2005 paul vanraden animal improvement programs laboratory agricultural research service, usda,...

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200 5 Paul VanRaden Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD [email protected] An Example from Dairy An Example from Dairy Cattle Selection: The Cattle Selection: The Net Merit Index Net Merit Index

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Page 1: 2005 Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD paul@aipl.arsusda.gov An Example from Dairy

2005

Paul VanRadenPaul VanRaden

Animal Improvement Programs LaboratoryAgricultural Research Service, USDA, Beltsville, [email protected]

An Example from Dairy Cattle An Example from Dairy Cattle Selection: The Net Merit IndexSelection: The Net Merit Index

Page 2: 2005 Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD paul@aipl.arsusda.gov An Example from Dairy

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The Old Way of Selecting CattleThe Old Way of Selecting Cattle

Page 3: 2005 Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD paul@aipl.arsusda.gov An Example from Dairy

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ObjectivesObjectives

Document USA Net Merit index

Compare national selection indexes for dairy cattle

Discuss traits that affect profit and direction of selection

Outline approach for estimating economic values

Page 4: 2005 Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD paul@aipl.arsusda.gov An Example from Dairy

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Selection TheorySelection Theory

Progress = accuracy intensity genetic SD / generation interval

Multiply above by directional lossAccuracy = Corr (EBV, BV)

Directional loss = Corr (e EBV, a EBV)

Estimated (e) vs. actual (a) economic values

Direction may be the most important factor

Page 5: 2005 Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD paul@aipl.arsusda.gov An Example from Dairy

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Direction of SelectionDirection of SelectionTrait 1

Trait 2

Accuracy contours

Animalsselected

Page 6: 2005 Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD paul@aipl.arsusda.gov An Example from Dairy

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Trait Direction Not ClearTrait Direction Not Clear

Concentrated (less) or diluted (more) milk?

Large or small cows? Skinny or fat cows? Dairy or beef or dual purpose?

• Can change direction by replacing a population instead of selecting within

• Specialized populations can be useful

Page 7: 2005 Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD paul@aipl.arsusda.gov An Example from Dairy

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Coefficients of variation (CV)Coefficients of variation (CV)

TraitHerit-ability

CV (%)Pheno- typic Genetic

Stature .42 3 2

Protein yield .30 13 7Longevity .08 54 16Fertility .04 65 13

Page 8: 2005 Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD paul@aipl.arsusda.gov An Example from Dairy

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Measures of accuracyMeasures of accuracyAverages for recently proven Holstein bullsAverages for recently proven Holstein bulls

TraitACC rBV,EBV

REL r2

EBV,BV

BIF ACC 1 - 1-r2

Protein yield .92 .85 .61SCS (mastitis) .77 .59 .36Productive life .78 .61 .38Cow fertility .75 .56 .34Calving Ease .85 .72 .47

Page 9: 2005 Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD paul@aipl.arsusda.gov An Example from Dairy

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Relative EmphasisRelative Emphasis

Easily compare selection goals independent of trait units• Trait economic value times genetic SD• Divide by the sum across all traits• Multiply by 100

Expresses relative emphasis as percent of total selection• Added traits decrease emphasis on others• Convenient way to display indexes

Page 10: 2005 Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD paul@aipl.arsusda.gov An Example from Dairy

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History of USDA economic indexesHistory of USDA economic indexes(PD$, MFP$, CY$, and NM$)(PD$, MFP$, CY$, and NM$)

and Holstein Association TPIand Holstein Association TPIYear Introduced and Index Name

1971 1976 1977 1980 1984 1987 1989 1992 1994 1997 2000 2000Trait PD$ TPI MFP$ TPI CY$ TPI TPI TPI NM$ TPI TPI NM$

Protein 27 53 40 34 50 43 50 41 36Fat 48 46 45 40 34 17 25 17 16 21

Milk 52 60 27 60 -2 6 5

% Fat 20

Longevity 20 13 14

SCS 6 1 9

Udder 17 17 11 9 7

Feet / legs 5 5 4

Size -4

Final Score 40 20 20 17 17 17 14

Page 11: 2005 Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD paul@aipl.arsusda.gov An Example from Dairy

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Current National Selection Indexes:Current National Selection Indexes:Yield and Health TraitsYield and Health Traits

Country (Interbull Code)

USA DEU FRA NZL NLD CAN GBR AUS ITA DNK SWE

% of Interbull Population 17.4 15.3 12.3 10.6 9.3 4.7 4.7 4.5 4.3 4.1 1.5

Index Name NM$ TPI RZG ISU BW DPS LPI PLI APR PFT S – I TMI

TraitProtein 33 32 36 35 34 32 31 57 36 42 21 21

Fat 22 18 9 10 13 7 20 11 12 12 10 4

Milk -17 -12 -19 -20 -3 -4

% Protein 4 2 2 3

% Fat 1 2 1 2

Longevity 11 8 25 13 8 8 7 15 12 8 6 6

SCS / mastitis 9 5 5 13 14 3 7 10 15 12

Fertility 7 5 2 13 10 10 5 9 10

Other diseases 2 3

Page 12: 2005 Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD paul@aipl.arsusda.gov An Example from Dairy

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Current National Selection Indexes:Current National Selection Indexes:Conformation and Management TraitsConformation and Management Traits

Country (Interbull Code)

USA DEU FRA NZL NLD CAN GBR AUS ITA DNK SWE

% of Interbull Population 17.4 15.3 12.3 10.6 9.3 4.7 4.7 4.5 4.3 4.1 1.5

Index Name NM$ TPI RZG ISU BW DPS LPI PLI APR PFT S – I TMI

TraitUdder traits 7 10 6 8 16 13 9 12

Feet / legs 4 5 4 1 5 11 6 5 9

Size -3 2 2 -18 -5 4 -4 2

Dairy character -2 2

Rump 1 1

Final score 13 4 2

Calving ease 4 2 4 7 6 12

Growth / meat 4 6

Milking Speed <1 4 6

Temperament 5 2 3

Page 13: 2005 Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD paul@aipl.arsusda.gov An Example from Dairy

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Milk Pricing and Feed CostMilk Pricing and Feed Cost($ per pound)($ per pound)

Index Milk Fat Protein

Fluid Merit .051 1.30 1.00

Net Merit .012 1.30 2.30

Cheese Merit -.009 1.30 3.00

Feed Cost -.012 -.35 -.50

Page 14: 2005 Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD paul@aipl.arsusda.gov An Example from Dairy

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Value of Cow FertilityValue of Cow Fertility

Daughter pregnancy rate (DPR)• Pregnancies achieved per 21-day cycle• 1% higher DPR = 4 fewer days open

Fertility expenses per day open• Heat detection ($20 / lact .005) = $.10• Semen ($15 / unit + $5 labor) *.025 = $.50• Pregnancy exam ($10 / exam)*.012 = $.12• Lactations too long or short = $.75

Relative value of DPR = 7% of total

Page 15: 2005 Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD paul@aipl.arsusda.gov An Example from Dairy

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Value of Calving EaseValue of Calving Ease

Daughter CE value / difficult birth• Veterinary, labor costs = $50• Calf death (20% prob) = $25• Cow deaths before 1st test (1% prob) = $15

Service sire CE also includes• Yield losses / lactation = $40• Fertility and longevity losses = $30

Relative values of each are 2% of total

Page 16: 2005 Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD paul@aipl.arsusda.gov An Example from Dairy

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Linear vs Non-linear ProfitLinear vs Non-linear ProfitCalculation of Net Merit $Calculation of Net Merit $

Non-linear profit = (income – expense per lactation) number of lactations + cull value – raising cost

Linear profit obtained by taking partial derivatives at trait means

Corr (linear, non-linear) = .999

Page 17: 2005 Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD paul@aipl.arsusda.gov An Example from Dairy

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LifetimeLifetime Net Merit Net Merit $$

Incomes and expenses estimated from yield traits, SCS, longevity, fertility, conformation, calving ease

Example: body size• Convert from visual scores to weight• Cull price - growth cost + lactations

(calves – maintenance) = $-1.28 / kg• Less beef = more profit to dairy farmer

Page 18: 2005 Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD paul@aipl.arsusda.gov An Example from Dairy

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Goals of Index CalculationGoals of Index Calculation

Give breeders the index they want• Breed association or AI committees• Emotional approach (TPI)

Give scientists the index they want• Add incomes, subtract expenses• Mathematical approach (NM$)

Future prices difficult to prove

Page 19: 2005 Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD paul@aipl.arsusda.gov An Example from Dairy

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Top Net Merit BullsTop Net Merit BullsMay 2005May 2005

Bull Cntry DtrsNM$ REL

Net Merit $

Pro-tein

O Man USA 230 93 729 57

Loe Martin NLD 166 74 657 79

Lombard DEU 93 70 655 73

Mascol DEU 98 68 645 59

Marion USA 56 76 613 74

S D Jordan NLD 120 76 595 61

Alton USA 97 82 585 55

Page 20: 2005 Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD paul@aipl.arsusda.gov An Example from Dairy

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Trait HarmonizationTrait HarmonizationMark, 2003 EAAP meetingMark, 2003 EAAP meeting

Trait

Coun-tries

Average corr.

Avg. cor w / USA

Protein 27 .87 .89

Stature 21 .89 .90

Fore Udder 21 .75 .79

SCS 20 .85 .86

Longevity 14 .59 .74

D. CalvEase 10 .83 .86

M. CalvEase 10 .58 .64

Page 21: 2005 Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD paul@aipl.arsusda.gov An Example from Dairy

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Paul’s Beef ExperiencePaul’s Beef Experience

Page 22: 2005 Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD paul@aipl.arsusda.gov An Example from Dairy

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Interbull Beef ProposalInterbull Beef Proposal

Provide international evaluations within ICAR subcommittee

Combine raw data files instead of national evaluations

Favorable responses received from many countries

Charolais, Limousin most likely

Page 23: 2005 Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD paul@aipl.arsusda.gov An Example from Dairy

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Conclusions - DairyConclusions - Dairy

Many traits in addition to yield contribute to dairy cattle profit

Longevity, fertility, health, and type traits get half of emphasis

Direction unclear for some traits

Indexes began in 1970’s and have improved rapidly in recent years

Page 24: 2005 Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD paul@aipl.arsusda.gov An Example from Dairy

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Conclusions - BeefConclusions - Beef

An official, published goal:• Stimulates economic research• Gives breeders direction

An overall index helps breeders:• Promote their own animals • Locate superior breeding stock• Compete to improve the breed