NEW research, using sheep tags with sensors, may address weaknesses in the collection of pedigree and behavioural data in the livestock industry.
At the 2017 BestWool BestLamb conference in Bendigo recently, La Trobe University research and PhD candidate Rajneet Sohi said commercial sensor technology had successfully matched ewes with lambs, as well as monitor sheep behaviour, in a Victorian flock near Glenrowan from 2014 to 2016.
About 100 first-cross ewes and their lambs - from one to three weeks of age - were fitted with activity monitors equipped with Bluetooth technology attached to halters and collars respectively. After ten days, the sensor units data was analysed revealing maternal pedigree was established within the first 15 minutes of the ewes and lambs being dispatched with sensors, with 100 per cent accuracy.
Each sensor acted as a beacon and receiver, and scanned neighbouring beacons within a certain boundary every minute, while the beacon signalled its identification four times every second.
This sensor system uses proximity detection to determine maternal bond and lamb feeding behaviour.
The pedigree determined by Bluetooth was compared to the pedigree determined by DNA profiling and verification.
Maternal signals received during the night were significantly higher than the maternal signals received during the daylight period.
Three week old lambs received a significantly lower number of maternal signals during light period when compared to and two week-old lambs.
Mr Sohi said the results showed Bluetooth wireless networking was a fast and reliable method for determining maternal pedigree of lambs in extensive farming systems.
He said the research had the potential to develop a commercially viable cost effective tool to assess maternal pedigree of lambs, with an estimated cost of less than $5 a tag.
The sensors are now being used to monitor and collect a range of sheep behaviour data such as grazing, walking, rumination, proximity with other animals and radio positioning of individual animals in a paddock.
Mr Sohi said this behavioural information could ultimately be used to detect theft and predatory attacks, as well as help farm management applications such as better planning and improving reproductive efficiency, optimising feed and the health management of livestock.