Sire Conception Rate (SCR)
Sire Conception Rate (SCR) is the only measure of male fertility that is published by a third party (not an individual AI organisation) and that uses data from all the USA Dairy Records Processing Centres.
Using SCR Information
- In order to receive a Sire Conception Rate evaluation, a Holstein bull (proven or genomic) must have a minimum of 300 breeding’s in the past 48 months (with 100 in the last 12 months) in at least 10 herds. SCR evaluations are produced for other dairy breeds but they require a lower number of matings. Newly released proven sires and very young genomic bulls often don’t have an SCR figure for their first active proof period because of this requirement. This is no reflection on the fertility of those bulls – they simply do not have enough data to include in the calculation.
- The SCR evaluation model is complex and takes into account variables relating to herd, the environment, the fertility of the cow and numerous factors related to the fertility potential of the bull including: the age of the bull, the year the semen was used, the inbreeding percentage of the service sire and the resulting offspring.
- The breed average for Sire Conception Rate is 0 and SCR values are expressed as plus or minus deviations from that average.
- For example, a bull with a SCR value of +2.0 is expected to improve conception rates (CR) by 2% compared to an average sire. Sires ranking a point in either direction of zero are considered average.
- The Industry average for SCR in April 2021 is +0.14. Between the highest and lowest ranking sires in the population there is a difference of up to 12% in conception rate.
- There is an estimated value of £2 per point of SCR.
SCR Evaluation Model
- SCR data was first published in 2008. SCR evaluations are calculated by the Council for Dairy Cattle Breeding (CDCB), the same organization that is responsible for the official U.S. genetic and genomic evaluations.
- SCR evaluations utilize an extensive database with data on more than 57 million breedings. The size of the database contributes to the accuracy of this model.