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2 Jun 2021

VikingGenetics joins the Global Climate Task Force

The Danish Agriculture & Food Council launched the Global Climate Task Force and VikingGenetics is proud to be part of this effort to reduce carbon footprint globally. 

Denmark accounts for 0.1 percent of the world’s Carbon Dioxide (CO2) emissions, but to face the global climate challenges more cross-border efforts are required. In this context, the Danish Agriculture & Food Council launched the initiative called Global Climate Task Force with the participation of 10 solid companies from the Danish food cluster. 

The new group will develop concrete initiatives to minimize greenhouse gas emissions at a global level. 

“Denmark alone can´t bring a solution to the global warming, but VikingGenetics, as a large cooperative of dairy and beef producers, can share its knowledge on genetics to support other countries. We welcome this initiative and are happy to be part of it” Niels Bo as an interim CEO at VikingGenetics, says.

For many years, we have strived with success to breed healthy, efficient, trouble-free cows, and we have also invested heavily in better feed efficiency to have a more sustainable milk- and beef production”, he adds. 

The most important part of the future work of the Global Climate Task Force will be to identify how the Danish food cluster can be part of the solution to the global climate challenge. 

Best practices to share with the world

VikingGenetics can make an important contribution, as its exports of sustainable genetics for cattle breeding goes to more than 50 countries, many of them developing countries where resources to reduce greenhouse gases are still minimal. 

“VikingGenetics is one of the leading companies in the industry that strive and invest heavily to reduce the carbon footprint from cattle breeding”, Chief Sales and Marketing Officer, David Stenkær Ravnkilde, says. 

“For us, it makes a lot of sense to be part of the solution and contribute with our know-how to this important effort. A dairy farmer in India can, for example, reduce methane emissions by 33% per liter milk if they are using our genetics”, he adds.  

State-of-the-art artificial intelligence

Research regarding greenhouse gases indicates that, on average, 6% of the energy that a cow eats is spent on producing methane. However, this varies from 2-12% depending on how efficient the cow is in converting feed into milk.

VikingGenetics has developed a system based on artificial intelligence where the feed intake of individual cows can be monitored by 3D cameras in barns. Today we know the composition of the feed, but so far it has only been possible to measure the amount of feed that each cow consumes on experimental farms with expensive equipment. Analyses of the data collected on cows’ weight, feed intake and milk production will contribute to identifying which cows have the most efficient energy intake.


Saving feed and cutting greenhouse gas emissions

“The difference between the most and least efficient animals has been shown to be a substantial one tonne of dry matter intake per 305-day lactation for animals giving the same amount of milk. This offers enormous scope for saving feed and cutting greenhouse gas emissions – which broadly increase in line with feed consumed – if rolled out on a global basis.” Ends David Ravnkilde.

SDG´s always in focus 


By being part of the Global Climate Task Force, VikingGenetics is also accomplishing its commitment to the Sustainable Development Goals (SDGs). 

Goal #12 – Ensure sustainable consumption and production, where we commit to making fundamental changes in the way that our societies produce and consume goods and services.  

Goal #13 – Climate Action, referred to take urgent action to combat climate change and its impacts. 

Read more about the Global Climate Task Force here:

Read more about the SDG´s goals here:


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For further information, please contact:

David Stenkær Ravnkilde, CSMO - Chief Sales and Marketing Officer | T: +45 8795 9400 Email:

Verónica Löfgren, Content and PR | T:  +46 511 267 00 | Email: