Quantification of methane emitted by ruminants: a review of methods

The contribution of greenhouse gas (GHG) emissions from ruminant production systems varies between countries and between regions within individual countries. The appropriate quantification of GHG emissions, specifically methane (CH4), has raised questions about the correct reporting of GHG inventories and, perhaps more importantly, how best to mitigate CH4 emissions. This review documents existing methods and methodologies to measure and estimate CH4 emissions from ruminant animals and the manure produced therein over various scales and conditions. Measurements of CH4 have frequently been conducted in research settings using classical methodologies developed for bioenergetic purposes, such as gas exchange techniques (respiration chambers, headboxes). While very precise, these techniques are limited to research settings as they are expensive, labor-intensive, and applicable only to a few animals. Head-stalls, such as the GreenFeed system, have been used to measure expired CH4 for individual animals housed alone or in groups in confinement or grazing. This technique requires frequent animal visitation over the diurnal measurement period and an adequate number of collection days. The tracer gas technique can be used to measure CH4 from individual animals housed outdoors, as there is a need to ensure low background concentrations. Micrometeorological techniques (e.g., open-path lasers) can measure CH4 emissions over larger areas and many animals, but limitations exist, including the need to measure over more extended periods. Measurement of CH4 emissions from manure depends on the type of storage, animal housing, CH4 concentration inside and outside the boundaries of the area of interest, and ventilation rate, which is likely the variable that contributes the greatest to measurement uncertainty. For large-scale areas, aircraft, drones, and satellites have been used in association with the tracer flux method, inverse modeling, imagery, and LiDAR (Light Detection and Ranging), but research is lagging in validating these methods. Bottom-up approaches to estimating CH4 emissions rely on empirical or mechanistic modeling to quantify the contribution of individual sources (enteric and manure). In contrast, top-down approaches estimate the amount of CH4 in the atmosphere using spatial and temporal models to account for transportation from an emitter to an observation point. While these two estimation approaches rarely agree, they help identify knowledge gaps and research requirements in practice.

Repeatability and ranking of long-term enteric methane emissions measurement on dairy cows across diets and time using GreenFeed system in farm-conditions

The aims of this work were to study on dairy farm conditions: i) the repeatability of long-term enteric CH₄ emissions measurement from lactating dairy cows using GreenFeed (GF); ii) the ranking of dairy cows according to their CH₄ emissions across diets. Forty-five Holstein lactating dairy cows were randomly assigned to 3 equivalent groups at the beginning of their lactation. The experiment was composed of 3 successive periods: i) pre-experimental period (weeks 1 to 5) in which all cows received a common diet; ii) a dietary treatment transition period (weeks 6 to 10); and iii) an experimental period (weeks 11 to 26) in which each group was fed a different diet. Experimental diets were formulated to generate more or less CH₄ production: i) a diet based on ryegrass silage and concentrates, low in starch and lipid, designed to induce high CH₄ emissions (CH4+); ii) a diet based on maize silage and concentrates, rich in starch, designed to induce intermediate CH₄ emissions (CH4int); iii) a diet based on maize silage and concentrates, rich in starch and lipid, designed to induce low CH₄ emissions (CH4-). Gas emissions were individually measured using GF systems. Repeatability of gas emissions, dry matter intake (DMI) and dairy performances measurements was calculated from data averaged over 1, 2, 4, and 8 weeks for each animal. Hierarchical cluster analysis was performed to rank individual animals according to their CH₄ emissions. No significant differences were observed for daily CH₄ emissions (g/day) among diets, because of lower DMI of CH4+ cows. When CH₄ emissions were referred to units of DMI or milk, the differences among diets emerged as significant and persistent over the observed period of lactation. Repeatability values of gas emissions measurements were higher than 0.7 averaged over 8 weeks of measurement, but still higher than 0.6 for CH₄ g/day, CO₂ g/day, CH₄ g/kg milk, and CH₄/CO₂ even averaging only 2 weeks of measurement. The repeatability of CH₄ emissions measurement was systematically lower than those of DMI or dairy performance parameters, like milk and FPCM yield, irrespective of the averaged measurement period. The dairy cow ranking was not stable over time between all individuals or within any of the diets. In our experimental conditions, the GF performance in the long term can be considered reliable in differentiating dairy herds by their CH₄ emissions according to diets with different methanogenic potential, but did not allow the ranking of individual dairy cows within a same diet. Our data highlight the importance of phenotyping animals across environment in which they will be expected to perform.

A Review of Enteric Methane Emission Measurement Techniques in Ruminants

To identify relationships between animal, dietary and management factors and the resulting methane (CH₄) emissions, and to identify potential mitigation strategies for CH₄ production, it is vital to develop reliable and accurate CH₄ measurement techniques. This review outlines various methods for measuring enteric CH₄ emissions from ruminants such as respiration chambers (RC), sulphur hexafluoride (SF₆) tracer, GreenFeed, sniffer method, ventilated hood, facemask, laser CH₄ detector and portable accumulation chamber. The advantages and disadvantages of these techniques are discussed. In general, RC, SF₆ and ventilated hood are capable of 24 h continuous measurements for each individual animal, providing accurate reference methods used for research and inventory purposes. However, they require high labor input, animal training and are time consuming. In contrast, short-term measurement techniques (i.e., GreenFeed, sniffer method, facemask, laser CH₄ detector and portable accumulation chamber) contain additional variations in timing and frequency of measurements obtained relative to the 24 h feeding cycle. However, they are suitable for large-scale measurements under commercial conditions due to their simplicity and high throughput. Successful use of these techniques relies on optimal matching between the objectives of the studies and the mechanism of each method with consideration of animal behavior and welfare. This review can provide useful information in selecting suitable techniques for CH₄ emission measurement in ruminants.

Comparison of Methods to Measure Methane for Use in Genetic Evaluation of Dairy Cattle

Partners in Expert Working Group WG2 of the COST Action METHAGENE have used several methods for measuring methane output by individual dairy cattle under various environmental conditions. Methods included respiration chambers, the sulphur hexafluoride (SF6) tracer technique, breath sampling during milking or feeding, the GreenFeed system, and the laser methane detector. The aim of the current study was to review and compare the suitability of methods for large-scale measurements of methane output by individual animals, which may be combined with other databases for genetic evaluations. Accuracy, precision and correlation between methods were assessed. Accuracy and precision are important, but data from different sources can be weighted or adjusted when combined if they are suitably correlated with the 'true' value. All methods showed high correlations with respiration chambers. Comparisons among alternative methods generally had lower correlations than comparisons with respiration chambers, despite higher numbers of animals and in most cases simultaneous repeated measures per cow per method. Lower correlations could be due to increased variability and imprecision of alternative methods, or maybe different aspects of methane emission are captured using different methods. Results confirm that there is sufficient correlation between methods for measurements from all methods to be combined for international genetic studies and provide a much-needed framework for comparing genetic correlations between methods should these become available.

Persistence of differences between dairy cows categorized as low or high methane emitters, as estimated from milk mid-infrared spectra and measured by GreenFeed

Currently, various attempts are being made to implement breeding schemes aimed at producing low methane (CH₄) emitting cows. We investigated the persistence of differences in CH₄ emission between groups of cows categorized as either low or high emitters over a 5-mo period. Two feeding regimens (pasture vs. indoors) were used. Early- to mid-lactation Holstein Friesian cows were categorized as low or high emitters (n = 10 each) retrospectively, using predictions from milk mid-infrared (MIR) spectra, before the start of the experiment. Data from MIR estimates and from measurements with the GreenFeed (GF; C-Lock Technology Inc., Rapid City, SD) system over the 5-mo experiment were combined into 7-, 14-, and 28-d periods. Feed intake, eating and ruminating behavior, and ruminal fluid traits were determined in two 7-d measurement periods in the grazing season. The CH₄ emission data were analyzed using a split-plot ANOVA, and the repeatability of each of the applied methods for determining CH₄ emission was calculated. Traits other than CH₄ emission were analyzed for differences between low and high emitters using a linear mixed model. The initial category-dependent differences in daily CH₄ production persisted over the subsequent 5 mo and across 2 feeding regimens with both methods. The repeatability analysis indicated that the biweekly milk control scheme, and even a monthly scheme as practiced on farms, might be sufficient for confirming category differences. However, the relationship between CH₄ data estimated by MIR and measured with GF for individual cows was weak (R² = 0.26). The categorization based on CH₄ production also generated differences in CH₄ emission per kilogram of milk; differentiation between cow categories was not persistent based on milk MIR spectra and GF. Compared with the high emitters, low emitters tended to show a lower acetate-to-propionate ratio in ruminal volatile fatty acids, whereas feed intake and ruminating time did not differ. Interestingly, the low emitters spent less time eating than the high emitters. In conclusion, the CH₄ estimation from analyzing the milk MIR spectra is an appropriate proxy to form and regularly control categories of cows with different CH₄ production levels. The categorization was also sufficient to secure similar and persistent differences in emission intensity when estimated by MIR spectra of the milk. Further studies are needed to determine whether MIR data from individual cows are sufficiently accurate for breeding.

Energy relations in cattle can be quantified using open-circuit gas-quantification systems

This study was conducted to evaluate the relationships between metabolisable energy (ME) intake and outputs of methane (CH4), rumen-derived carbon dioxide (rCO2), lung-derived carbon dioxide (lCO2), and total carbon dioxide output (tCO2) measured using an open-circuit gas-quantification system (GQS). Three trials were conducted to produce a wide range of energy intake and gas emissions to allow relationships between gas outputs and ME intake to be quantified. Gas emissions and ME intake were measured in eight Angus steers (455 ± 24.6 kg initial bodyweight; Trials 1 and 2), and in eight pregnant Angus heifers (503 ± 22.0 kg initial bodyweight; 5 months pregnant; Trial 3). Animals were fed twice daily to allow ad libitum intake in Trial 1, whereas in Trials 2 and 3, feed intake was restricted and energy density was varied to provide a wide range of ME intakes. Animals were allocated to individual pens during a 20-, 19- and 15-day experimental periods, and total faecal output was measured for the last 8, 4 and 4 days in Trials 1, 2 and 3 respectively. Gas emissions were measured for 16, 8 and 8 days after the adaptation period (4, 11 and 7 days) and each animal was allowed to visit the GQS every 2 h. Total CO2 in breath (tCO2) was separated into CO2 arising from rumen fermentation (rCO2) and CO2 in expired air from the lungs (lCO2) by manually identifying the eructations from normal breaths using the GQS gas-output trace. All CO2 outputs (lCO2, rCO2 and tCO2) were highly correlated with each other (r = 0.74–0.99; P < 0.01). Measurement of CO2 output was more repeatable with fewer days of measurement than was CH4 output. Metabolisable-energy intake was closely related to all three measures of CO2 output (rCO2, r = 0.69, P < 0.001; lCO2, r = 0.70, P < 0.001; and tCO2, r = 0.73, P < 0.001). Heat production was estimated from lCO2 output by assuming a value of 0.85 for the respiratory quotient of metabolised products. The heat production estimated at the extrapolated zero ME intake (0.52 MJ/kg0.75) was 60% higher than previous estimates of fasting heat production in cattle. However, our estimate was made under non-fasting, non-sedentary, non-thermoneutral conditions, so it may be a realistic estimate of maintenance energy requirement excluding heat increment of feeding. In conclusion, the open-circuit GQS can be used to provide estimates of the ME intake and heat production of cattle, and, as such, provides a valuable opportunity to describe the energy relations and efficiency of beef cattle in the field, with minimal interference to normal grazing patterns and behaviour.

Relationships between milk mid-IR predicted gastro-enteric methane production and the technical and financial performance of commercial dairy herds

Considering economic and environmental issues is important in ensuring the sustainability of dairy farms. The objective of this study was to investigate univariate relationships between lactating dairy cow gastro-enteric methane (CH4) production predicted from milk mid-IR (MIR) spectra and technico-economic variables by the use of large scale and on-farm data. A total of 525 697 individual CH4 predictions from milk MIR spectra (MIR-CH4 (g/day)) of milk samples collected on 206 farms during the Walloon milk recording scheme were used to create a MIR-CH4 prediction for each herd and year (HYMIR-CH4). These predictions were merged with dairy herd accounting data. This allowed a simultaneous study of HYMIR-CH4 and 42 technical and economic variables for 1024 herd and year records from 2007 to 2014. Pearson correlation coefficients (r) were used to assess significant relationships (P<0.05). Low HYMIR-CH4 was significantly associated with, amongst others, lower fat and protein corrected milk (FPCM) yield (r=0.18), lower milk fat and protein content (r=0.38 and 0.33, respectively), lower quantity of milk produced from forages (r=0.12) and suboptimal reproduction and health performance (e.g. longer calving interval (r=-0.21) and higher culling rate (r=-0.15)). Concerning economic results, low HYMIR-CH4 was significantly associated with lower gross margin per cow (r=0.19) and per litre FPCM (r=0.09). To conclude, this study suggested that low lactating dairy cow gastro-enteric CH4 production tended to be associated with more extensive or suboptimal management practices, which could lead to lower profitability. The observed low correlations suggest complex interactions between variables due to the use of on-farm data with large variability in technical and management practices.

Effect of high-oleic-acid soybeans on production performance, milk fatty acid composition, and enteric methane emission in dairy cows

The objective of this study was to investigate the effect of 3 soybean sources differing in fatty acid profile and processing method on productivity, milk composition, digestibility, rumen fermentation, and enteric methane emission in lactating dairy cows. The soybean sources were conventional, high-linoleic-acid variety extruded soybean meal (ESBM; 8.7% ether extract with 15% oleic and 54% linoleic acids); extruded Plenish (DuPont Pioneer, Johnston, IA), high-oleic-acid variety soybean meal (EPSBM; 8.4% ether extract with 73% oleic and 8% linoleic acids); and whole, heated Plenish soybeans (WPSB; 20.2% ether extract). The study involved 15 Holstein cows in a replicated 3 × 3 Latin square design experiment with three 28-d periods. The inclusion rate of the soybean sources in the diet was (dry matter basis) 17.1, 17.1, and 7.4% for ESBM, EPSBM, and WPSB, respectively, which resulted in ether extract concentration of the diets of 3.99, 3.94, and 4.18%, respectively. Compared with ESBM, the Plenish diets tended to increase dry matter intake and decreased feed efficiency (but had no effect on energy-corrected milk feed efficiency). The Plenish diets increased milk fat concentration on average by 5.6% and tended to increase milk fat yield, compared with ESBM. The WPSB diet tended to increased milk true protein compared with the extruded soybean meal diets. Treatments had no effect on rumen fermentation and enteric methane or carbon dioxide emissions, except pH was higher for WPSB versus EPSBM. The Plenish diets decreased the prevalence of Ruminococcus and increased that of Eubacterium and Treponema in whole ruminal contents. Total-tract apparent digestibility of organic matter and crude protein were decreased by WPSB compared with ESBM and EPSBM. Compared with the other treatments, urinary N excretion was increased by EPSBM and fecal N excretion was greater for WPSB. Treatments had marked effects on milk fatty acid profile. Generally, the Plenish diets increased mono-unsaturated (mostly cis-9 18:1) and decreased polyunsaturated, total trans-, and conjugated linoleic fatty acids concentrations in milk fat. In this study, compared with conventional, high-linoleic-acid variety extruded soybean meal, the Plenish soybean diets increased milk fat concentration and tended to increase fat yield, decreased feed efficiency, and modified milk fatty acid profile in a manner expected from the greater concentration of oleic acid in Plenish soybean oil.