Use this URL to cite or link to this record in EThOS:
Title: Investigating the use of behavioural, accelerometer and heart rate measurements to predict calving in dairy cows
Author: Miedema, Johanna Mary
ISNI:       0000 0004 2728 7822
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 2010
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Please try the link below.
Access from Institution:
Calving is an essential event in dairy production, as lactation only begins after calving and cows must give birth at regular intervals in order to maintain milk production. Careful management is important during the weeks around calving as this is when dairy cows most frequently experience health problems. Experienced stockmen use judgements based on physical and behavioural changes in order to recognise when cows may be about to calve, and subsequently be available to offer assistance when required. With increasing herd sizes and large numbers of cows per stockman, individual attention is often difficult. An automated system that monitors behavioural or physiological changes before calving could potentially be used to predict the time of calving, and help improve supervision by farm staff. Data comprising two years of records from Langhill Farm were used to identify any variables which could be used for calving prediction or as risk factors for various calving problems. Records kept by stockmen detailing the signs of calving and time of observation were compared with quantitative behavioural data. Observations from video recordings were used to identify any consistent behavioural changes occurring the day before calving that could be used to predict the onset of calving. The frequencies of lying and tail raises proved to be the most useful indicators, as they showed consistent changes in the final six hours before calving. Differences between heifers and cows, and between those experiencing calving difficulties and those which did not, were also investigated. Differences between heifers and cows were shown which should be taken into account when predicting calving times. However, no early-warning signs of difficulties were identified for cows and heifers assisted with a calving jack. Cows were also fitted with collars containing accelerometers to investigate if features in tri-axial accelerometer data could be shown to correspond to specific behaviours. Some success was achieved in identifying eating behaviour and postural changes, demonstrating that there is potential for monitoring behaviour using this method. Weekly heart rate recordings were also taken to establish if there was a change in the heart rate or heart rate variability during the final six weeks of gestation. Changes were found but, although they were statistically significant, they were considered too subtle for any practical application. Consistent changes in behaviour were observed in the six hours before calving, some of which could be measured using accelerometers. These changes have the potential to be used as the basis of an automated monitoring system to predict calving.
Supervisor: Macrae, Alastair. ; Dwyer, Cathy. ; Cockram, Michael. Sponsor: ITI Techmedia
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: behaviour ; welfare ; parturition ; dairy cows