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N. Gengler 1,2 , G.R. Wiggans *,3 , J.R. Wright 3 , and T. Druet 1,2 1 Gembloux Agricultural University, Belgium 2 National Fund for Scientific Research, Brussels, Belgium 3 Agricultural Research Service, USDA, Beltsville, MD wiggans@aipl.arsusda.gov.
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N. Gengler1,2, G.R. Wiggans*,3, J.R. Wright3, and T. Druet1,2 1 Gembloux Agricultural University, Belgium 2 National Fund for Scientific Research, Brussels, Belgium 3 Agricultural Research Service, USDA, Beltsville, MD wiggans@aipl.arsusda.gov Simultaneous Accounting for Heterogeneity of (Co)Variance Components in Genetic Evaluation of Type Traits
USDA Type Evaluation • Breeds: • Ayrshire, Brown Swiss, Guernsey, Jersey, Milking Shorthorn, and Red & White • 15 Linear traits and Final Score • Multi-trait Model • Canonical Transformation • Estimation of missing values
Heterogeneity of (Co)Variance • Variance tends to decrease with increasing herd average final score • Changes in appraisal program over time can be a cause
Methods of HV Estimation • Holstein Association estimates phenotypic variance using combination • observed variance • predicted variance from model including • mean final score • registry status • number of appraisals for herd-classification date • Meuwissen proposed simultaneous estimation of variances and breeding values • expected to improve accuracy of both estimates
USDA HV Adjustment System • Apply Canonical transformation to linear traits • Prepare data for 2 models • score= herd-sire + herd-year-season-parity + parity-time_period-age + parity-time_period-stage • var= mean + parity-group_size + parity-herd_mean_final_score + parity-year-season + herd-year-month
Differences Between HV-Adjusted and Unadjusted Evaluations • Standard deviations & mean absolute values • increased as reliabilities increased to 80% • decreased slightly for reliabilities of > 90% • Mean differences largest for bulls • born from 1985 through 1994 • with lowest mean daughters final scores
Interbull Trend Validation for Jersey and Brown Swiss Type • Trend tests conducted for • Stature • Udder support • Comparison • first parity v. all parities • without recent years v. all data • Trend differences within tolerance
Benefits of HV Adjustment • Simultaneous estimation of BV & Variances possible • Requires substantially more computer time • Improves stability of Mendelian Sampling Variance over time • HV adjusted EBV enable more accurate selection decisions
HV Model Implementation Plans • Jersey - May 2001 • Other breeds planned for August 2002