on reducing actual variation within a group of pigs.

  • Improve pig birth and weaning weights.

    Total pigs born/litter and number born alive/litter have increased dramatically in the last several years. Since 2000, the rate of progress has been approximately 0.2 pigs/litter each year.

    This dramatic increase in litter size has been achieved through the application of genetic improvement focusing on ovulation rate. While genetic selection for increased ovulation rate has increased litter size, unfortunately, it has also increased the number of stillborns/litter and lowered average pig birth weights.

    Many factors affect fetal growth and development, including sow ovulation rate, uterine capacity, genotype, nutrition and feeding regimens.

    Researchers are beginning to understand that uterine capacity, which determines the number of fetuses maintained during pregnancy, is one of the greatest limitations to litter size. And litter weight is directly related to litter size. Pigs born in large litters are lighter at term because of the decreased placental surface area available to each.

    Additionally, mobilization of energy substrates increases in sows with larger litters. Glucose is a major energy substrate for fetuses, and has been shown to decrease in sows with large litters, due to the high-energy requirement necessary to sustain the uterus and fetuses.

  • There are two approaches to help solve the variability in piglet birth weights — genetically or nutritionally. Genetically, producers could select for moderate ovulation rate with high embryonic survival to reduce lightweight fetuses. The nutritional approach is to increase nutrient availability to the lightest fetuses to increase their size.

    Research has shown secondary muscle fiber development, which is an important determinant of postnatal growth, can be improved by increasing sow feed intake from Day 25 to Day 50 of gestation or after Day 70 of gestation. But high-energy intake during gestation increases expense, decreases feed intake during lactation and impairs mammary gland development. And research shows that high intake in gestation doesn't always increase birth weight, secondary muscle fiber number or carcass parameters.

    The addition of L-carnitine, a water-soluble, vitamin-like compound, to gestation diets has consistently resulted in increased litter weights at birth and weaning.

    Other researchers have observed increased sow weight gain and improved average fetal weight at Day 70 of gestation in sows fed supplemental L-carnitine. These effects can be attributed to significant changes in gene expression due to L-carnitine supplementation, which is involved in the regulation of muscle fiber development of the fetus and, therefore, improves pig and litter weight at birth.

  • Increase weight gain of the smallest pigs in a farrowing group.

    Several procedures can be used to increase the weight gain of the smaller pigs in an attempt to reduce variation in a group. Split suckling, use of supplemental milk and shifting the smallest pigs to better milking sows are examples. These management techniques have been proven to slightly increase the weight gain of the small pigs and, thus, reduce variation at market weight. However, the impacts are all relatively small, so the economic payback must be carefully calculated before implementation.

    Split-nursing — allowing the smallest half of the litter access to the sow for two hours within a 24-hour period after farrowing — has been shown to reduce variation in average daily gain and, thus, numerically reduce the variation in weaning weight. But, again, the impact is relatively small (about 2% lower coefficient of variation [CV]).

    Research has also shown that offering milk replacer to nursing litters can effectively increase weaning weight and that weight is not lost during the nursery stage. Thus, the increased weight at weaning remains at market time, but it must pay for the entire cost of the milk replacer.

    Similarly, trials with complex nursery diets have demonstrated increased weight gain in the nursery. Although data has not been entirely consistent, the advantage often does not become larger during the finishing stage.

    These changes in pig weight are relatively small compared to the differences caused by weaning age, sex or health status.

  • Consider split-gender housing and feeding.

    Since barrows grow faster than gilts, raising pigs within a common group based on gender will reduce the variation within that group simply because the variation in growth rate compared to mixed-gender feeding is reduced. Because barrow and gilt growth rates differ, diets are often formulated for specific genders at given weights.

    Another approach is to feed barrows and gilts the same diets, but alter the feed budget to match their nutrient needs at different stages of growth.

    Although split-gender feeding is simple in concept, the production system must be large enough to fill a barn or site with one gender within a reasonable amount of time.

    If split-gender feeding is practiced, but it takes several weeks to fill the barn, the variation in pig weights within that barn will be greater than if the pigs were housed as mixed-gender groups from a common weaning group.

    Likewise, if a common barn is filled by gender in a short period of time, but the pigs come from multiple sow production sites, the health status of the pigs may be jeopardized, which may reduce growth rates of the entire barn.

    The bottom line is this — filling a site or barn over multiple weeks or from multiple sources produces other large sources of variation (weaning age, health status) that may overwhelm any advantage of single-gender housing. As a rule of thumb, if a barn cannot be filled with a single sex within seven days, pigs should be housed as mixed sex to improve facility utilization.

  • Feed multiple diets within a group.

    Grouping pigs by gender in order to feed higher amino acid levels to the gilts has been practiced in the industry for some time. However, simply dividing groups based on weight has not been commonly practiced.

  • Research has shown that feeding different energy level diets to the light pigs compared to heavy pigs can reduce final variation of a common group. In concept, the lightest 50% of pigs in a barn are fed a higher-energy diet than the heaviest 50% of pigs. Research clearly shows improved average daily gain when pigs are fed higher-energy diets, especially in the early finishing period.
  • Thus, feeding different diets based on initial body weight going into the finisher may help reduce the final variation in the barn.

    Another approach to increasing weight gain of the lighter pigs in a group is to bump amino acid levels. In reality, the lightest pigs may not actually have a higher amino acid requirement than the heavier pigs. Weight does not accurately depict the amino acid requirements within a population.

    Rate of protein accretion and feed intake are the major determinants of amino acid requirements. Therefore, the heavier, faster-growing pigs may actually have a higher amino acid requirement because they have higher protein deposition rates, even though they consume more feed. With current knowledge, we formulate diets for the light and heavy groups to have similar amino acid:calorie ratios based on their average weight.

  • Use alternative feed ingredients.

    The use of alternative feed ingredients that are cheaper than corn or soybean meal can lower diet costs. The challenge is to balance the lower cost with any other potential pitfalls that may come with the alternative ingredients.

    Before any alternative ingredient is used, the nutrient composition must be understood, and the aid of a professional nutritionist should be sought to minimize any negative effects and to capture the potential value.

    For example, the use of distiller's dried grains with solubles (DDGS) will lower diet cost in most situations. However, use of the ethanol by-product also reduces carcass yield, and has been shown to increase the variation in weight within a common group of pigs when fed through marketing.

    While less data is available on the effects of various bakery by-products, meat and bonemeal or fibrous ingredients, such as wheat middlings or soybean hulls, on variation of pig weight, producers need to be aware of the potential lost revenue if the alternative ingredients result in increased variation due to changes in feed intake patterns.

    In addition, the economic impact of the change in carcass yield or quality (carcass fat softness) must be taken into account when determining the value of alternative feed ingredients. With any alternative, increased sampling and ingredient testing must occur to determine nutrient variability. Then, an informed decision can be made relative to any potential negative impacts that the variability will have on pig performance.

  • Weigh health programs and antibiotic usage.

    Although “high-health systems” is a nebulous term, it is meant to encompass the many factors that improve the health status of pigs within a group.

    Research has shown that pigs reared in an all-in, all-out manner have less variation in growth rate and market weight (7.5% vs. 8.8% CV) than pigs reared in a continuous-flow manner.

    Other system design factors that can lead to sustained improvements in health status, such as reduction in sources of pigs, location of the source herd and location of the growing barns, would be expected to also reduce variation in weight gain.

    Promptly treating clinical disease to enhance recovery and reduce spread of the bacteria within the group will reduce the number of lightweight pigs at market and, thus, reduce variation.

    The use of feed-grade antibiotics has been cited as a means of reducing variation in final market weight. Published evidence is lacking that this phenomena actually occurs because the impact is relatively small. A large number of pigs or groups of pigs are required to experimentally prove or disprove the concept.

    However, there is evidence that in multi-site production systems, feeding antibiotics consistently results in improved growth rate of nursery pigs, but not in finishing pigs.

  • Consider pelleted feed.

    Pellets can be made of different lengths, diameters and degrees of hardness. The ingredients in the diet will influence pellet hardness and quality. Various studies suggest a 3-6% improvement in growth rate and feed efficiency when pigs are fed pelleted diets compared to a meal. The benefit appears to result from less feed wastage and the ability to use ingredients with smaller particle size.

    Pelleting appears to improve the nutritional value of high-fiber feed ingredients to a greater extent than that of low-fiber ingredients. This may be a result of increasing the bulk density of the feed. As with any feed processing method, the increased cost must be offset by the improved feed efficiency of pigs fed the pelleted diet.

    We are not aware of any data indicating that pelleting influences variation in growth rate.

  • Use nutrition to minimize seasonal variation.

    Although great strides have been made in managing the environment in barns, seasonal variation in growth rate remains a major obstacle within a production system. Pigs placed in the late summer through the early winter months grow faster than pigs placed in late winter and spring months (Figure 1). As a result, market weights are reduced by 6 to 13 lb. for pigs marketed in June through mid-September. Market price is normally highest during this same time period.

    For many production systems, 75 to 80% of the net profit for the year is derived during these summer months. The most profitable systems have determined methods to maintain market weights through the summer months. The only way that weights can be maintained is by increasing growth rate for groups of pigs finished during this time or by increasing days in the barn.

    Growth rate can be increased by one of two main feeding interventions. First, increase the energy density of the diet during summer months or for newly placed groups that will be marketed during the summer and early fall. Second, optimize ractopamine (Paylean) use by season of the year to assist in making market weights more uniform throughout the year.

    Because the response to ractopamine is consistent for pigs at various weights, it can also be used to increase the growth rate of the lightest pigs in the group to make them grow similar to the heaviest pigs. This is especially important during the summer months to maximize average daily gain of both the fastest and the slowest-growing pigs. In winter months, more emphasis is placed on slowest-growing pigs, as the growth rate of the entire group is higher.

    The difference between feeding ractopamine and increasing energy density of the diet is that feeding ractopamine is often economical regardless of whether the weight gain is needed or not. The economic value of feeding ractopamine is much greater in pigs that require the extra weight gain; however, the improvements in feed efficiency and carcass parameters (loin depth and yield) usually make it economical to feed to heavy pigs also. Thus, if ractopamine were only fed to the light pigs in the group, the potential increase in profit on the heavy pigs would be lost.

    If dietary energy is already at the economic maximum and ractopamine is already being used, pigs must be given more days to grow to achieve the same market weight in the summer due to the lower seasonal growth rate. Finding extra days is not easy, but the production system needs to be built with this flexibility.

    For example, wean-to-finish barns offer flexibility, as they can be double- or triple-stocked in the summer months to allow pigs in other barns more time before the facility is needed.

    Similarly, heavier stocking density in nurseries in summer months reduces the finishing barn requirements. Heavier stocking density will reduce growth rate of these pigs; however, they will be marketed during the winter months when space is normally not a problem.

  • Maximize water availability.

    As with all areas of production, clean, fresh water should be made available to pigs at all times. While this suggestion seems simple, it can be a source of concern if no one is paying attention to the pigs' water needs.

    Groups of pigs with insufficient access to water will have more variation. Plugged nipples, poorly designed water troughs or incomplete filling of gestation barn troughs caused by feed blockage can cause restricted water supply. Standard operating procedures on a farm should ensure that all pigs have proper access to feed and water.