TotalDairy Seminar Set behavioural changes give warning of disease around calving

Dairy cows show specific changes in behaviour several weeks prior to calving which could be used as a way to predict and prevent different transition diseases, according to new research from Spain.

Speaking at the recent TotalDairy Seminar in Gloucestershire, Professor Sergio Calsagmiglia from The University of Barcelona, said he was "confident" that looking at behaviour and time budgets in the run up to calving could be a useful predictor of disease around calving. This could enable automated systems to be developed that would allow targeted treatment of at risk cows, which would lower costs and increase treatment success.

"I can tell at least 20 days in advance whether she will have a problem. A cow that will be sick will spend less time at the feed bunk, have less feed bunk visits, less standing/lying swaps, take less steps and lie down for longer," he said.

Pedometers and a specially designed feed fence that monitored feed bunk visits were used in the trial on a 1,500 cow dairy near Barcelona. It highlighted that cows that went on to develop metritis at caving showed a strong reduction in time in front of the feed bunk and less steps, three weeks prior to calving. Cows that developed retained foetal membranes also had reduced time at the feed bunk and increased standing times. The patterns in time budgets were shown to be unique, depending on the disease developed around calving (see table).

Another study also showed a similar behavioural link to periparturient disease. For example, you could tell one week in advance if a cow was going to develop subclinical ketosis.

Professor Calsagmiglia explained: "The number of visits and time at the feed bunk can tell you two weeks in advance if there there is a high chance of her getting subclinical ketosis."

With this experiment also showing that calving could be accurately predicted within two hours of the event using a pedometer, Professor Calsagmiglia said in the future the two parameters could be combined so that propylene glycol could be administered at exactly the right time, for example.

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