Cow genes dictate environmentally friendly microbiomes: a step towards reducing greenhouse gas emissions.

Ruminants contribute to global warming by releasing methane (CH4) gas by enteric fermentation. This has increased interest among animal scientists to develop and improve equations predicting CH4 production. The objectives of the current study were to collect a data set from respiration studies and to evaluate the effects of dietary and animal factors on CH4 production from diets that can safely be fed to dairy cows, using a mixed model regression analysis. Therefore, diets containing more than 75% concentrate on a dry matter (DM) basis were excluded from the analysis. The final data set included a total of 298 treatment means from 52 published papers with 207 cattle and 91 sheep diets. Dry matter intake per kilogram of body weight (DMIBW), organic matter digestibility estimated at the maintenance level of feeding (OMDm), and dietary concentrations of neutral detergent fiber (NDF), nonfiber carbohydrates (NFC), and ether extract (EE) were the variables of the best-fit equation predicting CH4 energy (CH4-E) as a proportion of gross energy intake (GE): CH4-E/GE (kJ/MJ)=-0.6 (±12.76) - 0.70 (±0.072) × DMIBW (g/kg) + 0.076 (±0.0118) × OMDm (g/kg) - 0.13 (±0.020) × EE (g/kg of DM) + 0.046 (±0.0097) × NDF (g/kg of DM) + 0.044 (±0.0094) × NFC (g/kg of DM), resulting in the lowest root mean square error adjusted for random study effect (adj. RMSE=3.26 kJ/MJ). Total CH4 production (L/d) in the cattle data set was closely related to DM intake. However, further inclusion of other variables improved the model: CH4 (L/d)=-64.0 (±35.0) + 26.0 (±1.02) × DM intake (kg/d) - 0.61 (±0.132) × DMI(2)(centered) + 0.25 (±0.051) × OMDm (g/kg) - 66.4 (±8.22) × EE intake (kg of DM/d) - 45.0 (±23.50) × NFC/(NDF + NFC), with adj. RMSE of 21.1 L/d. Cross-validation of the CH4-E/GE equation [observed CH4-E/GE=0.96 (±0.103) × predicted CH4-E/GE + 2.3 (±7.05); R(2)=0.85, adj. RMSE=3.38 kJ/MJ] indicated that differences in CH4 production between the diets could be predicted accurately. We conclude that feed intake is the main determinant of total CH4 production and that CH4-E/GE is negatively related to feeding level and dietary fat concentration and positively to diet digestibility, whereas dietary carbohydrate composition has only minor effects.

Nutritional and animal-selection strategies to mitigate enteric methane (CH4) depend on accurate, cost-effective methods to determine emissions from a large number of animals. The objective of the present study was to compare 2 spot-sampling methods to determine CH4 emissions from dairy cows, using gas quantification equipment installed in concentrate feeders or automatic milking stalls. In the first method (sniffer method), CH4 and carbon dioxide (CO2) concentrations were measured in close proximity to the muzzle of the animal, and average CH4 concentrations or CH4/CO2 ratio was calculated. In the second method (flux method), measurement of CH4 and CO2 concentration was combined with an active airflow inside the feed troughs for capture of emitted gas and measurements of CH4 and CO2 fluxes. A muzzle sensor was used allowing data to be filtered when the muzzle was not near the sampling inlet. In a laboratory study, a model cow head was built that emitted CO2 at a constant rate. It was found that CO2 concentrations using the sniffer method decreased up to 39% when the distance of the muzzle from the sampling inlet increased to 30cm, but no muzzle-position effects were observed for the flux method. The methods were compared in 2 on-farm studies conducted using 32 (experiment 1) or 59 (experiment 2) cows in a switch-back design of 5 (experiment 1) or 4 (experiment 2) periods for replicated comparisons between methods. Between-cow coefficient of variation (CV) in CH4 was smaller for the flux than the sniffer method (experiment 1, CV=11.0 vs. 17.5%, and experiment 2, 17.6 vs. 28.0%). Repeatability of the measurements from both methods were high (0.72-0.88), but the relationship between the sniffer and flux methods was weak (R(2)=0.09 in both experiments). With the flux method CH4 was found to be correlated to dry matter intake or body weight, but this was not the case with the sniffer method. The CH4/CO2 ratio was more highly correlated between the flux and sniffer methods (R(2)=0.30), and CV was similar (6.4-8.8%). In experiment 2, cow muzzle position was highly repeatable (0.82) and influenced sniffer and flux method results when not filtered for muzzle position. It was concluded that the flux method provides more reliable estimates of CH4 emissions than the sniffer method. The sniffer method appears to be affected by variable air-mixing conditions created by geometry of feed trough, muzzle movement, and muzzle position.

It may be possible for dairy farms to improve profitability and reduce environmental impacts by selecting for higher feed efficiency and lower methane (CH4) emission traits. It remains to be clarified how CH4 emission and feed efficiency traits are related to each other, which will require direct and accurate measurements of both of these traits in large numbers of animals under the conditions in which they are expected to perform. The ranking of animals for feed efficiency and CH4 emission traits can differ depending upon the type and duration of measurement used, the trait definitions and calculations used, the period in lactation examined and the production system, as well as interactions among these factors. Because the correlation values obtained between feed efficiency and CH4 emission data are likely to be biased when either or both are expressed as ratios, therefore researchers would be well advised to maintain weighted components of the ratios in the selection index. Nutrition studies indicate that selecting low emitting animals may result in reduced efficiency of cell wall digestion, that is NDF, a key ruminant characteristic in human food production. Moreover, many interacting biological factors that are not measured directly, including digestion rate, passage rate, the rumen microbiome and rumen fermentation, may influence feed efficiency and CH4 emission. Elucidating these mechanisms may improve dairy farmers ability to select for feed efficiency and reduced CH4 emission.

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.