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Integrating Science into PracticeIntegrating Science into Practiceand Getting it Rightand Getting it Right

R. Dean Boyd, R. Dean Boyd, PhPh D DTechnical Director Technical Director –– The The HanorHanor Company Company

Adjunct Professor of Animal NutritionAdjunct Professor of Animal NutritionNorth Carolina State U.North Carolina State U.

AASV 43AASV 43rdrd Annual Meeting, 2012 Annual Meeting, 2012‘‘Integrating Science, Welfare and Economics in PracticeIntegrating Science, Welfare and Economics in Practice’

A Tribute in Honor and Remembrance of A Tribute in Honor and Remembrance of ––DrDr. Howard . Howard W. Dunne, W. Dunne, 1913-19741913-1974

1941 DVM – Iowa State U.1951 Ph D – Michigan State U.1953–1974 – Penn State U.

90 Scientific papers, Editor – Diseases of Swine

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Presentation Addresses:Presentation Addresses:The Integration of Science into PracticeThe Integration of Science into Practice

••Getting Science Applied CorrectGetting Science Applied Correct

••Role of Technical Professionals in that ProcessRole of Technical Professionals in that Process

••ID Problems to be Resolved in 5-8 YearsID Problems to be Resolved in 5-8 Years

Science THEN Science THEN –– Science NOW Science NOW

Since the passing of Dr. Dunne, advancesin Science have come like a Tsunami;almost everything has changed.

Genetics Genetics –– Science of the 21Science of the 21stst Century ? Century ?Advances during the past 2 decades alone have been so significantthat this Field may be considered the Science of 21st Century.

Sample Advances:

Human Genome Mapped

Recombinant DNA Technology

e.g. Improve vaccine development for viruses

Polymerase Chain Reaction

DNA Map to define Pathogen Strain as

Native, Foreign or ‘Evolved again’

Gene Microarray to ID DNA in Play

Some Discoveries Some Discoveries –– Not Quite as Imagined Not Quite as Imagined

These Technologies are remarkable additions to Biological Scienceand Food Animal production. Viral strain ID, Viral vaccine and Drugproduction are among the most welcomeoutcomes. However, some Discoverieswere not as Imagined.

Ex. Human Gene ID MapHuman Gene ID MapExpected to be much smarter IF . . . Map.In Reality, do not know that much more

because Gene Outcomes are all about the Interactions (Gene networks, ‘Environment’)

Vast Obesity GeneVast Obesity Geness NetworkNetwork

Science is Science is NotNot Always Applied Correctly Always Applied CorrectlyNuances are Nuances are NotNot Always Known Always Known –– Sometimes Sometimes IgnoredIgnored

Practical Studies are important to expose short-comings in how weare attempting to apply Science. Some of these are discussed inthis Paper because what we Learned was so remarkable.3 Examples –

Early Wean Technology (immune ontogeny, epigenetic nuance)

Increasing Littersize while Ignoring other Physiological ImperativesRobustness is Huge. Its Proof must be in the Field and routine

monitored (nature of gene expression determined by Environment)

The Everyday Practice of Science The Everyday Practice of Science ––Cognitive Prejudice is Cognitive Prejudice is LethalLethal to Correct Application of Science to Correct Application of Science

Common Disease among Researchers isCognitive Prejudice.

It is easy to be a bad decision-maker. Best way to make unbiased decisions is to rely heavily on Data.

Bias can cause Scientists to cling toConcepts despite Contrary evidence.

Dr. Frederick Grinnell Dr. Frederick Grinnell –– ‘‘Where IntuitionWhere Intuitionandand

Passion Passion meetmeet Objectivity and Logic Objectivity and Logic’’

The Everyday Practice of Science The Everyday Practice of Science ––Research Often Throws a Research Often Throws a CurveCurve BallBall into Scientific Theories into Scientific Theories

Discovery is a matter of ‘Seeing what everybodySeeing what everybody

has seen and thinking what nobody has thoughthas seen and thinking what nobody has thought’’

Albert Szent-Gyorgi, 1937 Nobel Prize in Physiology.

A Fortuitous Curve Ball –Our Best findings have come when a Curve Ballappeared to Trash good Experiments.

Cabrera et al. 2002 is Classic Curve Ball Recipients of an Unexpected, Seminal Find. Discovered that E-W Technology hurts ADG, Viability and Loin depth (SeeSee p. 15, middle column p. 15, middle column)

(Blecha et al., 1983 timid proposal was correct) (immune ontogeny or epigenetic)

Szent-Gyorgi NIH Appt.

Role of Technical Professionals in Getting ScienceRole of Technical Professionals in Getting ScienceApplied CorrectlyApplied Correctly

State of Art FacilitiesResearch Method in the Field with EU

for Statistical SensitivityEnvironment where Technology will employ

Research Model is a powerful complement toAcademia; comes at a time when theirresources for Animal Research aredwindling.

We are in a Unique Position to assist in getting Science understoodand applied because we have Facilities and Financial means to Testprospective Technologies.

Getting Science Right by Doing Research WellGetting Science Right by Doing Research Well

Science in Practice –Impressive array of highly skilled Animal andVeterinary Scientists with Facilities that areUnparalleled by any Prior Era.

Research Imperatives – SeeSee Paper Paper

Competent Facilities – PersonnelCompetent Experimental Design (Familiar N-EQ)

Completeness in Variables Measured *Students Educated beyond their Main Interest

will make greater Contributions (e.g. Immunology, Molecular Genetics, Metabolism)

** Adverse Reactions to Food, Brit. Nutrition Foundation2002

Will We Will We AlwaysAlways Get Science Applied Right ? Get Science Applied Right ?

NO – Not at First !Science is so Complex and has so many Intricacies that it will continueto be an unfolding series of Discovery.

BUT –

Challenge the application of ‘isolated Science’ when proposedOutcomes are apt to have ‘unexpected’ down-sides.

e.g. Extreme Litter-size without coincident increases in Uterine

Capacity

Constraints that Most Limit Profit in N. AmericaConstraints that Most Limit Profit in N. America

Transition:Dr. Dunne was all about Diagnosis and Resolution of Problems.With this in mind, the 2nd half of this presentation involvesIdentification of Problems that most Constrain or Threaten Profit inNorth American Pig Operations.

Probe For Most Differentiating Factors toProbe For Most Differentiating Factors toProfit Profit AmongAmong Producers Producers

Performance Mean and Relative AdvantageMetric Unit AVG Top 25% ADV Rank OutcomePost-wean mortality % 9.5 6.8 1.290 1 No. pigsCulled at barn close % 2.8 2.1 1.253 2 No. pigsPre-wean mortality % 14.8 13.4 1.094 3 No. pigsMarket price $/100 Lb 52.2 56.1 1.075 4 PriceTotal finish cost $/100 Lb 49.0 45.9 1.064 5 CostWean pig cost $/Pig 27.8 26.4 1.049 6 CostFinish feed cost $/Ton 206.4 199.5 1.033 7 CostWeaned/mated sow Pigs 23.7 24.4 1.030 8 No. pigs

Caloric FCE, Finish Kcal ME/Lb 3874 3906 0.992 102 Cost

Agri-Stats Records summary for Live Production, n=68 Firms

Imperfect Tool

Pig Viability was most Important Differentiating Factor

Differentiating Factors ranked the same in Profit and Loss years (2,2)

Metric Required ∆ Unit Value Assumption

Full value weaned pigs 0.50 Pigs/litter Simplified using only wean pig cost

Wean pig cost 1.45 $/pig W-F mortality assumed, 6.0%

W-F mortality 1.00 % $75/Carcass Cwt

Finish feed cost 5.00 $/ton 2.83 FCE (2.60 FCE, $4.25/ton if W–F)

W-F FCE improvement 0.037 Feed : Gain $300/ton complete diet

W-F ADG improvement 0.15 lbs/d $38 per pig space

Carcass yield increase 0.70 % $75/Carcass Cwt

Carcass value 0.71 $/Carcass

Sow Turnover ? %

Probe for Opportunities to Advance Profit Probe for Opportunities to Advance Profit withinwithinOur System using Financial ModelOur System using Financial ModelRelative value of Factors was considered in an Internal Financial Model.Computed the amount a Metric would have to change in our System (Dec.

2011) to generate $1.50 Profit/pig.KEY Metric ID = (Deliverable KEY Metric ID = (Deliverable ∆∆) x (Value, $), ) x (Value, $), SeeSee Table 3 Table 3

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These Problems We Must Solve:These Problems We Must Solve:Problems that limit Profit in a significant and persistentProblems that limit Profit in a significant and persistentway for next 5-8 yrs.way for next 5-8 yrs.

•• Specific Evolving Specific Evolving DiseaseDisease (bullets 1-2 relate back to 2 prior slides(bullets 1-2 relate back to 2 prior slides

•• Mortality Non-SpecificMortality Non-Specific

•• Genome - Disease Genome - Disease Constrained FCEConstrained FCE

•• Sow Life-time ProductivitySow Life-time Productivity

•• An Emerging Problem An Emerging Problem ––

Extreme Extreme Litter-sizeLitter-size

These Problems We Must SolveThese Problems We Must Solve

1. Specific Evolving DiseaseSpecific Evolving Disease Diseases such as PRRS and SIV persist despite an Impressivearray of Research Tools and Personnel, who are searching for aSolution. Solution to an evolving Virus is so complex that it bringsto mind a statement by the late Dr. Laurence J. Peter –

‘‘Some problems are so complex that you have to beSome problems are so complex that you have to be

highly intelligent and well informed just to be undecidedhighly intelligent and well informed just to be undecided

about themabout them’’

These Problems We Must SolveThese Problems We Must Solve

2. Non-Specific MortalityNon-Specific Mortality Shown that the Top Firms are differentiating themselves by thisMetric (-29%). There are known differences in Viability (Robustness)among Sire Lines, but we expect this to be no different for the SowLine who composes 50% of the progeny.

Principle:Viability can only be tested under conditions of Moderate to High ImmuneStress. The Genome must be (1) challenged, and by a (2) variety of FieldPathogens to see how the animal is Programmed.Field Environments will tease out strengths and weaknesses that a LowImmune Stress environment will obscure.

These Problems We Must SolveThese Problems We Must Solve

2. Non-Specific MortalityNon-Specific Mortality Ex. Field Validation of Sire Line is routine. This Figure illustrates a howthe Progeny from a Maternal Line lived Post-wean (25 - 278 lbs).

N = 986 each Line SEM 0.77, P<0.001

Important FCE Technology in Important FCE Technology in ‘‘SuspensionSuspension’’

3. Genome Genome –– Disease Constrained FCE Disease Constrained FCE Most Important Nutritional means to improve FCE is the Pellet. HealthControl is essential because Pellets and poor Health can combine to causedeath in near biblical proportion.Q How Much FCE Opportunity when Health is not a Factor ?

Criterion Meal Pellet SEM Prob. P<No. Pens 89 89 - - - -Total No. Pigs Placed 1065 1086 - - - -Initial Weight, lbs 61.4 62.6 1.21 0.996End Weight, lbs 270 278 0.78 0.001Days on Feed 94.6 93.8 - - - -ADG, lbs/d 2.04 2.10 0.01 0.001ADFI, lbs/d 4.75 4.45 0.03 0.001FCE 2.72 2.50 0.01 0.001Mortality + Removal, % 2.70 3.20 1.05 0.161

N. Williams and co-workers, 2005

Classic Genetic x Environment InteractionClassic Genetic x Environment InteractionFigure 1 a. Low Immune Stress, (N=2839) (Full PCV-2 dose)NO better Illustration of the G x E Interaction than combining Pellets withInflammatory disease (environment). There is a Genetic basis to Pellet-related death and there is an unusual effect of Disease (SIV, MP, HPS).

Classic Genetic Classic Genetic x x Environment Environment InteractionInteractionFigure 1 b. High Immune Stress, (N=3162) (1/2 PCV-2 dose)Sire Line A served as the Control since previously proved Resilient to anImmune challenge. Performed true for greater Robustness than Line Bunder both levels of Immune Stress, but neither performed adequatelyunder High Immune Stress with Pellets.

These Problems We Must SolveThese Problems We Must Solve

4. Sow Life-time Productivity

Definition: Total Quality pigs weaned from Breed Eligible Exit.Problem: SLP is not a Metric that is commonly benchmarked.Problem illustrated by about 42% of Females have 19 or fewer pigs,which agrees with the concern of getting a young female thru 2reproductive cycles.Turnover ca. 50-60%.

Q What is a ReductionIn Replacement, 55% to45% worth ?

These Problems We Must SolveThese Problems We Must Solve

4. Sow Life-time Production (Retention, FVP weaned)

NPB Task Force operates within Animal Science Committee Objective: 30% turnover decline

4.6 parity exit (3.3-3.6 present)10-15 pigs/SL

3 Research Area’s . Gilt development – Young sow retention . Increase Quality Pigs weaned . Bioinformatics mechanism to benchmark 6 Projects Funded, 2011

These Problems We Must SolveThese Problems We Must Solve

5. An Emerging Problem An Emerging Problem –– Extreme Litter-size Extreme Litter-size

Frank Assessment –LS Science is not CompleteLittersize is Increasing butSmall Pigs are increasing3 Concerns –

More Small Pigs Litter Mortality Increase Disease Susceptibility ?

Unclear what level PSY Bornbecomes a Liability (continuum)

This Paper concludes with an emerging Concern – Extreme LS

The Problem of Extreme Litter-sizeThe Problem of Extreme Litter-size

Data collected on 6039 newborn pigs from Litter 1-7 sows.Linear decline, P<0.001. Y = -0.088 + 4.471

Unpublished internal study, 2001

I. Average Pig Birthweight Decline with Increasing LSI. Average Pig Birthweight Decline with Increasing LS

The Problem of Extreme Litter-sizeThe Problem of Extreme Litter-size

Birthweight on Pre-Wean Mortality and Life-time Full-value %Birthweight on Pre-Wean Mortality and Life-time Full-value %

Data from 434 Litters and 5039 Pigs from 2 Dam Lines, common Sire LineUnpublished Internal Memo, 2009

3. IUGR Program for Disease Susceptibility ?3. IUGR Program for Disease Susceptibility ?

Q Evidence for Fetal Programmed Disease Susceptibility ?

Fetal Programmed disease is supported by a significant body ofHuman and some Food Animal literature (sheep).Moderate to Dire IUGR of human Fetus was related to a myriad ofdiseases of Metabolic and Immunologic nature.

Fetal Origins of Adult Disease, Barker et al. 2002 – Int. J. Epidem.Developmental Origins of Adult Disease, Barker et al. 2004, J. Nutr.Foetal Programming of Immune Competence, Cronje, 2003, Aus. J.

Exp. Agri.Prenatal Programming . . . Health of Livestock. Bell, 2006 (P.

Greenwood IUGR Lamb hypophagia)

Biological Basis for Prenatal Programming of PostnatalPerformance in Pigs, Foxcroft et al. 2006, J. Anim. Sci.

The Problem of Litter-size The Problem of Litter-size andand Birth Size: Birth Size:EinsteinEinstein’’s Axiom for Mistaken Actionss Axiom for Mistaken Actions

Problem is that we do not know what PSY balance to strike with Litter-size. We do not know what the Financial Implication of more Small Pigsmay be. One can imagine some steps to minimize the weaning of ‘toomany’ small pigs but . . . This much is certain –

‘Problems cannot be solved at thesame level of awareness that

created them’ A. Einstein

Physiological Imperatives to LS TechnologyPhysiological Imperatives to LS TechnologyUterine Capacity increase to preventPlacenta Mass decline per Fetus

andMilk Production, Nipple No. and Nipple

placement

Meanwhile Meanwhile –– Progressively More Challenging Progressively More Challenging

Industrial Approach to 48 h Pig Care is not Suitable48 h Team to address Mortality

Humane Euthanasia

Nipple Structure (bend over)

Small Pig Litters Supplemented

Rescue decksUterine Capacity measure ?

(R. Johnson et al. 1999 concludes)

Returning to Where We Began Returning to Where We Began ––The Integration of Science into PracticeThe Integration of Science into Practice

Q What is the Take-home Message ?

Devolving Brainof:BoydLoulaConnorsHarrisBakerHenry

1

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Most Important Take-Home PointsMost Important Take-Home Points

Animal and Veterinary Scientists can be a PowerfulCombination in Applying Technology.

Gene Expression is all about the Interactions; among Genesand with the Environment.

Field Research is a must for this Reason.

Robustness is lacking in most modern Genotypes (Sow, Pigs).This is proven in Sow Replacement, Pig Viability and by ourinability to use a major FCE Technology (Pellets).

Litter-size increase that is not matched by increases in UterineCapacity is fast-becoming counter-productive.

FinaleFinale –– The Most Important Element of The Most Important Element ofCreativityCreativity

‘Seeing what everybody has seen but Thinking whatnobody has thought’

Albert Szent-Gyorgi

e.g. How many have seen Mount Rushmorefrom the Canadian side ?