Early Mastitis Detection in Robotic Milkers Reduces Antibiotic Use


It is usual to identify mastitis on farm by observing clots, or a raised temperature and hard quarter. Often somatic cellcounts are taken, but this is often historic information after laboratory analysis , and the data is an average of all 4 quarters of the cow.

Robotic milkers, such as the GEA monobox used at the SW dairy Development Centre, measure milk conductivity, temperature and colour from each quarter. (There is now also an option to install quarter somatic cellcount detection). Data is collected at each milking, and is analysed by comparing previous data from the same cow, alerting when there is a significant change in a specific quarter. This allows a much earlier diagnosis af mastitis, which gives allows for non antibiotic treatments – such as the application of udder linament, and increasing the frequency of milking – to effect a self-cure. If, in extreme cases, it is decided that the best course of action is to use intramammery antibiotics, the earlier detection can lead to higher cure rates.

This system is much more accurate as it takes quarter information, and algorithms compare to results from the individual cow, rather than generic averages. The real-time nature of the data means diagnosis is earlier which in turn leads to a reduction in antibiotic use, both from reducing the number of cows that need antibiotisc, and having better cure rates in those that do. There is also a finacial benefit with more milk per cow being sold off farm ( less “treated” milk, and less milk reduction due to sick cows)