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SCR1 (7-08)

Sire conception rate:
New national AI bull fertility evaluation

H.D. Norman, J.L. Hutchison, and J.R. Wright
Animal Improvement Programs Laboratory, ARS-USDA, Beltsville, MD 20705-2350
301-504-8334 (voice) ~ 301-504-8092 (fax) ~ ~

Starting in August 2008, sire conception rate (SCR), a new and more accurate evaluation of the fertility of artificial-insemination (AI) service-sire fertility will be available to dairy producers from USDA. From 1986 to November 2005, bull fertility evaluations termed estimated relative conception rate (ERCR) were provided to the dairy industry by Dairy Records Management Systems (DRMS; Raleigh, NC). In May 2006, USDA's Animal Improvement Programs Laboratory assumed responsibility for phenotypic evaluation of U.S. bull fertility. As an initial step, ERCR evaluations were implemented without change in calculating methods.

Over the next 4 years, an intense research effort primarily by Dr. Melvin Kuhn was made to develop methods that would improve the accuracy of bull fertility evaluations as well as broaden the scope of the data used for those evaluations. Those studies can be roughly categorized into two approaches. First, factors were identified that were related to the bull that provided the unit of semen and that helped to improve the prediction of whether that unit of semen resulted in a pregnancy. Second, factors were identified that were related to the cow receiving the unit of semen and that distorted the fertility measure for the bull providing the semen (nuisance variables); those nuisance variables were removed to allow obtaining the best measure of the bull's success in impregnating the cow.

Which factors associated with
service sire contribute to SCR?
Which nuisance variables are
removed to improve SCR?
  • Inbreeding of the bull
  • Inbreeding of the embryo from the mating
  • Age of the bull
  • AI organization combined with year of the mating
  • Effect of the bull itself
  • Group effect of cow herd, year of mating, cow lactation number, and cow registry status
  • Month and year of mating combined with State in which mating occurred
  • Lactation number of the cow
  • Service number
  • Effect of having a short interval between matings
  • Age of the cow
  • Standardized milk yield of the cow
  • Effect of the cow (both permanent environmental and genetic)

Comparison of ERCR and SCR

Category ERCR SCR
Trait evaluated First service 70-day nonreturn rate Conception rate
Breeds evaluated Holstein, Jersey Ayrshire, Brown Swiss, Guernsey, Holstein, Jersey, Milking Shorthorn
Lactation numbers included All lactation numbers with 6th and above set to 6th 1st through 5th
Service numbers included 1st 1st through 7th
Bulls included AI, <12 years old AI (not inactive,) <13 years old
Minimum number of matings ≥300 first services ≥300 services in the last 4 years and ≥100 in the last year for Holsteins; somewhat fewer services for other breeds
Minimum number of herds None 10 for Holsteins and Jerseys, somewhat fewer for other breeds
Fertility expression Deviation from mean (nearest 1%) Deviation from mean (nearest 0.1%)
Base assigned Published bulls sum to 0 Published bulls sum to 0
Dairy records processing centers participating AgSource Cooperative Services, DRMS, Minnesota Dairy Herd Improvement Association AgriTech Analytics, AgSource Cooperative Services, DRMS

Interpretation of SCR

How SCR evaluations should be used remains largely unchanged from how ERCR evaluations were used. Technically, 70-day nonreturn rate and conception rate differ in that conception rate is based on confirmed pregnancy. However, the two traits are highly related when derived from the same cows. A bull with an SCR of 2.0% is expected to produce a conception rate of 32% in a herd that normally averages 30% and historically has used average CR bulls. The term “expected“ indicates what the results would be if based on extremely large numbers of matings. Obviously, a herd with only two inseminations to that bull could realize only a conception rate of 0, 50, or 100% for his matings.

Improved accuracy

The addition of more inseminations for calculation of SCR is one of the main reasons for the higher accuracy compared with ERCR. Not only are more services (2nd through 7th) being used from the same herds, which approximately tripled the data, but new large herds are now included, specifically from AgriTech Analytics (Visalia, CA). In addition to incorporating many desirable features of ERCR, SCR also includes a number of new benefits that have been shown to improve accuracy of predicting conception rate for an independent data set.

Additional resources