Author: Kristine Piccart (ILVO) - September 4, 2017
The proportion of automatic milking systems (AMS) is continuously increasing throughout Europe. Robotic milking offers great advantages in terms of labour flexibility and data collection, but comes with a steep learning curve. One of the biggest challenges for farmers using AMS, is the high number of false mastitis alerts. So how can dairy farmers distinguish true from false alerts?
Automated mastitis detection systems generate a huge amount of data. But how do you handle this information, and what is the trigger to intervene?
Every commercial AMS model uses a different method to generate a mastitis alarm. The most frequently used factors for monitoring mastitis, however, are the electrical conductivity of milk and milk yield measurements. Both can be measured per quarter. Theoretically, visually inspecting every single mastitis alarm in the barn is the best option to detect clinical mastitis – but this would result in an impossible workload.
The first step in controlling mastitis on AMS farms, is checking the computer at least twice a day. The software will automatically generate “attention lists”, highlighting the cows that require the farmer’s attention. Still, not every cow on the attention list has mastitis, and not every cow with mastitis requires an antibiotic treatment.
Combining multiple variables (electrical properties, milk yield, color alerts, …) with the cow’s known history (days in lactation, milking interval, …) is essential for properly evaluating mastitis alerts. Cows that turn up more than once on the attention list should definitely be kept an eye on.
Quarter milk data gives even more insight into udder health. For instance, if the overall electrical conductivity in the milk is slightly elevated, you should evaluate each individual quarter. Does one particular quarter stand out? Then it might be worth stripping this quarter, looking for clots or other abnormalities.
While the AMS offers a huge amount of information, it’s still up to the dairy farmer to keep track of all confirmed mastitis cases. Farmers should also try to record all “suspicious” cases, meaning cows that generate mastitis alerts but do not show any clinical symptoms of mastitis. These cows might as well suffer from subclinical mastitis, which can later flare up and result in a serious, clinical case. A CMT-test could quickly clarify this issue.
Finally, common sense is indispensable. The more you look at the AMS data, the more you see.
This is an example taken from Fullwood’s Crystal herd management software (in Dutch). This particular cow is 384 days in lactation. The blue line represents her milk yield, while the red line represents the electrical conductivity of the milk throughout lactation. What do you think: does this cow require a check-up? Leave your thoughts in the comment section below.