Interview with Lorena Nodar, Spain Analytics & bovine mastitis: how can data help you to make the right decision?

You may already be familiar with the concept of “Big Data”, but did you know that dairy farms can also apply this concept to improve their decision-making? Lorena Nodar – expert on ruminants health and data analysis at HIPRA – explains here the keys to improve decision-making on dairy farming and the importance it has for preventing bovine mastitis.

Lorena Nodar is a veterinarian specialized in data analysis and Udder health at HIPRA.

1. 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 even sensors (collars, tags and even tablets
inserted into the rumen), but nevertheless we do not always make the most of them.

 

2. 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 fattening, as
the data are longitudinal. In this production system, the same cow will have different samples over time, which makes the data and the format more complex in themselves.

 

“It’s essential to measure the benefit of the vaccination and to evaluate whether the objective that was set has been achieved”

3. Can/should any farm do it?

Any farm or company can make use of their data and transform them 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 established, 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.

 

4. Which are the key parameters we should be monitoring in the farm to be able to make decisions regarding udder health?

There are some data that are ESSENTIAL. We can highlight two types of data:

  • Those that allow us to measure udder health (cases of clinical mastitis, bulk-tank SCC, individual SCC, antibiotic treatments, milk production…)
  • Those that can affect the above, such as risk or protective factors: vaccination, milking management, type of drying-off, bedding material, density, hygiene, type of milking machine, operation of the machine… these are all factors that can have an impact on udder health.

Nevertheless, it will always depend on the company. Whenever there is variability, it can be a risk factor. For example, whilst bedding material is important, if the same sort is always used, there will be no variability and its impact cannot be studied.

 

5. How many years’ 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 (Somatic Cell Count) and clinical mastitis, therefore having data from more than two years will help us to
counteract its influence on the different udder health indicators.

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