CQUni agtech tested for Argentinean farming systems
Published:07 August 2019
CQUni DataMuster reps Michael Thomson and Professor Dave Swain pictured in Argentina
CQUniversity researchers are investigating Argentinean beef production systems with a view to opening markets for emerging agtech company, DataMuster.
The DataMuster automated livestock management system, which has been developed by CQUniversity’s Precision Livestock Management team, will be evaluated on 15 farms and three Argentinean Government research stations as part of a project which commenced following meetings in Buenos Aires last week.
CQUniversity researcher and DataMuster inventor Professor Dave Swain said the project was designed to work with cattle producers to understand their business models and unique production systems in order to optimise DataMuster for future commercial delivery in Latin American markets.
“Australia is a world leader in developing agricultural technologies, which presents an opportunity not just to enhance livestock production in Australia, but also develop new export industries in farm hardware and software specifically designed for overseas markets,” Professor Swain said.
“And by working with industry partners overseas we will also gain new insights to improve our technologies to better support Australian producers in the future.”
The three-year project is supported by the Australian Government’s Global Innovation Linkage Program, through which CQUniversity will work with Argentina’s National Institute of Agri-technology (INTA) and producer group CREA to evaluate and enhance the DataMuster system.
DataMuster is a web-based management tool which allows cattle producers to automatically monitor and manage their herd right down to the individual animal level.
Using sophisticated animal behavioural algorithms, the system interprets data gathered from walk-over-weigh scales and electronic animal identification readers located at water troughs. Animals can also be managed remotely, with the software connecting to paddock-based auto-drafters to separate animals for sale, health treatments or supplementary nutrition.
“Rather than overwhelming producers with huge volumes of data, the system provides producers with the information they need to make more timely and more informed management decisions based on the animals’ growth rates, their need for supplementary nutrition, the maternal parentage of calves, and even the date which a calf is born,” Professor Swain said.
“By working with INTA, we will also be looking at integrating new data flows from their automated system for measuring the feed intake of individual animals in feedlots, and how this can be used for nutritional management and genetic selection here in Australia.”