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A National Sire Fertility Index

A National Sire Fertility Index. Bull fertility (phenotypic ranking). Estimated relative conception rate (ERCR) 70-day nonreturn rate (NRR) Source: DRMS, Raleigh, NC, 1986−2005 USDA, Beltsville, MD, 2006−present Western Bull Fertility Analysis

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A National Sire Fertility Index

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  1. A National Sire Fertility Index

  2. Bull fertility(phenotypic ranking) • Estimated relative conception rate (ERCR) • 70-day nonreturn rate (NRR) • Source: • DRMS, Raleigh, NC, 1986−2005 • USDA, Beltsville, MD, 2006−present • Western Bull Fertility Analysis • 75-d veterinary-confirmed conception rate (CR) • Source: AgriTech, Visalia, CA, 2003 −present

  3. Sire conception rate (SCR) • New USDA service-sire phenotypic fertility evaluation • Based on CR rather than NRR • More accurate • Inseminations from most of the United States • Services 1–7 (not just first) • Additional model effects included • Implemented August 2008

  4. Data included • Only AI inseminations with pregnancy status confirmation (success or failure) • Inseminations 1–7 for cows in lactations 1–5 • Lactation length at breeding limited to 30–365 DIM • Cow age of 2–15 yr • Standardized milk yield • >10,000 lb for Holsteins • >8,000 lb for Brown Swiss • >6,000 lb for all other breeds

  5. Data included (cont.) • Most recent 4 yr of breeding records • Inseminations ≥70 d before data submission deadline • 6 traditional U.S. dairy breeds • Ayrshire • Brown Swiss • Guernsey • Holstein • Jersey • Milking Shorthorn

  6. Data excluded • Embryo-transfer donors • Sexed semen • Heifers • Consecutive services within 10 d of each other • Only information from later service kept • Earlier service not considered when assigning subsequent service numbers for same lactation

  7. Data excluded (cont.) • Herd with ≥50% of milking cows without recorded breeding • Herd CR <10% or >90% • Service sire <0.8 yr old

  8. Data sources (August 2008) • 3 dairy records processing centers • AgriTech Analytics • AgSource Cooperative Service • DRMS • >99% of data • 46 States and Puerto Rico

  9. Development of SCR • 4-year research effort – primarily by Dr. Melvin Kuhn • Bull variables (expanded service-sire effect) • Cow (nuisance) variables

  10. Bull variables • Inbreeding • Service sire • Embryo • Bull age • AI organization combined with mating year • Bull

  11. Cow variables • Combined herd, mating year, cow parity, and cow registry status • Combined mating month, year, and State • Cow parity • Service number • Short interval between matings • Cow age • Cow standardized milk yield • Cow’s permanent environment • Cow’s genetics

  12. SCR model • Categorical effects • Individual parities for lactations 1–5 • State-year-month of insemination group • 6 standardized milk yield groups • Service number for inseminations 1–7 • Cow age • Herd-year-season-parity-registry status class • Covariate (linear regression) effects • Service-sire inbreeding coefficient • Mating inbreeding coefficients • Random effects • Service-sire age group • AI organization-insemination year group • Individual service sire • Cow’s genetic ability to conceive • Cow’s permanent environmental effect • Residual “The most complex model that I know of to evaluate animal performance” — Bennet Cassell, VPISU, 2008

  13. Variances • Service-sire age 0.00014 • AI organization-insemination year 0.00011 • Service sire 0.00054 • Cow 0.00294 • Cow’s permanent environment 0.00533 • Residual 0.19697

  14. SCR accuracy • Reliability (R) = n/(n + 260) • n = number of inseminations • Constant 260 derived by including all random effects in expanded service sire term • Confidence interval (CI) = • 0.02313 = true standard deviation • 1.282 = standard normal variate from normal distribution for an 80% CI

  15. Relationship of R and 80% CI

  16. Proposed CI table

  17. SCR release • Released 3 times a year in conjunction with USDA national genetic evaluations • January • April • August • Only AI bulls ≤15 yr old • Active AI • Progeny test

  18. SCR release (cont.) • Overall matings • Holstein ≥300 in ≥10 herds • Ayrshire, Brown Swiss, ≥200 in ≥5 herds Guernsey, Jersey • Milking Shorthorn ≥100 in ≥5 herds • Matings during current 12 mo • Holsteins, Jersey ≥100 • Ayrshires, Brown Swiss, ≥30 Guernsey • Milking Shorthorn ≥10

  19. Interpretation of SCR • Phenotypic predictor of bull fertility • Expressed as relative CR • Reported as a percentage • Average bull has SCR of 0.0% • Standard deviation for August 2008 SCR was 2.4%

  20. Examples • Bull with SCR of 3.0% expected to have 3% higher CR than average bull and 6% higher CR than bull with SCR of −3.0% • Bull with SCR of 2.0% expected to have CR of 32% in herd that normally averages 30% and historically has used bulls with average SCR

  21. Impact of individual effects • Individual effects sequentially removed from full model to test alternative models • Service-sire inbreeding • Mating inbreeding • Service-sire age • AI organization-insemination year • Each effect added back to the model and another effect removed

  22. Correlations of alternatives with full model

  23. Service-sire age effect • Greatest impact on SCR prediction across and within AI organization • Interpolated age expected to provide most consistent evaluations across time • Not intended for comparison of rankings at a common age • Provide more accurate representation of phenotypic value of CR for a bull’s semen at this point in his life

  24. Maximum absolute change • Individual bull • Comparison with January 2008 full-model evaluation Change • Alternative models (percentage units) • No AI organization-insemination year 2.2 • No service sire-age 1.9 • Interpolated age 0.9 • No service-sire inbreeding 0.8 • No mating inbreeding 0.2

  25. Prediction effectiveness • July 2006 Holstein SCR from alternative models • Average CR for later (July 2006 – January 2008) inseminations • Deviation of outcome for each later insemination from average for all inseminations in same herd-year-season • Herd fertility differences removed • ≥300 inseminations for each bull SCR and either ≥100 or ≥300 inseminations for later CR

  26. Bull correlations of SCR with later CR

  27. Optimal AI organization-insemination year • AI industry concern • NAAB code used to assign bulls to AI organization-insemination years • Not as effective in predicting future CR as assigning all bulls to most recent AI organization-year • Assigning bulls to AI organization-year just prior to most recent also of considerable value

  28. Optimal AI organization-year(cont.) • Additional studies applied multiple-regression methods • Prediction of future CR most improved by including 2 most recent AI organization-years • 60% weighting for most recent year • 40% weighting for previous year

  29. Herd fertility • Relationship between bull SCR and fertility of herds for which bull was service sire • Herd-years stratified into 3 equally sized groups by CR • ≤27.3% Low fertility • 27.4 to 33.9% Medium fertility • ≥34.0% High fertility • Bulls stratified into 3 equally sized groups by SCR • ≤−0.9% Low fertility • −0.8 to 1.0% Medium fertility • ≥1.1% High fertility

  30. Herd CR (August 2008)

  31. Conclusions • New SCR evaluation • Based on confirmed pregnancies • Measures phenotypic service-sire fertility • Expressed as a relative CR (average bull has SCR of 0.0%) • Standard deviation of 2.4% in August 2008

  32. Conclusions (cont.) • First official SCR evaluations released in August 2008 for active-AI and progeny-test bulls • Data from >80% of DHI herds that collect breeding information • Most States and Puerto Rico represented for 6 dairy breeds

  33. Conclusions(cont.) • SCR more accurate than ERCR because of data from 3 times more inseminations • More DHI herds (Western herds added) • Extra services (2–7)

  34. Female fertility evaluations • Genetic evaluations to be implemented in 2009 • Heifer conception rate (HCR) • Percentage of inseminated heifers that become pregnant at each service • Cow conception rate (CCR) • Percentage of inseminated cows that become pregnant at each service • Similar to reporting for daughter pregnancy rate (DPR) • Will be reported to Interbull

  35. Acknowledgments • Reproductive records supplied by AgriTech Analytics, AgSource Cooperative Service, and DRMS • Willingness of U.S. dairy producers to record their management data essential for continuation of effective fertility evaluation • Suggestions provided by the National Association of Animal Breeders’ Fertility Committee beneficial in development of SCR

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