P.PSH.0817 - Reducing mortality rates in beef and sheep enterprises
In-paddock walk-over-weighing (WoW) systems fitted with digital and thermal cameras will provide information of cattle live weight, growth rate, body condition and body temperature in near-real time.
| Project start date: | 19 June 2017 |
| Project end date: | 29 January 2023 |
| Publication date: | 07 May 2024 |
| Project status: | Completed |
| Livestock species: | Grain-fed Cattle, Grass-fed Cattle, Sheep, Lamb |
| Relevant regions: | National |
Summary
The purpose of this project is to reduce mortality rates of cattle and sheep using new technologies and prediction models for early warning and detection of the risk of mortality of individuals and groups. In-paddock walk-over-weighing (WoW) systems fitted with digital and thermal cameras will provide information of cattle live weight, growth rate, body condition and body temperature in near-real time from at least 8 different properties throughout Australia. This information together with data from weather and vegetation will be used by prediction models to predict the risk of mortality in near-real time. The project will increase the understanding of factors affecting cattle and sheep mortality, develop recommendations of best management practices, develop early warning systems of mortality risk and monitor the effect of management and environmental factors on mortality risk.
Objectives
The objective of this project is to identify early and automatically measured indicators of mortality and disease using remote monitoring systems, and developing prediction models of mortality risk.
Key findings
A real-time monitoring system of mortality risk (likelihood of animals to die) was developed based on automatically measured body condition score (BCS) predicted from live weight (LW) and LW loss measured with walk-over-weighing stations. The risk of breeder cow mortality increased during the dry season as animals lost LW (average 100 kg and up to 230 kg) and BCS. Mortality rate peaked at 8% at the end of the dry season depending on year due to factors such as rainfall patterns, feed supplementation, and weaning. This real-time monitoring system can include other factors such as disease prevalence, dog predation, or others.
Benefits to industry
The creation of predictive models to determine the risk or mortality in real-time will prove beneficial to industry by assisting in the development of best management practices. The use of walk-over-weighing systems can provide producers with real-time data on live-weight, growth rate, body condition and body temperature.
MLA action
An online summary for this research will be published on the MLA R&D reports page.
Future research
There is potential for further research in this area, and MLA will continue to engage in animal welfare research that is beneficial to industry.
More information
| Project manager: | Michael Laurence |
| Contact email: | reports@mla.com.au |
| Primary researcher: | University of Sydney |
