The use of walk over weigh to predict calving date in extensively managed beef herds

Title
The use of walk over weigh to predict calving date in extensively managed beef herds
Publication Date
2017
Author(s)
Aldridge, Michael N
( author )
OrcID: https://orcid.org/0000-0002-9033-3081
Email: maldrid3@une.edu.au
UNE Id une-id:maldrid3
Lee, Stephen J
Taylor, Julian D
Popplewell, Greg I
Job, Fergus R
Pitchford, Wayne S
Type of document
Journal Article
Language
en
Entity Type
Publication
Publisher
CSIRO Publishing
Place of publication
Australia
DOI
10.1071/an15172
UNE publication id
une:1959.11/59318
Abstract

Beef cattle reproductive rate in northern Australia is low and substantial effort is underway to make improvements. Collection of calf birth date to inform female reproductive rate data is often not practical. Therefore, there is a need to find alternative methods for collecting birth date data. The aim of the project was to trial an automated animal weighing technology (walk over weigh) to estimate calving date for cows in a northern breeding herd grazing in an extensive pasture system. Two-hundred and thirty-two Wagyu cows from a herd of 1195 with confirmed pregnancy tests were stocked in a paddock with a walk over weigh unit at the entry point of the water yard. Each calf born in the paddock was weighed, ear-tagged and a DNA sample collected. After processing, cleaning and smoothing the data, weight profiles of the 232 cows over a 119-day period were analysed. From the weight profiles and confirmed DNA parentage, 96 out of a possible 162 (59%) cows that calved had a correct calving date prediction. It is proposed that improvements in calving date prediction could be increased through engineering changes designed to slow cow movement over the walk over weigh unit. The trial demonstrated with the proposed changes that walk over weigh could be used to estimate calving date in extensive beef herds, with the expectation that this information could be used in genetic evaluation to improve reproductive rate in northern Australia.

Link
Citation
Animal Production Science, 57(3), p. 583-591
ISSN
1836-5787
1836-0939
Start page
583
End page
591

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