According to a recent University of Guelph study, how a heifer spends her time before calving may help predict how easily she adapts to a free-traffic automatic milking system (AMS). Researchers observed 22 first-lactation Holsteins from three weeks pre-calving through 23 days in milk to explore the relationship between daily behaviour and early robot-milking performance.
What They Found
Heifers were grouped as low-fetch (LF)—those that adapted quickly—and high-fetch (HF)—those that required frequent fetching.
Even before calving, HF heifers showed subtle differences:
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Longer total eating time but fewer feed-bin visits
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Slower feeding rate
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Slightly less daily rumination
After calving, these patterns continued:
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HF heifers made fewer voluntary AMS visits and fewer milkings per day
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They spent more time in the fetch pen
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Milk yield and feed efficiency were lower for HF cows, despite similar dry matter intake
Interestingly, lying time remained similar across both groups, suggesting cows preserved rest even while adjusting to robot routines.
Why It Matters
Understanding how pre-calving behaviour influences AMS adaptation could help producers identify at-risk heifers earlyand provide targeted support during the transition. Subtle pre-calving time-budget differences may serve as useful early indicators of how a cow will perform after calving.
Practical Takeaways
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Watch for red flags pre-calving: long eating sessions, few feed-bin visits, or lower rumination time
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Monitor AMS metrics early: low milking frequency (<3 milkings/day after week 1) or extended fetch-pen time
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Provide extra guidance: gentle robot training, consistent enticement feed, and calm handling in the first two weeks postpartum
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Support slower eaters: ensure bunk space and frequent feed push-ups to maintain intake
Key Takeaway
This University of Guelph study suggests that subtle pre-calving feeding and rumination patterns may predict which heifers will adapt easily—or struggle—on robots. By tracking time budgets before calving and AMS visits early postpartum, producers can identify animals that benefit from extra attention, helping improve efficiency, milk yield, and overall welfare.
