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RESEARCH ARTICLE (Open Access)

Using Walk-over-Weighing technology for parturition date determination in beef cattle

Don Menzies A B , Kym P. Patison A , Nick J. Corbet A and Dave L. Swain A
+ Author Affiliations
- Author Affiliations

A CQUniversity, School of Health, Medical and Applied Sciences, Precision Livestock Management Research Group, Rockhampton, Qld 4702, Australia.

B Corresponding author. Email: d.menzies@cqu.edu.au

Animal Production Science 58(9) 1743-1750 https://doi.org/10.1071/AN16694
Submitted: 22 October 2016  Accepted: 16 March 2017   Published: 31 May 2017

Journal compilation © CSIRO 2018 Open Access CC BY-NC-ND

Abstract

The northern Australian beef industry is dominated by cow-calf operations where reproductive efficiency is a major profit driver. The postpartum anoestrus interval is a major contributor to an animal’s reproductive efficiency and is influenced by genetic selection. The genetic trait that measures an animal’s postpartum anoestrus interval is the days to calving estimated breeding value and a key requirement is knowledge of the cow’s calving date. Traditionally calving date is recorded using laborious and costly methods that are impeding the recording and hence the accuracy of genetic predictions for this trait by the northern Australian seedstock industry. The present experiment used Walk-over-Weighing technology to automatically record animal weights as cattle enter a restricted area where they access water. With the use of a novel method to accurately assess weights, the growth paths of cows were tracked from late gestation to post-calving. The calving date was visualised in the growth paths of most cows (78.3%) and a custom algorithm was able to automatically detect the calving date within 10 days of the observed calving period for 63% of cows. The use of Walk-over-Weighing to record calving date provides the opportunity to increase the recording of the days to calving estimated breeding value in the northern seedstock industry, thereby increasing reproductive efficiency and improving the profitability of northern beef producers.

Additional keywords: autonomous data collection, calving, reproductive efficiency.


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