Led by Dr. Filippo Miglior of the Canadian Dairy Network and the University of Guelph, and Dr. Paul Stothard from the University of Alberta, one of Genome Alberta's LSARP projects aims to enhance the key genetic traits of feed efficiency and methane emissions in dairy cattle. Selecting for those qualities, however, means measuring genetic variation in them to optimize breeding values used in the selection process.
It’s a measurement that’s both difficult and expensive, which is where mid-infrared (MIR) spectroscopy and MIR spectral data come in.
Reaching the peaks
“Spectroscopy is a scientific measurement technique,” said project manager Mary De Pauw. “It measures light that is emitted, absorbed, or scattered by materials and can be used to study, identify and quantify those materials.”
As De Pauw explained, spectroscopy produces MIR spectral data, a range of peaks or ‘spectra’ that correlate with specific compounds, and the application of that data to the dairy industry has piqued the interest of researchers on this project.
“MIR spectra is used to quantify fat, protein and lactose content in milk, “said De Pauw. “These are quality control measures performed on all commercial dairy herds in Canada on a regular basis.”
Currently, those are the only dairy-related uses of the data, but that’s about to change.
Brave moo world
“Our hope is that we can apply MIR spectra in predicting feed efficiency and methane emissions. Compared to the current method of collecting phenotypes to predict these traits, MIR spectra technology is easier and less expensive.”
Best of all, milk MIR spectral data is already being collected.
Like milking a kicking cow by hand, however, getting to the prize is not without its challenges.
“Within milk MIR spectra there are thousands of peaks, so a lot of work goes into identifying what different peaks correspond to.”
Also, in order to use this MIR spectra for the purposes of the Genome Alberta project, researchers must increase the amount of data they compile from cows for which they already have phenotype information on feed efficiency and methane emissions. This will be done with research herds at the University of Alberta, University of Guelph and a commercial farm.
That will take time, but De Pauw considers it time well spent, as the more data they have, the more accurate their prediction equations will be. That’s good news for the dairy industry as a whole.
“If we can produce these prediction equations for feed efficiency, the information could be used by farmers on a day-to-day basis for herd management, and in breeding programs to increase genetic gain for feed efficiency and methane emission.”
Share the wealth…of information
Furthermore, all of their data and equations will be shared with their international partners: USDA in Maryland, the Victoria Government in Australia, Scotland’s Rural College (SRUC) in Edinburgh and Qualitas Centre from Switzerland.
“A lot of these countries have their own large initiatives working on feed efficiency, methane emissions and relative MIR spectra, so we can all benefit from each other in the process.”
In essence, milk MIR spectra represent a world of possibilities to De Pauw and the research team.
“If we can develop and apply it properly, MIR spectra can be a highly effective tool for improving prediction accuracy and reducing costs. The data is already being collected so we don’t have to create new pipelines; it just makes so much sense to take existing data and expand its use for the benefit of all.”
Besides, when you find a great tool for building a better dairy cow, why not milk it for all its worth?