Synchronisation and fixed time ai protocols for beef heifers


Results summary:

Of the 30 females synchronised in this study only 5 (1 in 6) were PD positive at the initial ultrasound examination at a stage of pregnancy consistent with the AI programme.  A further two animals were PD positive but at a stage consistent with the first cycle with the bull and natural service.  All 5 of these PD positive animals had been under the modified study programme (HE)-no controls had become pregnant to AI in the control group (RR).

Secondly, variation in progesterone levels was apparent at the stages of sampling.  This was expected at the initial sample, when females would be at any stage of the cycle, but test 2 (time of PG administration) was expected to show more animals at high progesterone and test 3 (time of insemination) more animals at low progesterone than was apparent.

Reasons for the poor levels of pregnancy could be numerous but the unusually inclement weather during the treatment and insemination period is likely to be influential. Along with many other herds in the region of the study, Schmallenberg virus (SBV) seroconversion was noted during late summer of 2012 which could have also been a contributing factor.


Planned activity:

  • Leaflet on AI for beef cattle
  • Articles in bulletin and e-newsletter
  • Briefing
  • Poster presentation/short communication at BCVA congress or similar
Beef & Lamb
Project code:
01 February 2012 - 31 December 2012
AHDB Beef & Lamb
Project leader:
RAFT Solutions Ltd



About this project

The Problem:

Artificial insemination (AI) represents an opportunity for improvement in the beef suckler herd. Bull genetics may be economically selected on EBVs targeted specifically to future breeding performance rather than inappropriate carcase traits associated with terminal sires. Use of breeding technologies represents an important opportunity for beef suckler herds to mitigate greenhouse gas emissions by improving productivity and efficiency (Chadwick et al 2007). Oestrus synchronisation protocols exist for fixed time AI (Penny 2005) but results can be disappointing when compared to natural service.


Project Aims:

This study aims to investigate opportunities to improve pregnancy rates using modifications of existing synchronisation and fixed time AI programmes.



This pilot study investigates the effect of equine chorionic gonadotrophin (eCG) &  human chorionic gonadotrophin (hCG) on performance of AI programmes in beef heifers as measured by blood progesterone assay and related to subsequent reproductive outcomes i.e. pregnancy success.