More than an ear tag

It started with a flexible, plastic ear tag.

It was 1955 in Palmerston North, New Zealand. Brian Murphy, a dairy farmer, and John Burford, an entrepreneur, came together to design an ear tag that could identify livestock more reliably and efficiently.

The partnership was the foundation of a business – Allflex Livestock Intelligence – that went on to use the latest technology in animal identification and monitoring for all types of animals, from cattle to fish to pets. Today, the company identifies more than 500 million animals a year with their tags.

The animal health business is challenged on many fronts. There is growing concern with ways to meet food demand for the world’s nine billion people by 2050. There is limited ability to grow herds and increase reliance on technology to bridge the gap between supply and demand to boost productivity.

There is an evolving public concern around food safety and traceability. There are issues surrounding disease control and eradication as well as preserving animal well-being and welfare.

Advanced identification techniques allow for producers to track a wealth of information that in turn helps producers learn more about their animals’ health.

More than 5.5 million cows are monitored with Allflex technology each day. It can classify and detect various actions and behaviors from early fertility to immediate health alerts. The detailed sensory information feeds a suite of machine learning algorithms that give farmers insights into their herd health.

The company’s animal identification business markets visual ear tags (VID), which contain printed identification numbers unique to the animal or the farm. The company also markets electronic identification (EID) tags, which hold RFID (radio-frequency identification) electronic components that have the ability to read information digitally. The shape and size of the tags can vary based on species.

The company also makes tissue sampling tags that capture DNA samples while tagging the animal.

Advanced monitoring tags in the form of both collars and ear tags provide heat detection, health reports and real-time alerts for individuals or groups of cows. The tags contain sensors and algorithms to capture insights on animal activity, feeding management, disease detection and animal behavior such as eating and grazing.

The company’s digital technology and predictive analytics business then analyzes the data, which is used by farmers to manage hundreds of millions of animals worldwide. By putting this data into the farmers’ hands, they can be prepared to safeguard their animals’ health, while reaching production goals.

The analytic tools provide value across the entire ecosystem, from farmers and artificial intelligence companies to government institutions, meat and dairy distributors, retailers and animal nutrition companies.

“We have the potential to improve productivity, enhance traceability, assist in disease prevention and provide for animal health and well-being accountability,” said Brian Bolton, chief executive officer of Antelliq, which is part of Merck Animal Health. “For us, it’s about the ability to combine the physiological understanding of the animal with the mathematical models, machine learning and artificial intelligence to make sense of all these data points that we collect.”

Allflex Young Stock is a new application for new born calves up to 6 months old. The light-weight ear tag monitors a calf’s behavior and health status to help farmers detect health issues such as respiratory disease and gastrointestinal issues before clinical symptoms appear.

SenseHub Beef Monitoring System checks heat, health and behavior of beef cattle. It lets farmers know if an animal is in distress or needs attention. It can monitor for the peak time for insemination or report difficult birth situations and post-natal health problems.

In 2020, Allflex Livestock Intelligence will celebrate its 65th year.

“Animal health intelligence is rapidly emerging as a high-growth sector within the animal health industry,” Bolton said.

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