Strategies for maximizing cow comfort towards improved profitability

Dr. Jeffrey Bewley, the dairy housing and analytics specialist at animal nutrition company, Alltech, spoke at the Pacific Northwest Animal Nutrition conference in Boise, Idaho, USA in January 2019.


M² magazine listened in on his presentation and pulled out a summary of his talk. Dr. Bewley has extensive experience with dairy cows and has clear views on current technologies and how new technologies will develop in the future.


Dr. Bewley opened with his views on dairy farming technology and in particular, on precision dairy management technology and the opportunities it presents for the industry. He said he was excited by the technologies currently available, but more so, by the new technologies coming over the horizon.

However, he was realistic, sounding a note of caution saying, ”but it’s not all rainbows and flowers, there are some challenges”

For dairy farmers themselves and for their dairy advisers – they need to think about these technologies and how best they can master them to provide an economic advantage.

Dr. Bewley is well placed to debate the issues – he has 15 years experience in the area, both as an academic and in a “hands on” role with dairy farmers. He is involved in the development of existing technologies, in developing new technologies and in looking at both the economic and social effects on the industry of the adoption of the technologies.

Dr. Bewley acknowledged that the progressive dairy farms of to-day have a good handle on the routines which go with good performance and achievement. Cow nutrition is good, cow comfort is excellent, superior genetics are in use and genetic progress is being maintained. Diseases are well controlled, somatic cell counts are low and reproductive management is good.

Of course, not all farms meet the ideal standard, but in general, the farms that have survived the changes in the industry over the past 15 to 20 years, are well run. In summarizing the position he said, “the biology is sorted”.


Now, the challenge is around the data collected on farms and how the data are sorted and analyzed; and more importantly, the use made of the data in management decisions. Data is now collected by robots, drones, 3-D printers and sensors of various types.

Examining the data takes us into the areas of

  • Artificial intelligence
  • Block chain technology
  • Virtual reality
  • Augmented reality

In this regard, the dairy industry is not creating new technologies, rather it is adopting from other industries and molding to suit it’s own needs. For example, accelerometers (which measure movement in 3D), as used in mobile phones and fitbits, are used in the kit on use on dairy farms. In the dairy environment, we can measure, rumination, feeding time etc – and it’s available to our industry because the accelerometer is cheap, as cheap as US $1.

However, to gain the benefit, the industry needs to make use of the data as an aid to making useful management decisions. That is the challenge and it’s from here that the opportunities for farmers will emerge.


The technology enables us to measure and record the data for the same cow over time. It could be something in the milk, or a behaviour, or conformation or a physiological characteristic. The technology provides measurements for the individual cow.

It sits well with big herds, and essentially it takes us back to an earlier era, when, with smaller herds of say 65 cows, the farmer knew each cow individually. Now, with the new technologies, in herds of 650 or 6,500 cows or of whatever size, we can get information on each individual cow.

At the farm level, all farms have similar animals with similar equipment, facilities and labour etc, so the question is – how does a farmer gain an advantage over his neighbor. It’s a bit like the US mega-companies, like Netflix, Amazon, and the grocery chains – they use analytics to gain an advantage.

So, as we move forward, the top dairies will use the information to get a competitive advantage. It will no longer be sufficient to describe what has happened in the past, like how many cows have calves, or what is the conception rate, or what is the pregnancy rate, or the somatic cell count. All these are descriptive – we now need different information.

Milking robots use spectroscopy to assess milk passing in the line and provides data on fat, protein and lactose, amino acids, fatty acids and progesterone levels


Now we have to go further and look at techniques such as

Diagnostic analytics – looking at why did something happen
Predictive analytics – looking to identify what will happen in future
Prescriptive analytics – looking at what we can do to make it happen

Most experienced farmers can look at a cow and take in various features, like her body condition score or her locomotion, maybe not make a record, but nevertheless make the measurement.

Now, new technology enables us to measure and record all the cows, all of the time. This could be overwhelming – so much data. The secret to success is how we analyze and make use of the data. Data for the sake of data is not the issue. Data must be useful, interesting and we must be able to turn the data into something of

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