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 75-d veterinary-confirmed conception rate (CR) Source: AgriTech, Visalia, CA, 2003 −present

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

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

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

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

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

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

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

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

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

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

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

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

Relationship of R and 80% CI Inseminations R (%) 80% CI 200 43 ± 2.2 300 54 ± 2.0 500 66 ± 1.7 1,000 79 ± 1.3 2,000 88 ± 1.0 5,000 95 ± 0.7 10,000 97 ± 0.5 15,000 98 ± 0.4 20,000 99 ± 0.3

Proposed CI table Bull name SCR (%) R 80% CI A 1.6 99 1.3 to 1.9 B 0.8 98 0.4 to 1.2 C −0.4 90 −1.3 to 0.5 D 1.1 82 −0.2 to 2.4 E −3.8 77 −5.2 to −2.4 F 2.3 59 0.4 to 4.2

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

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

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%

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

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

Correlations of alternatives with full model Alternative model AI organization All A B C D E F No mating inbreeding 1.00 No service-sire No AI organization- insemination year 0.98 No service-sire age 0.95 0.94 0.93 0.92 Interpolated age 0.99

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

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

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

Bull correlations of SCR with later CR Model Bulls with 100 inseminations Bulls with 300 inseminations Full model 0.6213 0.6526 No mating inbreeding 0.6222 0.6536 No service-sire 0.6189 0.6497 No AI organization- insemination year 0.6179 0.6488 No service-sire age 0.6089 0.6326 Interpolated age 0.6238 0.6549

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

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

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

Herd CR (August 2008) Service-sire fertility Herd fertility Low Medium High 20.3 27.4 35.3 22.6 30.0 38.7 24.8 32.4 41.4 Difference 4.5 5.0 6.1

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

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

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)

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

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