PARTNER FEATURE ▶▶▶
Mastitis: How can data help in making the right decisions?
“Big data” is a concept that dairy farms can use to improve their decision making. Lorena Nodar, an expert on ruminant health and data analysis at HIPRA, explores this and the importance it has for preventing bovine mastitis.
BY PAULA VILLORIA, DVM, CORPORATE PRODUCT MANAGER MASTITIS, RUMI- NANTS BUSINESS UNIT, HIPRA
Why is it important to monitor data on dairy farms? Do people really do that? It is important in order to optimise decision making, to do it objectively without simply basing our decisions on intuition. A large amount of data is generated in dairy farming, relating to bulk-tank milk quality, sometimes individual milk quality, treatment and bovine mastitis monitoring, water and feed analysis and in some cases sensors (collars, tags and even tablets inserted into the rumen), but we do not always make the most of it.
Does it always have to be done in a complicated way? It does not have to be done in a complicated way. However, the production data for dairy farming are more complicated than those for a different production system, such as calf fat-
tening, as the data are longitudinal. In this production sys- tem, the same cow will have different samples over time, which makes the data and the format more complex.
Can/should any farm do it? Any farm or company can make use of their data and trans- form it into information that will help their decision making. The more animals and parameters that are studied, the more information it will be possible to obtain. Relatively simple studies, such as how to monitor a change that is made on a farm, can be key in the company’s strategy. A clear example of this is that when a vaccination plan is es- tablished, for example against bovine mastitis, it is essential to measure the benefit of the vaccination and to evaluate whether the objective that was set has been achieved.
What are the key parameters we should monitor on the farm to be able to make decisions regarding udder health? Some data are essential. We can highlight two types of data: Firstly, data that allow us to measure udder health (cases of clinical mastitis, bulk-tank somatic cell count [SCC], individual SCC, antibiotic treatments, milk production, etc); and second- ly, data about risk or protective factors that can affect udder health, such as vaccination, milking management, type of drying-off, bedding material, density, hygiene, type of milk- ing machine and operation of the machine. Nevertheless, it will always depend on the company. When- ever there is variability, it can be a risk factor. For example, while bedding material is important, if the same sort is al- ways used, there will be no variability and its impact cannot be studied.
Lorena Nodar is a veterinarian specialising in data analysis and udder health at HIPRA.
18 ▶ DAIRY GLOBAL | Volume 8, No. 1, 2021
How many years of historical data are necessary for decisions to be sufficiently well founded? Seasonality is a factor that causes variations in parameters such as milk production, SCC and clinical mastitis; therefore, having data from more than two years will help us to coun- teract its influence on the different udder health indicators.
PHOTO: HIPRA
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