The results confirm lameness is not just a management challenge — it is also heritable to a meaningful degree, indicating targeted breeding strategies could reduce it over time.
These new insights have been enabled through the use of large, consistent datasets collected via AI-based CattleEye video system, distributed globally by GEA.
For the first time, researchers have access to millions of objective, daily mobility assessments — a data volume and precision that traditional manual scoring systems could never economically provide.
Terry Canning, senior director at GEA and founder of CattleEye, said “we’re looking at breeding cows that simply don’t get lame as often”.
“This isn’t about treating lameness better or catching it earlier,” he said.
“It’s about creating herds where the problem largely doesn’t occur. That’s transformational — for both animal welfare and farm economics.”
New genetic traits in development
The findings presented at the World Dairy Expo highlight two potential new genetic traits currently under development:
- hoof health — based on lesion data collected by professional hoof trimmers.
- mobility — a novel trait derived from AI-generated mobility scores collected via CattleEye’s video analytics platform.
While the heritability of hoof disorders has been known for years, this study is the first to combine daily, objective mobility data at this scale with genomic information.
It opens the possibility to quantify the heritability of mobility itself — a direct measure of how smoothly an animal walks.
Preliminary analysis by the CDCB suggests heritability between 10 and 30 per cent, providing a strong foundation for breeding more resilient herds over time.
Maximilian Jacobi, senior director market and product management at GEA, said the combination of big data, artificial intelligence and genetics was transforming the understanding of animal health.
“Our customers see CattleEye not only as a diagnostic tool, but as a data platform that empowers them to actively breed for healthier, more durable herds,” he said.
A milestone for animal welfare, productivity and sustainability
Lameness remains one of the most significant economic and welfare challenges in dairy production worldwide.
Depending on region, herd size, lameness severity and management conditions, the annual costs for dairy farms can be substantial.
Beyond direct treatment costs, lameness affects milk yield, fertility and the lifespan of the animals.
Modelling studies and review articles suggest costs per affected cow average around $530 to $710 per year, with variations depending on country, housing system and disease prevalence.
From early detection to a sustainably healthy herd
The GEA CattleEye solution provides daily, objective mobility data that not only enables early detection, but can also serve as the foundation for genetic selection in the near future.
Javier Buchard, chief innovation officer at CDCB, said this collaborative research was a prime example of pairing existing information — hoof trimmer records, with novel insights and camera data — to address high-impact issues on dairy farms.
“Genetic solutions are a powerful tool to drive cumulative and permanent improvements in herd health, beyond environmental factors,” he said.
Within three to five years, farmers could select breeding stock with substantially lower lameness risk. Their daughters can potentially stay healthier, produce more milk, conceive faster and last longer in the herd.
By integrating CattleEye data into national breeding programs, the project is creating the first closed data loop between barn, science and breeding organisations. For dairy producers, this means:
- early detection of lameness through automated AI monitoring.
- genetic selection for cows with greater mobility resilience.
- healthier, longer-living herds that produce more milk and require fewer interventions.
“For our customers, this means lameness can not only be better managed — but that we can also make a genetic contribution to reducing it over time,” Mr Jacobi said.
“The project shows the added potential that emerges when AI, big data and genetics come together.”
The CDCB-UMN project began in July 2021 and is partly funded by the Foundation for Food and Agriculture Research.
