Scotland may be best known for bagpipes, but it’s the data derived from Scottish dairy cows that is music to the ears of genomic researchers. As it seeks to enhance feed efficiency and reduce methane emissions with the power of genomics, a Genome Alberta project is part of a global initiative. That effort includes a dairy research herd at Scotland’s Rural College (SRUC) Dairy Research Centre on the outskirts of Dumfries, South West Scotland, supported primarily by funding from the Scottish government.
The project aims to use milk mid-infrared (MIR) spectral data to estimate feed efficiency and methane emissions as the data correlates well with both traits. Compared to the current method of collecting phenotypes to predict these traits, MIR data is easier and less expensive.
Best of all, this data is already being collected. In order to use it for their purposes, however, researchers must increase the amount of data they compile from cows for which they already have phenotype information on the targeted traits.
As it turns out, the SRUC research herd fits the bill.
“We’ve been running 200 cows for 45 years now,” said Eileen Wall, Team Leader of Integrative Animal Sciences at SRUC.
“We phenotype the heck out of our research herd animals and follow them from birth through three lactations of production data, gathering weekly information on key aspects like feeding behavior and feed intake, including regular milk MIR profiles.”
Having gathered hundreds of thousands of rows of research phenotypes, Eileen and her team tie into a national evaluation system and obtain data on every milk-producing cow in the country. In collaboration with National Milk Records, they have collected MIR data on 1.5 million cows over the last year in what she calls a “really stunning example of the research community working with industry”, assisted by funding from the Innovate UK and BBSRC (British Biological Sciences Research Council).
One product of all this data is a powerful set of genetic prediction tools for traits of interest to dairy producers.
“Our dairy research herd serves as an excellent resource for reference phenotypes. The prediction tools developed to date were based on more than half a million records taken from over 900 Holstein Friesian cows from 2003 – 2014 on a range of phenotypes and dietary components. As we continue to collect records on farm and spectral data we can routinely update and improve tools as well as test and develop tools to predict new phenotypes.”
In turn, the Scottish results are helping the Efficient Dairy Genome Project develop a similar set of robust prediction equations using MIR data.
“Based on our experience, we can share information with the Canadian researchers and help them avoid any mistakes that we made along the way; so it’s a combination of pooled data and shared learning.”
Also, since North America and the U.K. have different production systems, pooling data should produce better genomic predictions for a wider range of cows and systems.
Motivating research in both Canada and the United Kingdom is the potential benefit for producers.
“Feed is the highest intake cost for dairy farmers. If we can increase the efficiency of milk production, it will help farmers save money and stay competitive. Right now our government is stressing the need for research to have real-life applications so that results don’t stay on paper but are translated to the field.”
For the U.K. dairy industry, reducing feed waste has the potential to cumulatively increase profitability by 17 million GBP (British pounds) per year. The hope is that Canada can realize similar benefits by making active selection decisions for critical traits. Who knows, maybe Canadian farmers will even don kilts as a show of solidarity.
Well, one step at a time.