Precision Pastoral Management Tools

Project Overview

The Precision Pastoral Management Tools (PPMT) project concluded in June 2017. It developed the Precision Pastoral Management System (PPMS) to integrate precision animal data with precision pasture data to match livestock performance to environmental conditions, leading to more productive and efficient pastoral management. The project also encouraged adoption of the systems and technologies to remote pastoral enterprises.

The PPMT project integrated remotely collected animal and pasture data into a management decision support system, which was commercialised. The research showed that individual animal performance is highly variable, although herd averages are positively correlated with the rainfall on enterprises with good land condition. Pastoralists described the value of the PPMS to their business, particularly when making decisions about reducing stocking rates. The availability of objective animal and pasture data was also identified by pastoralists as a significant development removing the ‘guess-work’ from important economic and business decisions.

Impact from this research were:

The PPMS improved decision-making on cattle stations by having greater understanding and control over the groundcover (feed) and stocking rate responsiveness. This resulted in:

• improved decision making and reduced costs of monitoring and evaluating land cover information
• better control over groundcover with ability to monitor trends and avoidance of unwanted conditions
• improved decision-making on animal condition, resulting in better liveweight and market price
• reduced operating costs and improved occupational health and safety from less physical monitoring of remote assets
• beef producers with more time to optimise their business performance.

Outputs from this research included:

• The major output of this project was the PPMS software that operates at a resolution, and on a geographic scale, that allows pastoralists to integrate precision animal data with precision spatial data to match livestock performance to environmental conditions, leading to more efficient pastoral enterprises.

Research results from this project were disseminated widely, with the project publishing 2 journal papers, presenting at 6 conferences and creating 18 other end-user publications.