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Abstract

This project demonstrated how a combination of technologies can facilitate user-controlled data sharing and assigned data ownership to produce insights using real-world data from red meat supply chain partners. The aim of the project was to deliver a working example of how an integrated digital data platform can lead to better research, development and adoption outcomes. The project showcased to producers the potential for automated data flows to feed directly through to research algorithms, to help them make data driven decisions.
Six producers representing seven different Property Identification Codes (PICs) engaged with the project, signing up through AgriTrakka to share their data with data analysts from Charles Sturt University (CSU). The dataset used for analysis includes 3,231 unique cattle RFID tags from five properties and 45,313 individual weight records, with 2,197 cattle accessing an automated paddock weighing system during the data collection period.
The ‘AgriTrakka’ product now provides project participants with the ability to access and direct automated in-paddock weigh data, plus uploaded spreadsheet data from yard weights through to the project data storage. Algorithms developed within the project are now hosted on the Shaipup algorithm hosting platform and are undergoing refinement. Reports are being prepared for the producers who contributed to the project, providing them with feedback and insight on their data using the algorithms developed.
Original languageEnglish
Place of PublicationNorth Sydney, NSW
PublisherMeat and Livestock Australia
Commissioning bodyMeat and Livestock Australia
Number of pages42
Publication statusPublished - 29 May 2023

Grant Number

  • RM103677

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