Importance of Genetic Evaluation for Structure in the US Dairy Industry October 10, 2012 Sam Comstock, Ph.D.

Slides:



Advertisements
Similar presentations
Linear Ben Krahn Oregon State University Dairy Research Center.
Advertisements

John B. Cole Animal Genomics and Improvement Laboratory Agricultural Research Service, USDA Beltsville, MD Phenotypes.
John B. Cole* and Paul M. VanRaden Animal Genomics and Improvement Laboratory Agricultural Research Service, USDA Beltsville, MD
2003 George R. Wiggans Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD USDA Dairy Goat.
George R. Wiggans Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD Select Sires’
2012 ADSA-AMPA-ASAS-CSAS-WSASAS joint annual meeting (1)Norman Comparison of daughter performance of New Zealand and North American sires in US herds H.D.
 87 of the top 100 active proven TPI sires are descendants of Planet, O Man, Shottle and Goldwyn.  58 descendants of O Man  32 descendants of Shottle.
But who will be the next GREAT one?. USA Bull Proofs * Bulls are ranked based upon their DAUGHTER’S (progeny) production and physical characteristics.
2002 Curt Van Tassell Gene Evaluation and Mapping Laboratory and Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville,
December 2014 Proof Changes
2002 Paul M. VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD Selection of dairy.
2007 J. B. Cole 1,*, P. M. VanRaden 1, J. R. O'Connell 3, C. P. Van Tassell 1,2, T. S. Sonstegard 2, R. D. Schnabel 4, J. F. Taylor 4, and G. R. Wiggans.
George R. Wiggans Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD National Association.
Dairy Breeds and Selection
Dairy Industry: Selection OBJECTIVES By: Mr. Weaver Identify specific traits associated with making a decision regarding dairy cattle selection. Evaluate.
G. R. Wiggans*, L. L. M. Thornton*,1, R. R. Neitzel †, and N. Gengler ‡ * Animal Improvement Programs Laboratory, ARS, USDA, Beltsville, MD †
 PTA mobility was highly correlated with udder composite.  PTA mobility showed a moderate, positive correlation with production, productive life, and.
2002 ADSA 2002 (HDN-1) H.D. NORMAN* ( ), R.H. MILLER, P.M. V AN RADEN, and J.R. WRIGHT Animal Improvement Programs.
Norway (1) 2005 Status of Dairy Cattle Breeding in the United States Dr. H. Duane Norman Animal Improvement Programs Laboratory Agricultural Research Service,
John B. Cole* and Paul M. VanRaden Animal Genomics and Improvement Laboratory Agricultural Research Service, USDA Beltsville, MD
Semenzoo Italy Holstein HOLSTEIN BREED IN ITALY ( The past ) First holstein cattle has been imported from North America on 1930 Since 1930 to 1980.
2006 Paul VanRaden Animal Improvement Programs Laboratory, USDA Agricultural Research Service, Beltsville, MD, USA Fertility Trait.
2007 Paul VanRaden, Mel Tooker, Jan Wright, Chuanyu Sun, and Jana Hutchison Animal Improvement Programs Lab, Beltsville, MD National Association of Animal.
R. L. Powell Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD Historical.
H. Duane Norman Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD Missouri Dairy Summit.
G.R. Wiggans Animal Improvement Programs Laboratory Agricultural Research Service, USDA Beltsville, MD 2009 G.R. WiggansInner.
2002 George R. Wiggans Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD USDA Dairy Goat.
John B. Cole, Ph.D. Animal Improvement Programs Laboratory Agricultural Research Service, USDA Beltsville, MD, USA The U.S. genetic.
2006 Paul VanRaden, John Cole, and George Wiggans Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD
2005 Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD An Example from Dairy.
2005 Paul VanRaden Animal Improvement Programs Laboratory, USDA Agricultural Research Service, Beltsville, MD, USA Selection for.
Evaluating Longevity: 10 Years of Using Stayability EPD Larry Keenan Research & Special Projects Coordinator, RAAA.
Adjustment of selection index coefficients and polygenic variance to improve regressions and reliability of genomic evaluations P. M. VanRaden, J. R. Wright*,
Paul VanRaden and Melvin Tooker* Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD 2006.
Dairy Breeds and Selection. Dairy Breeds and Selection Overview Major Breeds of Dairy Cattle Dairy Terms and Definitions Parts of a Dairy Cow Dairy Traits.
2003 P.M. VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD Genetic Evaluations.
2006 Mid-Atlantic Dairy Grazing Conference, 2006 (1) Is There a Need for Different Genetics in Dairy Grazing Systems? H. D. Norman, J. R. Wright, R. L.
XX International Grassland Conference 2005 (1) 2005 Genetic Alternatives for Dairy Producers who Practise Grazing H. D. Norman, J. R. Wright, R. L. Powell.
7 th World Congr. Genet. Appl. Livest. Prod Selection of dairy cattle for lifetime profit Paul M. VanRaden Animal Improvement Programs Laboratory.
1 Dairy Cattle Production (95313, 95314) Topic 3: Characteristics of dairy cattle and dairy type traits.
H.D. Norman, J.R. Wright, and R.H. Miller Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD, USA
WiggansARS Big Data Computing Workshop (1) 2013 George R. Wiggans Animal Improvement Programs Laboratory Agricultural Research Service, USDA Beltsville,
Council on Dairy Cattle Breeding April 27, 2010 Interpretation of genomic breeding values from a unified, one-step national evaluation Research project.
Dairy Cattle Selection. Dairy Cattle Selection Overview Dairy Terms and Definitions Parts of a Dairy Cow Dairy Traits and Selection.
Introduction To Dairy Cattle Evaluation
2003 P.M. VanRaden* and M.E. Tooker Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD Definition.
H.D. Norman* J.R. Wright, P.M. VanRaden, and M.T. Kuhn Animal Improvement Programs Laboratory Agricultural.
Advanced Animal Breeding
2001 ADSA Indianapolis 2001 (1) Heterosis and Breed Differences for Yield and Somatic Cell Scores of US Dairy Cattle in the 1990’s. PAUL VANRADEN Animal.
H. Duane Norman Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD Dairy Cattle Reproductive.
2006 George R. Wiggans Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD USDA Genetic.
2007 Paul VanRaden Animal Improvement Programs Laboratory, USDA Agricultural Research Service, Beltsville, MD, USA 2007 Genetic evaluation.
CRI – Spanish update (1) 2010 Status of Dairy Cattle Breeding in the United States Dr. H. Duane Norman Animal Improvement Programs Laboratory Agricultural.
Using EPDs in Selection Edited by: Jessica Hawley & Brandon Freel Originally compiled by Colorado Agriscience Curriculum.
Meori Rosen Past, Present, and Future Dairy Cattle Breeding in Israel.
2001 ASAS/ADSA 2001 Conference (1) Simultaneous accounting for heterogeneity of (co)variance components in genetic evaluation of type traits N. Gengler.
Application of Genetic Markers to Dairy Cattle. Overview Traditional selection Genetic markers Granddaughter design Resource populations QTL identification.
Dairy Cattle Evaluation
Dairy Breeds and Selection. Objectives: n Major Breeds of Dairy Cattle n Dairy Terms and Definitions n Parts of a Dairy Cow n Dairy Traits and Selection.
2006 8th World Congress on Genetics Applied to Livestock Production (1) Trait Selection When Culling U.S. Holsteins H.D. Norman, J.L. Hutchison, J.R. Wright,
Fundamentals of the Eurostar evaluations
Net Merit Changes April 2017.
Dairy Selection: General Overview
How selection for better health impacts dairy profitability
USDA Dairy Goat Genetic Evaluation Program
Improving production efficiency through genetic selection
Update on Structure EPD Development R. L. Weaber, J. Bormann, N
Domestic vs. imported AI semen for Holstein graziers in the US
How selection for better health impacts dairy profitability
Principles of Dairy Cattle Breeding
Presentation transcript:

Importance of Genetic Evaluation for Structure in the US Dairy Industry October 10, 2012 Sam Comstock, Ph.D.

Linear Descriptive Traits Stature Strength Body Depth Dairy Form Rump Angle Thurl Position Rump Width

Linear Descriptive Traits Fore Udder Attachment Rear Udder Height Rear Udder Width Udder Cleft Udder Depth Front Teat Placement Rear Teat Placement

Linear Descriptive Traits Teat Length Udder Tilt Rear Legs, Side View Rear Legs, Rear View Foot Angle Body Condition

Linear Descriptive Traits Traits get recorded and reported individually

Linear Descriptive Traits Educational material provided to breeders Review regularly Research traits added as needed

Final Score An overall score Based on five major categories (“breakdowns”) –Front End and Body Capacity –Dairy Strength –Rump –Feet and Legs –Udder

Final Score Major Breakdowns 15% Front End and Body Capacity 20% Dairy Strength 5% Rump 20% Feet and Legs 40% Udder

The Classifiers Employees of Holstein Association –Full time –Trained (and refreshers) –Continually monitored / evaluated Rotated through regions No back-to-back on same farm Luck of the draw

Types of Classifications Sire Evaluation for Type (SET) –Young bull daughters compared to herdmates Whole herd –Or a number of variations for partial herd –Options affect which records are used in genetic evaluation

Handheld Computer Pre-loaded with –Herd Inventory –Animal ID –“Required” Animals –“Optional” Animals Record scores for linears and breakdowns Print results at farm Transmits to laptop to association

Genetic Evaluation Phenotypic traits get recorded individually Most get a genetic prediction Beef EPD == Dairy PTA Linear PTA converted to Standardized Transmitting Abilities (STA)

Genetic Evaluation Phenotypic traits get recorded individually Most get a genetic prediction Beef EPD == Dairy PTA Linear PTA converted to Standardized Transmitting Abilities (STA)

Genetic Evaluation Multi-trait evaluations Repeat measures Animal model Requires estimation of heritabilities and genetic correlations, and development of appropriate analytical models

Genetic Evaluation 13,000,000 Final Scored cows 8,000,000 Linear scored cows

Genetic Evaluation Using the results 18 conformation predictions per animal Linear prediction useful for corrective matings Final Score (PTAT) overall prediction

Genetic Evaluation Using the results 18 conformation predictions per animal Linear prediction useful for corrective matings Final Score (PTAT) overall prediction No breakdown predictions Composites, instead

Composite Predictions Feet and Legs Udder Dairy Capacity Body Size

Composite Predictions Feet and Legs (FA*.48 + RLRV*.37 - RLSV*.15)*.5 + (Feet & Legs Score)*.5 Udder UD *.35 + FU*.16 + UH*.16 + UW*.12 + UC*.09 + TP*.05 – RP*.07 Body Size ST*.5 + SR*.25 + BD*.15 + TW*.1 Dairy Capacity

Composite Predictions Allow weighted selection on functional traits without becoming overwhelmed in data

Total Performance Index Combines –Conformation (28%) –Production (43%) –Health & Fertility (29%)

TPI – Total Performance Index 45% emphasis on ProductionFat and Protein & part of PTAT 21% emphasis on Udder HealthSCS, UDC & part of PTAT 21% emphasis on Early BreedingDPR, PL & DF 8% emphasis on MobilityFLC & part of PTAT 3% emphasis on Calving AbilityDaughter Calving Ease & Stillbirth 2% emphasis on Body SizePart of PTAT

Net Merit $ Index Classical production function Uses Composite Conformation Traits –Udder –Feet and Legs –Body Size Detailed derivation online

Trait Selection Information overload

Trait Selection Information overload Economically relevant Use to form composite predictions Incorporate in selection indexes Use within mating programs