‘Fit bits and calving cows – bringing together science and new technologies’
Photo: Anita Chang
Hi Fellow Animal Enthusiasts!
Many of us know that farming in northern Australia has it’s challenges. Remoteness, heat and flies, rough and often uncharted terrains, and dangerous feral animals just to name a few! Despite the challenges, farmers in northern Australia produce 64% of Australia’s total beef herd (ABARES); however, northern beef producers lose a combined $54 million annually in calf losses, and the major cause is unknown.
Researchers Anita Chang (PhD Student, Central Queensland University) and Tim Schatz (Principal Livestock Officer, NT Department of Primary Industry & Resources) have been doing some awesome science to help improve the productivity of northern beef systems through the use of technologies to monitor calving and calf loss.
On-animals technologies are already being used in Australia, largely in intensive dairy systems. They are generally in the form of collars or ear tags fitted with small accelerometers, GPS trackers and/or proximity loggers. A number of animal movements and behaviours can be identified with these technologies including (but not limited to) rumination, grazing, walking and resting and are distinguished from one another by their unique signal patterns. The question is, does the calving process or dystocia also have unique signal patterns? And can we adapt current technologies to monitor calving?
In preliminary studies using intensively housed black angus cows, Anita identified distinct signal patterns of calf-grooming and rumination that change during/immediately after calving. Anita also found that the initial calf grooming bout in a cow that gave birth to stillborn calf was over 15 minutes, whilst those that gave birth to live calves had grooming bouts averaging 2.5 minutes. Although interesting, only one animal in the study experienced calf loss so further research is warranted to classify the behaviour. Base algorithms developed in the preliminary study were tested on heifers in an extensive grazing system in Rockhampton QLD. There was a low sensitivity (79% accuracy, 67% sensitivity) for the measured behaviours, but GPS tracking of individual animals identified calving cows (96% accuracy, 78% sensitivity) based on their distance relative to the rest of the herd. Cows are pretty private when it comes to this ‘calving’ business.
Tim leads the CalfWatch project, which aims to develop a system to remotely monitor calving in extensive conditions and use it to investigate the causes of calf losses. Tim deployed 200 GPS collars and 200 vaginally-implanted birth sensors into cows in a study in Katherine NT. At the onset of calving, the sensor was expelled from the cow and activated, alerting them that the cow was calving, and the GPS allowed them to locate the cow to make observations. The birth sensors had an 85% success rate in alerting, but GPS collars were not always successful in locating the cow. But you could imagine a few cows were surprised to see Tim! Early indications are that accelerometers in the collars were also able to detect calving based on a change in movement patterns that was verified by the sensor alert. A new-improved GPS collar will be used in further trials to better locate the cows.
Both Anita and Tim’s research have shown that calving can be monitored using remote technologies and will help to identify causes of calf loss in northern beef systems. These technologies could also be applied on-farm to improve herd genetics via accurate calf birth date and subsequent growth rate. There is still a way to go in this space, including more studies and in more extensive systems but Anita and Tim are certainly paving the way!