Transforming calf care with precision tech

By Andi Anderson

Precision livestock farming uses real-time monitoring technologies to manage animal health by tracking individual data and detecting changes. These technologies are particularly promising in calf care, offering innovative ways to improve disease detection and overall management.

Traditionally, recognizing early signs of illness, like a subtle ear droop or head tilt, required skilled observation. Now, combining sensors and machine learning can provide around-the-clock monitoring, acting as a "virtual caretaker" for calves. Such systems can identify illnesses like bovine respiratory disease (BRD), which affects about a third of dairy calves, and diarrhea, which impacts 21% of pre-weaned calves.

Technologies like automated feeding systems play a crucial role in calf care. These systems allow calves to consume milk in smaller, more frequent meals, similar to natural feeding. They also collect data such as drinking speed, the number of meals, and instances of refusal to drink—all indicators that change when a calf feels unwell. For instance, calves receiving three or more gallons of milk daily typically show altered feeding patterns about three days before clinical symptoms appear.

Activity sensors further enhance disease detection. Tri-axial accelerometers track movement, lying time, and play intensity, all of which shift when calves become ill. Individually housed calves often show increased lying time and reduced activity before diagnosis, while group-housed calves may exhibit more lying bouts due to changes in social behaviour. These metrics vary based on housing style and feeding practices, making machine learning essential for tailoring alerts to specific farm conditions.

Temperature monitoring technologies are another innovation. Sensors placed in the rumen, ear, or under the skin can detect changes in body temperature. While these tools may not match the accuracy of rectal thermometers, they can identify illness earlier. For instance, rumen boluses have been shown to detect fever 2.5 days before farm personnel notice symptoms.

The future lies in integrating these systems into a single platform that learns farm-specific patterns, enabling early and accurate disease detection. This technology holds great potential to revolutionize calf care and improve outcomes for dairy operations.

Photo Credit: gettyimages-ahavelaar