Discover how genetic selection in dairy cattle can revolutionize farming and combat climate change by significantly reducing methane emissions. Will you join the change?
It’s undeniable; the dairy industry is under immense pressure to reduce its environmental impact. One of most the significant culprits? Methane emissions. This potent greenhouse gas is drawing increasing attention as we grapple with the realities of climate change. Amidst growing calls for sustainable development, innovative strategies are stepping into the spotlight. One such strategy is genetic selection in dairy cattle, an unconventional yet promising approach. In this article, we will explore how this technique can help curtail methane outputs from dairy cattle and introduce more sustainable farming practices.
Climate change, sparked by an upsurge in greenhouse gases (GHGs) in our atmosphere, has become a paramount global concern. Why has one specific GHG – methane (CH4) – garnered attention more than others? And how can genetic strategies in our cattle help mitigate these emissions? Stick around, as we delve into these pressing questions and more.
Understanding Methane Emissions in Dairy Farming
Imagine if you could reduce the amount of methane released by cows simply by choosing the right genetics. Here’s how it works: Dairy cows, like all ruminants, naturally produce methane as they digest food. This methane production is a byproduct of enteric fermentation, a fascinating biological process that involves the fermentation of plant material by a rich community of microbes inside the animal’s stomach. Now, methane, as you may know, is a mighty force in terms of its greenhouse gas potency. It’s over 25 times more potent than carbon dioxide! That’s a significant blow our environment takes every time a cow belches, which it does quite frequently.
The dairy sector worldwide is, unsurprisingly, under close scrutiny to reduce its methane contributions for the betterment of our environment. The good news is that solutions are being sought diligently in the realm of science and technology. One of these innovative strategies is genetic selection in cattle, which showcases promising possibilities. Hang in there, and we’ll dive into how exactly genetic selection can curb methane emissions from our lovely dairy cows, paving the way for more environmentally friendly dairy farming practices.
Intriguingly, methane production varies among individual cows. An average Holstein cow, one of the popular dairy breeds, can release almost 500 grams of methane daily, which is roughly 397 lbs annually. But get ready for an interesting twist in our methane saga: some cows produce 30% more than the average, while others release 30% less than the average. You’re probably confused. Here’s what it means: two cows in the same herd could be releasing vastly different amounts of methane – we’re talking differences of around 238 lbs annually! But here’s the silver lining – such genetic variations among cows make genetic selection a potent tool to reduce methane emissions. After all, if there’s a heritable attribute that influences how much methane a cow releases, it makes perfect sense to choose the cows with the most favorable genetics for breeding purposes, doesn’t it?
The Role of Genetic Selection
As you explore options to curtail the issue of methane emissions, you’ll find that genetic selection plays a pivotal role. This process zeroes in on those cattle that organically emit less methane, providing an environmentally-friendly solution to the issue at hand. It works by picking out individuals based on certain characteristics or genetic identifiers that are connected to reduced methane production. Intriguingly, studies demonstrate a noticeable difference in methane output between cows, implying that genetic components significantly affect this trait. Hence, an investment in genetic selection is an investment in a healthier, more sustainable future for our dairy farming industry.
- Identifying Low-Methane Emitters
How do scientists go about identifying cattle that produce less methane? It’s no simple task. They resort to multiple methodologies, such as examining the microbial composition in the gut or measuring the gas directly from the air cows exhale. These intricate analysis methods aimed at identifying lower methane emitters are the first step towards making a real difference in methane emissions. - Breeding Programs
After identifying the low-methane emitters, what’s next in the playbook? Breeding them preferentially. This innovative breeding strategy steers the genetic makeup of future generations towards lower methane production, all without compromising dairy productivity. Doesn’t that make for a compelling approach? - Technological Advancements
Coming to the rescue in this challenging process, today’s advanced technological developments, like genomic sequencing and cutting-edge statistical models, are crucial. They assist in identifying the genetic markers linked to low methane emission. This level of precision allows the dairy industry to implement more effective and efficient selection procedures, revolutionizing their approach to methane emissions.
Using Genetics to Reduce Methane Emissions
Picture this: A cleaner, more environmentally-friendly world of dairy farming than exists today. It may sound like a far-off dream, but trust us – it’s closer to reality than you might think! A robust, lasting solution to reduce methane emissions revolves around genetically selecting cows that emit less methane (CH4). It’s crucial to mention, though, while this method has been proven effective, the high costs associated with methane measurements can make it seem daunting—resulting in few cows with substantial CH4 data. That’s where our heroes enter the picture—a group of tenacious researchers at the University of Guelph and Lactanet, working hand-in-hand with Semex, have broken down this barrier by discovering alternative ways to accurately predict the methane emissions of our bovine friends. Thanks to their ground-breaking work, we’ve unearthed a treasure trove of opportunities for efficiently managing and cutting back on greenhouse gas emissions in dairy farming. This game-changing method became possible, in part, thanks to research conducted at the University of Guelph, which determined that milk’s mid-infrared spectrometer data could serve as a reliable predictor of methane emissions. The research made innovative use of machine learning technology, a subtype of artificial intelligence (AI). Mid-infrared spectrometer data is a common resource for milk testing organizations, providing information about milk’s fat and protein percentage, along with other test results from daily milk samples. Surprisingly, this valuable data is often discarded after testing, but at Lactanet, they’ve been saving every snippet since 2018—just in case it might later prove useful for research! The endeavor to collate methane emission data from research herds was driven by two large-scale international projects and encompassed two Canadian research herds totaling 700 cows. These herds were equipped with GreenFeed machines, considered the “gold standard” for measuring methane emissions because they suction in every breath exhaled by the cows. An alternative and more economical method is using a sniffer, a device that calculates gas density and can be fitted into a milking robot. Now, with at least 30 commercial farms across Canada using sniffers, an even broader dataset is being accumulated to validate the original process. Not to be left out, data from other cattle breeds is also being gathered to extend methane efficiency proofing in the near future.
Collected Data
Figure 1. GreenFeed system used to measure gas fluxes including methane from individual animals.
You’ll be fascinated to learn that under the frameworks of the Efficient Dairy Genome Project (EDGP) and the Resilient Dairy Genome Project (RDGP), which can be accessed at http://www.resilientdairy.ca/, teams of diligent researchers are amassing a wealth of data regarding CH4 production. This data promises to serve as a valuable reference population for the calculation of genomic evaluations. In order to collect this data, the primary approach has largely centered around the greenfeed system, which cleverly gauges gas fluxes—including that of CH4—from single animals each time they utilize the feed trough component of the machine (figure 1). Despite its ingenuity, this process presents challenges in the form of great labor intensity, high costs, and limited feasibility for application on commercial dairy farms, which has thus far resulted in a relatively small sample of animals with measured CH4 emission phenotypes. Rising to the challenge, researchers from the University of Guelph have introduced a cutting-edge alternative, fueled by artificial intelligence and machine learning methodologies, designed to deliver large-scale predictions of CH4 emissions, as the ongoing collection of emission data marches forward.
Predicted Data
Researchers have discovered fascinating correlations between the composition of cow’s milk – especially fatty acids – and the animal’s methane (CH4) emissions, which are largely driven by enteric fermentation. Because of this relationship, we can leverage the milk composition data to accurately forecast a cow’s methane emissions. An innovative method employed in this process is mid-infrared (MIR) spectroscopy, which discerns a milk sample’s chemical makeup by observing how light is absorbed by the milk. Already successfully used to pinpoint specific milk constituents like fat and protein percentages, or beta-hydroxybutyrate (BHB), the technology holds immense potential for CH4 emission prediction. Each MIR examination of a milk sample generates over a thousand data points, all of which are collected and stored in the expansive Lactanet database, thanks to our milk recording services and laboratory milk sample analysis. Lactanet has used these spectral data, in combination with previously gathered methane data from research herds across Canada, to develop a sophisticated methane prediction system via machine learning. Utilizing only the first lactation data spanning from 120 to 185 days in milk, it is found that the algorithm’s predicted methane emissions demonstrate an impressive 85% genetic correlation with collected methane data, boasting a relatively high heritability of 23%. This illustrates how cutting-edge science and technology are working hand in hand to help us effectively manage our carbon footprint in dairy farming.
Methane Efficiency Evaluations
You’re probably wondering how it’s even possible to measure methane emissions on an individual cow-by-cow basis. Believe it or not, it’s not only feasible but also cost-effective, thanks to the use of milk spectral data. Lactanet has developed a method that can accurately predict CH4 emissions for a large number of cows without breaking the bank. This breakthrough has opened the door to genetic evaluations for CH4 emissions, a critical step in reducing their overall impact. Supporting Dairy Farmers of Canada’s long-held goal of attaining net-zero GHG emissions from farm-level dairy production by 2050, Lactanet, working with the University of Guelph and Semex, has launch the first-ever national genetic evaluation to decrease CH4 emissions from dairy cattle.
This game-changing initiative will take effect from April 2023, when the single-step genomic evaluation of predicted CH4 will yield Relative Breeding Values (RBV) for methane efficiency, specifically in the Holstein breed. Dairy producers, take note! This means you have the opportunity to select traits that decrease CH4 emissions, without any negative repercussions on production traits. And with the substantial reference population at our disposal, the average reliability of methane efficiency for genotyped young bulls and heifers is expected to exceed 70%.
FIGURE 1. DISTRIBUTION OF METHANE EFFICIENCY RELATIVE BREEDING VALUES (RBV) FOR OFFICIAL SIRES
In plain English, the measure of methane efficiency (ME) in Canada is expressed similarly to other traits: an average of 100 with a standard deviation of 5. Scores usually fall between 85 to 115, with cattle scoring above 100 demonstrating greater methane efficiency i.e., they produce less methane than their counterparts with scores below 100. To put this into perspective, a bull that scores one standard deviation above the mean (say, 105) should father daughters that will emit 3kg or 6.6lb less methane annually – a minor reduction that over time and generations can accumulate significantly. If a breeder consistently selects bulls with a 105 ME rating, by 2050 their herd could have 20-30% lower methane emissions than today. Methane efficiency computation utilizes a single-step evaluation model, which conveniently incorporates all pedigree, performance, and genotype data into one calculation. The aim remains steadfast—to reduce methane emissions without disturbing milk, fat, and protein yields. To that end, methane efficiency is represented in such a way that it is genetically unconnected to these yields. The reliability of this trait for young genotyped bulls and heifers remains over a reassuring 70%.
FIGURE 2. HOLSTEIN PROOF CORRELATIONS BETWEEN METHANE EFFICIENCY AND OTHER TRAITS (SHADED AREA REPRESENTS CORRELATIONS WITHIN ± 15%)
It’s worth noting that methane efficiency does not bear any significant negative correlations with other essential characteristics, such as lpi or pro$. In context, correlations oscillating between ±0.15 are usually not deemed significant. On the upside, evidence suggests some crucial, albeit minor, positive associations with metabolic disease resistance, daughter fertility, and with broader health and fertility indicators. Now, consider this: methane emissions account for an energy loss of approximately 4-7% of total intake. Therefore, energy preserved, which could have otherwise been wasted on methane emissions, seems to be funneled towards boosting health outcomes. The meticulous crafting of this trait to ensure its independence from other production characteristics offers an explanation for its minuscule correlations with yield traits. Likely, this arrangement likewise influences its negative correlation of -.14% with feed efficiency. Therefore, the genetic selection for methane efficiency appears to bring along added health benefits while leaving other crucial production traits untouched.
Allow me to paint a picture for you with some top performers, providing insight into potential superior sires spearheading methane efficiency. Topping the chart with an awe-inspiring score of 118 is the bull S-S-I Renegade Improbable, a product of the prolific collaboration between S-S-I PR Renegade-ET and S-S-I Took 7261 8495-ET at Select Sires. This table of honour comprises not only methane efficiency but also feed efficiency, placing a spotlight on the intertwined relationship between these traits. An outlier that shatters the norm while excelling in both metrics is Drumdale Allday P, boasting a methane efficiency score of 115 and a feed efficiency score of 106. Tracing his lineage reveals a rich genetic heritage marked by Cherry-Lily Zip Luster-P, View-Home Powerball-P, and tracing back to Boldi V S G Epic Allie. Talk about genetic royalty, right? Moving forward, the key to ensuring continuous breed-wide improvement for this trait lies in its inclusion in the Total Index. It’s exciting news that Canada has initiated a modernization process for the LPI (Lifetime Profit Index), transitioning this evaluation model from a 3-sub-index to a 6-sub-index system as of April 2025. The Sustainability Index, a dynamic new sub-index, is anticipated to embrace both feed efficiency and body maintenance. And you guessed it – methane efficiency will proudly occupy a spot on that inclusive sustainability roster. Genetic selection coupled with comprehensive performance assessment, as you can see, has the capacity to transform the dairy industry’s impact on the environment dramatically.
| Name | LPI | Pro$ | Milk | Fat | Prot | %F | %P | Conf | ME | FE | ||
| S-S-I RENGADE IMPROBABLE-ET | 3287 | 1573 | 54 | 58 | 39 | 0.48 | 0.29 | 7 | 118 | 100 | ||
| VOGUE FIRECRACKER-ET | 3174 | 1269 | 14 | 24 | 29 | 0.21 | 0.23 | 10 | 117 | 102 | ||
| S-S-I MILLINGTON TOTEM-ET | 3287 | 1518 | 565 | 55 | 33 | 0.27 | 0.1 | 5 | 116 | 97 | ||
| PEAK ALTAVITOR-ET | 3089 | 1919 | 365 | 104 | 60 | 0.75 | 0.37 | -5 | 116 | 95 | ||
| SYNERGY ALTAPARQUET-ET | 2963 | 942 | 804 | 35 | 19 | 0.04 | -0.07 | 1 | 116 | 98 | ||
| PROGENESIS HEISENBERG | 2943 | 1345 | 145 | 34 | 24 | 0.24 | 0.16 | -5 | 116 | 101 | ||
| DRUMDALE ALLDAY P | 3456 | 2484 | 486 | 99 | 55 | 0.67 | 0.3 | 4 | 115 | 106 | ||
| STE ODILE PLEASE P | 2568 | 14 | 15 | -47 | 12 | -0.39 | 0.09 | -1 | 115 | 102 | ||
| WESTCOAST TICKET | 3065 | 1172 | -450 | 51 | 26 | 0.58 | 0.34 | -2 | 114 | 100 | ||
| DE-SU KING R RULER 13999-ET | 2676 | 509 | -990 | 36 | 15 | 0.66 | 0.4 | -4 | 113 | 101 | ||
| MR TANGOSTAR-ET | 2614 | 166 | 46 | 29 | 27 | 0.24 | 0.21 | -1 | 113 | 102 | ||
| ELSBERND ALTAHOMERIC-ET | 2488 | -166 | 374 | -40 | -10 | -0.45 | -0.17 | 1 | 113 | 99 | ||
| PROGENESIS ALTAPLEDGE-ET | 3312 | 2311 | 594 | 78 | 62 | 0.46 | 0.33 | -4 | 112 | 103 | ||
| GLEN-D-HAVEN ALTABUCK-ET | 2833 | 613 | -462 | 23 | 18 | 0.36 | 0.27 | 0 | 112 | 100 | ||
| JUMAU TORPIDO | 2775 | 498 | -165 | 21 | 29 | 0.23 | 0.27 | -1 | 112 | 101 | ||
| BOLDI V ALPHORN | 2663 | 197 | 537 | 8 | 23 | -0.1 | 0.04 | -3 | 112 | 99 | ||
| CLAYNOOK DEALER | 2605 | 245 | 822 | -2 | 20 | -0.27 | -0.05 | 0 | 112 | 95 |
Benefits of Methane Reduction and Beyond
Imagine our planet enveloped in a layer of greenhouse gases much like a protective blanket; these gases stop the sun’s heat from bouncing away, which maintains Earth’s average temperature at around 14⁰C (57⁰F). Absent this natural greenhouse effect, Earth’s temperature could plummet to -18⁰C (-0.4⁰F). The density of this gas layer has remained surprisingly consistent over millennia, largely because the primary greenhouse gas—carbon dioxide—takes an astounding 1,000 years to break down. Our other significant greenhouse gases include methane and nitrous oxide; methane, although it breaks down within just a dozen years, is 27 times more effective at trapping heat than carbon dioxide, while nitrous-oxide, despite a lengthy 120-year breakdown time, is an incredible 265 times more potent.
The relative constancy of our greenhouse gas layer, however, began to change with the onset of the industrial era. That’s when we started burning vast quantities of fossil fuels and pumping massive amounts of carbon dioxide into the atmosphere. Compounding the problem, the human population ballooned from 2 billion in 1924 to 8 billion by 2024, while forest coverage tumbled from two-thirds to just one-third. Between 1970 and 2004, our total greenhouse gas emissions shot up by 70%, driving atmospheric carbon dioxide density from 410 parts per million (ppm) in 1970 to 425 ppm today.
Against this backdrop, cutting methane emissions offers an attractive, short-term opportunity for decreasing overall greenhouse gas density. Since any reduction in methane levels will manifest in a comparable decrease in total atmospheric greenhouse gases within 12 years, and considering that methane contributes to 19% of the total greenhouse gas effect (with half of that coming from ruminants), it’s clear that we need to focus on this area. Indeed, since 1984, atmospheric methane has surged from 1,650 parts per billion to 1,900 parts per billion.
Moving forward, we should also tackle nitrous-oxide emissions, largely linked to excessive nitrogen fertilizer use. The production of ammonia—the foundation of nitrogen fertilizers—consumes significant quantities of natural gas and results in three tons of carbon dioxide being released for every ton of ammonia we produce. Combined, nitrous-oxide and the carbon dioxide produced during ammonia production account for 7.5% of the total greenhouse gas effect. Key to reducing our reliance on nitrogen fertilizers will be the expanded use of legumes, the improvement and increased use of inoculants to facilitate nitrogen fixation by grass species, the inclusion of mixed forage crops and perennials, and a pivot toward cover crops and minimum-tillage methods.
The benefits of genetic selection for low methane emissions extend beyond environmental impacts:
- Improved Efficiency: Cattle that produce less methane often digest food more efficiently, translating into better feed conversion ratios and potentially higher milk yields.
- Economic Advantages: Lower methane emissions can also mean reduced costs associated with feed, as more energy from feed is used for growth and production rather than lost as methane.
- Health and Welfare Improvements: Genetic advancements can lead to healthier cattle with better overall well-being, which is increasingly important to consumers.
The Bottom Line
In essence, the deployment of genetic selection marks a revolutionary pivot in the way the dairy sector counters its ecological hurdles. This innovative strategy of curbing methane emissions via purposeful breeding methods empowers dairy farmers to join hands in the global combat against climate change, while simultaneously beefing up the sustainability and efficacy of their individual businesses. The evolution of this domain holds immense potential in orchestrating the destiny of dairy farming, aligning it seamlessly with worldwide sustainability objectives.
