Mid-Infrared Methane Prediction and Production Traits: What It Means for Management

Measuring methane from an individual cow normally needs a respiration chamber, a sniffer in the feed bin or a head-hood system, none of which scales to a commercial herd. A newer idea is to estimate methane from something every herd on test already produces: the mid-infrared (MIR) spectrum of a milk sample. This article explains the approach, summarizes one large Holstein study, and sorts what is practical today from what is still research.

What a milk spectrum is

When a milk sample goes through a DHI lab, an instrument shines mid-infrared light through it and records how much is absorbed at many wavelengths. That pattern is how labs report fat, protein and lactose. The same spectrum carries information about the milk's fatty acid profile and other compounds, and some of those are linked to what happens in the rumen. Researchers build prediction equations by comparing spectra with methane measured in the same cows, then apply the equation to many cows that were never measured directly. If you are new to test-day records, our guide to reading a DHI record covers what comes off the lab.

Predicted is not measured

A predicted value is an estimate with error. It is useful for ranking animals across thousands of records but should not be treated as a precise reading for a single cow on a single day. The prediction equations in the study below were described as applicable in a window of roughly 70 to 200 days in milk, which is another reminder that they have boundaries.

What one large Holstein study found

In the Journal of Dairy Science in December 2024, Fresco, Boichard, Fritz and Martin published genetic parameters for methane traits predicted from milk MIR spectra throughout lactation in Holstein cows. The abstract is indexed at the Directory of Open Access Journals. According to that record:

• They predicted six methane traits: four methane production traits in grams per day, one methane intensity trait (grams per kilogram of fat- and protein-corrected milk) and one methane yield trait (grams per kilogram of dry matter intake).
• The models used 829,025 spectra from 167,514 first- and second-parity Holstein cows collected between January 2013 and February 2023.
• Average heritability across the six traits ranged from 0.24 to 0.45, so selection on them could in principle make progress.
• The traits were genetically stable within and between lactations, with average genetic correlations of 0.93 to 0.98 within a lactation.
• The traits were not interchangeable: pairwise genetic correlations ranged from negative 0.15 to 0.77.
• Two of the production measures and the intensity trait did not show antagonistic genetic correlations with milk yield, fat and protein content or somatic cell score. The authors suggest they could likely be included in breeding goals with limited impact on those traits.

How to read that result

Three things are worth stressing. First, methane production in grams per day and methane intensity per unit of milk behave differently. A high-yielding cow can emit more per day yet less per kilogram of milk. Which trait a program selects on changes the outcome. Second, heritable and stable does not mean an index exists for sale on your sire sheet. This is research, and the selection decisions you make today still rest on the traits in genomic testing and Net Merit. Third, a favorable correlation in a population does not guarantee that every management change will behave the same way. Feeding changes, for example, can move methane and milk components at once.

What it could mean on the farm

Even before methane appears on any proof, the idea points to practical management habits.

1. Efficiency is the common thread. Keeping cows healthy, fertile and productive generally lowers emissions per unit of milk, because less feed and fewer replacement animals are needed per kilogram produced. The transition period and fertility pay off here as much as on the milk check.
2. Know your forage. Forage quality and ration balance affect rumen fermentation, and a nutritionist can walk you through changes. See forage testing for the starting point.
3. Keep good records. Test-day samples are the raw material for any future spectrum-based tool, so consistent testing keeps your options open.
4. Watch the market signals. If processors or cooperatives begin asking for emissions figures, spectral predictions are one possible route, but programs will define their own rules.

Cautions before anyone sells you a methane number

Ask what equation was used, which population it was built on, how it was validated and across what stage of lactation. A model trained on one breed and diet may drift in another. Also ask whether the figure is production, intensity or yield, since the three answer different questions. Finally, remember that genetic evaluations in the United States are run through the Council on Dairy Cattle Breeding at uscdcb.com, so any methane trait would reach breeders through that channel before it reaches an A.I. catalog. We make no claim that one is available now.

For farm-level context on how dairies are handling a changing market, browse farm.fm's dairy coverage, and look up extension contacts through the Agriculture Directory. This site is independent and not affiliated with any breed association or evaluation body.