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Data analysis of the mortality of cattle and sheep recorded in a sample of Australian saleyards

Published online by Cambridge University Press:  15 January 2026

Barbara Padalino*
Affiliation:
Department of Agricultural and Food Sciences, University of Bologna , 40127 Bologna, Italy Faculty of Science and Engineering, Southern Cross University , Lismore, NSW, Australia
Naod Thomas Masebo
Affiliation:
Department of Agricultural and Food Sciences, University of Bologna , 40127 Bologna, Italy
Maria Gaia Angeloni
Affiliation:
Department of Agricultural and Food Sciences, University of Bologna , 40127 Bologna, Italy
Clive Julian Christie Phillips
Affiliation:
Curtin University Sustainability Policy Institute , Kent St., Bentley, Western Australia 6102, Australia Institute of Veterinary Medicine and Animal Sciences, Estonian University of Life Sciences , Kreutzwaldi 1, 51006 Tartu, Estonia
*
Corresponding author: Barbara Padalino; Emails: barbara.padalino@unibo.it; barbara.padalino@scu.edu.au
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Abstract

In Australia, nearly twenty million cattle and sheep pass through saleyards annually, with potentially significant impacts on their welfare. This study documented the mortality rate occurring from January 2021 to December 2024 at a sample of saleyards of cattle and sheep in New South Wales, Australia, and identified possible risk factors. A database of the number of animals sold and deceased, either on arrival or while contained at each saleyard on each sale day, was created from the National Livestock Identification System. Descriptive statistics, and uni- and multivariable linear regression were used to examine risk factors for mortality. The mean sale mortality rates were 0.016 and 0.096% for cattle and sheep, respectively. In the univariate model, cattle sale mortality rate was associated with the maximum daily temperature, year, size of saleyard, and saleyard location, while minimum daily temperature, region, and saleyard location were associated with sale mortality of sheep. In the multivariable model, size of saleyard, saleyard location, month and year were significant predictors for the cattle mortality rate, while saleyard location and minimum daily temperature remained significant predictors of sheep mortality rate. Furthermore, sale mortality rate was eight times higher in sheep than in cattle, and sheep mortality was higher than values reported in the literature for farms. Further studies investigating the cause of death, journey conditions, and management practices of saleyards are recommended.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2026. Published by Cambridge University Press on behalf of The Universities Federation for Animal Welfare
Figure 0

Table 1. Name, definition, type and role of variables included in the regression analysis of cattle sale mortality rates

Figure 1

Figure 1. Mean sale mortality rate (%) for cattle registered in the National Livestock Identification System from 2021 to 2024 at all saleyards in NSW (Australia) stratified by (a) region, (b) year, (c) season, (d) size of saleyard, and (e) month. Error bars indicate standard deviation (SD).

Figure 2

Table 2. Univariable linear regression models assessing the association between cattle sale mortality rate and the variables: maximum daily temperature, year, month, season, and size of saleyard

Figure 3

Table 3. Multivariable linear regression model results for the outcome variable cattle sale mortality rate

Figure 4

Figure 2. Mean sale mortality rate (%) of sheep registered in the National Livestock Identification System from 2021 to 2024 at four saleyards in NSW (Australia) stratified by (a) region, (b) year, (c) season, (d) size of saleyard, and (e) month. Error bars indicate standard deviation (SD).

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