Use of a cow-side oestrus detection test for fertility management in Kenyan smallholder dairy herds.

Andrew Peters, Johanna T Wong, Erin Williams, Bridgit Muasa, Nathaniel F. Makoni, Chris M. Ngige, Fiona Allan, Michael Christian, Peter J.H. Ball

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Background: The use of artificial insemination (AI) has great potential to improve smallholder dairy herds in Africa, however high costs and often poor success rates have been discouraging. Effective AI requires accurate oestrus detection and the measurement of progesterone (P4) can be used to indicate oestrus as well as non-pregnancy. A cow-side progesterone lateral flow test, P4 Rapid, was evaluated as an aid to detect oestrus and non-pregnancy in Kenyan dairy cows, and assessed for association with AI efficiency. Methods: A total of 527 cows were enrolled in the study, from two counties in central and southern Kenya. Cattle in the test group (n = 308) were presented when suspected to be in oestrus and tested with the P4 Rapid (low P4 = oestrus, medium P4 = inconclusive, high P4 = not in oestrus/pregnant). Cattle with low P4 were inseminated. Cattle in the control group (n = 219) were inseminated when oestrus behaviour was detected i.e. standard practice. Results: Of the total P4 Rapid tests performed (n = 745), 1.5% were inconclusive, with the true accuracy of the test between 87-97%. Conception rates were not significantly higher in the test group (83.9%) compared to the control group (77.9%). Abortion rates were not significantly different between the control (9.5%) and test groups (8.2%). In the test group, 6.2% (19/308) cows showed a medium or high P4 level on day 0 and 9 of these were subsequently found to have been already pregnant. Conclusions: The data indicated that the P4 Rapid test can be a useful tool to assist farmer decision-making in the confirmation of correct timing for AI, and importantly may avoid unnecessary inseminations in pregnant animals, thus reducing the risk of AI-induced abortion.

Original languageEnglish
Article number12
Pages (from-to)1-16
JournalGates Open Research
Issue number12
Early online date14 Mar 2022
Publication statusE-pub ahead of print - 14 Mar 2022

Keywords / Materials (for Non-textual outputs)

  • Artificial insemination
  • Dairy cattle
  • Oestrus detection
  • Progesterone
  • Smallholder


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