Predicting Oestrus and Calving

Evaluating the prediction of oestrus and parturition from data generated by a remote telemetry activity meter, ruminal temperature bolus and heatmount detector

Project number:                    72607

Lead contractor:                   RAFT Solutions

Start & end date:                   01 December 2012 – 01 October 2013

Actual end date:                    10 April 2014

 

The Problem:

Activity meters are widely used in the dairy industry to identify females on oestrus amongst other uses.  Rumen temperature measured via a bolus has also been identified as a potential indicator of oestrus and parturition.  Both technologies have potential to improve the reproductive performance of suckler herds.  In particular, identifying females in oestrus is paramount to successful AI protocols that do not use synchronisation.  Predicting calving time is a major benefit for suckler producers in terms of saving labour spent checking cows around calving, particularly when there are only a few cows due to calve perhaps at the end of the calving season.

 

Aims and Objectives:

Project Aims:

This project aims to test the following hypothesis:

Increased movement in beef cows and heifers as detected by distance telemetry activity meters (Heatime) or changes in ruminal temperature (DVM Systems  boluses) can be used to:

(a) successfully predict oestrus and facilitate appropriate timing of artificial insemination in beef suckler herds.

(b) provide temperature data which can predict the timing of parturition and hence facilitate calving management and outcomes‘

Deliverables:

A farm event will be possible on each farm after completion of the project and this will be accompanied by press coverage and messages incorporated into briefings, bulletins and farmers events and materials.

 

Approach:

  • Two demonstration farms have been identified in Yorkshire.  One is a commercial lowland producer and the other is a pedigree upland suckler producer.
  • A ruminal bolus (DVM systems, Greeley, USA) will be inserted into each animal and an activity meter neck collar (Heatime) attached to each animal recruited to the study. The bolus and activity meters will both be used to predict each of parturition and oestrus.
  • The equipment will be compared against visual observations of oestrus using pressure heat mount detectors (Kamar).
  • Progesterone levels will be measured in blood or milk samples using Ridgeway Target‘ kits to determine oestrus,
  • Body condition score at calving, insemination & pregnancy diagnosis will be recorded

 

Results:

Key Messages

Prediction of oestrus was achieved relatively successfully using the activity collars on both farms, although issues around establishing a baseline level of activity were noted where cows are moved just prior to calving.  There were also power issues when the cattle were monitored outside at grass. Temperature monitoring showed some promise in cows that had been synchronised for AI but was less successful when oestrus occured naturally.

Major technical difficulties on one farm meant that the dataset for bolus measurements was much depleted.  Interference of the signal form a neighboring RAF base was blamed but the problems was never solved.

 

Results

Results were variable across farms and between cows.  Some cows tending to show increases in activity around calving and other showing no change.  Temperature monitoring around calving showed no distinct patterns, however it was noticed that read frequency reduced around the time of calving.

Prediction of oestrus was achieved relatively successfully using the activity collars on both farms, although issues around establishing a baseline level of activity were noted where cows are moved just prior to calving.  There were also power issues when the cattle were monitored outside at grass. Temperature monitoring showed some promise in cows that had been synchronised for AI but was less successful when oestrus occured naturally.