Use of short-term breath measures to estimate daily methane production by cattle

Determination of gas flux and animal performance test duration of growing cattle in confined conditions

Data from three experiments was analyzed to determine the number of visits and days to assess gas flux (CH4, CO2, and O2), dry matter intake (DMI), and average daily gain (ADG) from growing animals under confined conditions. In experiment 1, 213 animals (461 ± 91 kg initial body weight [BW]) were fed a backgrounding diet and evaluated for 60 d. In experiment 2, 169 steers (488 ± 37 kg initial BW) were fed a finishing diet and assessed for 70 d. In experiment 3, 64 steers (514 ± 42 kg initial BW) were fed a finishing diet and evaluated for 80 d. In each experiment, animals were placed in one pen with one Greenfeed and five SmartFeeds to collect gas flux and feed intake simultaneously. Gas flux was analyzed using data from 161 animals from the three experiments with 100 visits for 2 or more min or 3 or more min. Also, metabolic heat production (MHP) was estimated using the individual gas flux. Daily DMI was calculated as the daily feed intake corrected by the dry matter concentration. ADG was computed as the slope of the regression of the shrunk BW (96% BW) throughout each of the experimental periods. The mean gas flux and MHP were estimated for increasing or decreasing 5-visit intervals starting with the first or the last 5 visits and increasing or decreasing until the full 100-visit dataset was utilized, respectively. Intervals of DMI were estimated for increasing or decreasing 5-d intervals starting with the first or the last 5 d and increasing or decreasing until the end of the experimental period, respectively. Intervals of ADG were estimated for increasing or decreasing measurement period intervals until the end of the experimental period, respectively. Pearson and Spearman correlations were computed between the maximum visits or days and each shortened visit or day interval. The minimum number of visits and days was determined when correlations with the total visits were greater than 0.95. The results indicated that the minimum number of visits needed to quantify CO2, O2, and MHP accurately was 40, while CH4 was 60. A visitation length of 2 min or more or 3 min or more did not modify the gas flux determination. Thus, based on the average daily visitation in these experiments, gas flux data could be collected for 25 d. Additionally, the required days to determine DMI was 30, while ADG could not be assessed in a shorter than 60-d period.

On-Farm Methane Mitigation and Animal Health Assessment of a Commercially Available Tannin Supplement in Organic Dairy Heifers

The objective of this experiment was to demonstrate the effectiveness of a commercially available tannin product (Silvafeed® ByPro, 70% tannic acid) as an enteric methane (CH4) mitigation and preventative animal health strategy in Holstein heifers (BW = 219 ± 17 kg; 9 mo), reared under organic production system requirements. Twenty heifers were randomly assigned to one of four commercial tannin supplementation treatments as follows: 0% (0 g/hd/d; CON), 0.075% (~5 g/hd/d; LOW), 0.15% (~10 g/hd/d; MED), and 0.30% (~21 g/hd/d; HIG) of dry matter intake (DMI). Heifers received their treatment in individual animal feeding stanchions and were fed a basal total mixed ration (TMR) through four SmartFeed Pro intake measurement bunk systems (C-Lock Inc., Rapid City, SD, USA) for 45 d. An automatic head chamber system (AHCS; i.e., GreenFeed, C-Lock Inc., Rapid City, SD, USA) was used to continuously evaluate enteric CH4 production. No effect was observed among the treatments for CH4 emissions (p ≥ 0.55), animal performance (p ≥ 0.38), or oxidative stress biomarker concentration (p ≥ 0.55). Superoxide dismutase (SOD) and reduced glutathione (GSH) concentrations exhibited a linear response to increasing tannin dose (p = 0.003), indicating a potential tannin effect on the antioxidant status of dairy heifers. This observation may encourage future tannin research relating to animal health, which may be of particular interest to organic dairy systems. The results of this study suggest that tannin supplementation at 0%, 0.075%, 0.15%, and 0.30% of DMI, did not alter CH4 emissions, animal performance, or oxidative stress biomarker concentration in organic Holstein heifers when assessed under an on-farm research approach. Further, the results of this study affirm the challenges associated with on-farm research and the development of climate-smart strategies that are capable of mitigating climate impacts in less controlled environments under standard working conditions.

Heritability and genetic correlations between enteric methane production and concentration recorded by GreenFeed and sniffers on dairy cows

To reduce methane (CH₄) emissions of dairy cows by animal breeding, CH₄ measurements have to be recorded on thousands of individual cows. Currently, several techniques are used to phenotype cows for CH₄, differing in costs and applicability. However, there is uncertainty about the agreement between techniques. To judge the similarity and repeatability between measurements of different recording techniques, the repeatability, heritability, and genetic correlation are useful metrics. Therefore, our objective was to estimate (1) the repeatability and heritability for CH₄ and carbon dioxide production recorded by GreenFeed (GF) and for CH₄ and carbon dioxide concentration measured by cost-effective but less accurate sniffers, and (2) the genetic correlation between CH₄ recorded with these 2 different on farm and high throughput techniques. Data were available from repeated measurements of CH₄ production (grams/day) by GF units and of CH₄ concentration (ppm) by sniffers, recorded on commercial dairy farms in the Netherlands. The final data comprised 24,284 GF daily means from 822 cows, 170,826 sniffer daily means from 1,800 cows, and 1,786 daily means from 75 cows by both GF and sniffer (in the same period). Additionally, CH₄ records were averaged per week. For daily and weekly mean GF CH₄ the heritabilities were 0.19 ± 0.02 and 0.33 ± 0.04, and for daily and weekly mean sniffer CH₄ the heritabilities were similar and were 0.18 ± 0.01 and 0.32 ± 0.02, respectively. Phenotypic correlations between GF CH₄ production and sniffer CH₄ concentration were moderate (0.39 ± 0.03 for daily means and 0.37 ± 0.05 for weekly means). However, genetic correlations were high; 0.71 ± 0.13 for daily means and 0.76 ± 0.15 for weekly means. The high genetic correlation indicates that selection on low CH₄ concentrations (ppm) recorded by the cost-effective sniffer method, will result in reduced CH₄ production (grams/day) as recorded with GF.

Phenotypic relationship and repeatability of methane emissions and performance traits in beef cattle using a GreenFeed system

Rumen methanogenesis results in the loss of 6% to 10% of gross energy intake in cattle and globally is the single most significant source of anthropogenic methane (CH4) emissions. The purpose of this study was to analyze greenhouse gas traits recorded in a commercial feedlot unit to gain an understanding into the relationships between greenhouse gas traits and production traits. Methane and carbon dioxide (CO2) data recorded via multiple GreenFeed Emission Monitoring (GEM), systems as well as feed intake, live weight, ultrasound scanning data, and slaughter data were available on 1,099 animals destined for beef production, of which 648 were steers, 361 were heifers, and 90 were bulls. Phenotypic relationships between GEM emission measurements with feed intake, weight traits, muscle ultrasound data, and carcass traits were estimated. Utilization of GEM systems, daily patterns of methane output, and repeatability of GEM system measurements across averaging periods were also assessed. Methane concentrations varied with visit number, duration, and time of day of visit to the GEM system. Mean CH4 and CO2 varied between sex, with mean CH4 of 256.1 g/day ± 64.23 for steers, 234.7 g/day ± 59.46 for heifers, and 156.9 g/day ± 55.98 for young bulls. A 10-d average period of GEM system measurements were required for steers and heifers to achieve a minimum repeatability of 0.60; however, higher levels of repeatability were observed in animals that attended the GEM system more frequently. In contrast, CO2 emissions reached repeatability estimates >0.6 for steers and heifers in all averaging periods greater than 2-d, suggesting that cattle have a moderately consistent CO2 emission pattern across time periods. Animals with heavier bodyweights were observed to have higher levels of CH4 (correlation = 0.30) and CO2 production (correlation = 0.61), and when assessing direct methane, higher levels of dry matter intake were associated with higher methane output (correlation = 0.31). Results suggest that reducing CH4 can have a negative impact on growth and body composition of cattle. Methane ratio traits, such as methane yield and intensity were also evaluated, and while easy to understand and compare across populations, ratio traits are undesirable in animal breeding, due to the unpredictable level of response. Methane adjusted for dry matter intake and liveweight (Residual CH4) should be considered as an alternative emission trait when selecting for reduced emissions within breeding goals.

Impact of forage diversity on forage productivity, nutritive value, beef cattle performance, and enteric methane emissions

Greenhouse gas emissions from the beef industry are largely attributed to the grazing sector, specifically from beef cattle enteric methane emissions. Therefore, the study objective was to examine how forage diversity impacts forage productivity, nutritive value, animal performance, and enteric methane emissions. This study occurred over three consecutive grazing seasons (2018 to 2020) and compared two common Midwest grazing mixtures: 1) a simple, 50:50 alfalfa:orchardgrass mixture (SIMP) and 2) a botanically diverse, cool-season species mixture (COMP). Fifty-six steers and heifers were adapted to an Automated Head Chamber System (AHCS) each year (C-Lock Inc., Rapid City, SD) and stratified into treatment groups based on acclimation visitation. Each treatment consisted of four pastures, three 3.2-ha and one 1.6-ha, with eight and four animals each, respectively. Forage production was measured biweekly in pre- and postgrazed paddocks, and forage nutritive value was analyzed using near-infrared reflectance spectroscopy. Shrunk body weights were taken monthly to determine animal performance. Forage availability did not differ between treatments (P = 0.69) but tended lower in 2018 (P = 0.06; 2.40 t dry matter ha⁻¹) than 2019 (2.92 t dry matter ha⁻¹) and 2020 (P = 0.10; 2.81 t dry matter ha⁻¹). Crude protein was significantly lower for COMP in 2018 compared with SIMP. Forage acid detergent fiber content was significantly lower for the COMP mixture (P = 0.02). The COMP treatment resulted higher dry matter digestibility (IVDMD48) in 2018 and 2019 compared with the SIMP treatment (P < 0.01). Animal performance did not differ between treatments (P > 0.50). There was a tendency for the COMP treatment to have lower enteric CH₄ production on a g d⁻¹ basis (P = 0.06), but no difference was observed on an emission intensity basis (g CH₄ kg⁻¹ gain; P = 0.56). These results would indicate that adoption of the complex forage mixture would not result in improved forage productivity, animal performance, or reduced emission intensity compared with the simple forage mixture.

Effect of divergence in residual methane emissions on feed intake and efficiency, growth and carcass performance, and indices of rumen fermentation and methane emissions in finishing beef cattle

Residual expressions of enteric emissions favor a more equitable identification of an animal's methanogenic potential compared with traditional measures of enteric emissions. The objective of this study was to investigate the effect of divergently ranking beef cattle for residual methane emissions (RME) on animal productivity, enteric emissions, and rumen fermentation. Dry matter intake (DMI), growth, feed efficiency, carcass output, and enteric emissions (GreenFeed emissions monitoring system) were recorded on 294 crossbred beef cattle (steers = 135 and heifers = 159; mean age 441 d (SD = 49); initial body weight (BW) of 476 kg (SD = 67)) at the Irish national beef cattle performance test center. Animals were offered a total mixed ration (77% concentrate and 23% forage; 12.6 MJ ME/kg of DM and 12% CP) ad libitum with emissions estimated for 21 d over a mean feed intake measurement period of 91 d. Animals had a mean daily methane emissions (DME) of 229.18 g/d (SD = 45.96), methane yield (MY) of 22.07 g/kg of DMI (SD = 4.06), methane intensity (MI) 0.70 g/kg of carcass weight (SD = 0.15), and RME 0.00 g/d (SD = 0.34). RME was computed as the residuals from a multiple regression model regressing DME on DMI and BW (R2 = 0.45). Animals were ranked into three groups namely high RME (>0.5 SD above the mean), medium RME (±0.5 SD above/below the mean), and low RME (>0.5 SD below the mean). Low RME animals produced 17.6% and 30.4% less (P < 0.05) DME compared with medium and high RME animals, respectively. A ~30% reduction in MY and MI was detected in low versus high RME animals. Positive correlations were apparent among all methane traits with RME most highly associated with (r = 0.86) DME. MY and MI were correlated (P < 0.05) with DMI, growth, feed efficiency, and carcass output. High RME had lower (P < 0.05) ruminal propionate compared with low RME animals and increased (P < 0.05) butyrate compared with medium and low RME animals. Propionate was negatively associated (P < 0.05) with all methane traits. Greater acetate:propionate ratio was associated with higher RME (r = 0.18; P < 0.05). Under the ad libitum feeding regime deployed here, RME was the best predictor of DME and only methane trait independent of animal productivity. Ranking animals on RME presents the opportunity to exploit interanimal variation in enteric emissions as well as providing a more equitable index of the methanogenic potential of an animal on which to investigate the underlying biological regulatory mechanisms.

Response to Climate Change: Evaluation of Methane Emissions in Northern Australian Beef Cattle on a High Quality Diet Supplemented with Desmanthus Using Open-Circuit Respiration Chambers and GreenFeed Emission Monitoring Systems

Simple Summary

The beef industry in Northern Australia is characterized by an extensive grazing system in dry tropical rangelands defined by climate change indices of very low rainfall, a prolonged dry season and feeds of low nutritive value. In response, beef cattle need to be more efficient in converting the available drought-tolerant feeds to muscle, in an attempt to minimize greenhouse gas emissions. This study addressed the problem of reducing methane emissions from tropical beef cattle with the goal of decreasing the impact of climate change and greenhouse gas emissions in Northern Australia. The primary objective was to compare the effect of supplementing tropical beef cattle with both good quality lucerne and poor quality hay with increasing levels of different Desmanthus cultivars on in vivo methane emission. The results showed that in tropical beef cattle on high-quality diets, irrespective of cultivar and emission evaluation method, Desmanthus does not reduce methane emissions.

Abstract

The main objective of this study was to compare the effect of supplementing beef cattle with Desmanthus virgatus cv. JCU2, D. bicornutus cv. JCU4, D. leptophyllus cv. JCU7 and lucerne on in vivo methane (CH₄) emissions measured by open-circuit respiration chambers (OC) or the GreenFeed emission monitoring (GEM) system. Experiment 1 employed OC and utilized sixteen yearling Brangus steers fed a basal diet of Rhodes grass (Chloris gayana) hay in four treatments—the three Desmanthus cultivars and lucerne (Medicago sativa) at 30% dry matter intake (DMI). Polyethylene glycol (PEG) was added to the diets to neutralize tannin binding and explore the effect on CH₄ emissions. Experiment 2 employed GEM and utilized forty-eight animals allocated to four treatments including a basal diet of Rhodes grass hay plus the three Desmanthus cultivars in equal proportions at 0%, 15%, 30% and 45% DMI. Lucerne was added to equilibrate crude protein content in all treatments. Experiment 1 showed no difference in CH₄ emissions between the Desmanthus cultivars, between Desmanthus and lucerne or between Desmanthus and the basal diet. Experiment 2 showed an increase in CH₄ emissions in the three levels containing Desmanthus. It is concluded that on high-quality diets, Desmanthus does not reduce CH₄ emissions.

Breeding for reduced methane emission and feed-efficient Holstein cows: An international response

Selecting for lower methane (CH₄) emitting animals is one of the best approaches to reduce CH₄ given that genetic progress is permanent and cumulative over generations. As genetic selection requires a large number of animals with records and few countries actively record CH₄, combining data from different countries could help to expedite accurate genetic parameters for CH₄ traits and build a future genomic reference population. Additionally, if we want to include CH₄ in the breeding goal, it is important to know the genetic correlations of CH₄ traits with other economically important traits. Therefore, the aim of this study was first to estimate genetic parameters of 7 suggested methane traits, as well as genetic correlations between methane traits and production, maintenance, and efficiency traits using a multicountry database. The second aim was to estimate genetic correlations within parities and stages of lactation for CH₄. The third aim was to evaluate the expected response of economically important traits by including CH₄ traits in the breeding goal. A total of 15,320 methane production (MeP, g/d) records from 2,990 cows belonging to 4 countries (Canada, Australia, Switzerland, and Denmark) were analyzed. Records on dry matter intake (DMI), body weight (BW), body condition score, and milk yield (MY) were also available. Additional traits such as methane yield (MeY; g/kg DMI), methane intensity (MeI; g/kg energy-corrected milk), a genetic standardized methane production, and 3 definitions of residual methane production (g/d), residual feed intake, metabolic BW (MBW), BW change, and energy-corrected milk were calculated. The estimated heritability of MeP was 0.21, whereas heritability estimates for MeY and MeI were 0.30 and 0.38, and for the residual methane traits heritability ranged from 0.13 to 0.16. Genetic correlations between different methane traits were moderate to high (0.41 to 0.97). Genetic correlations between MeP and economically important traits ranged from 0.29 (MY) to 0.65 (BW and MBW), being 0.41 for DMI. Selection index calculations showed that residual methane had the most potential for inclusion in the breeding goal when compared with MeP, MeY, and MeI, as residual methane allows for selection of low methane emitting animals without compromising other economically important traits. Inclusion of residual feed intake in the breeding goal could further reduce methane, as the correlation with residual methane is moderate and elicits a favorable correlated response. Adding a negative economic value for methane could facilitate a substantial reduction in methane emissions while maintaining an increase in milk production.

Technical note: validation of the GreenFeed system for measuring enteric gas emissions from cattle

There are knowledge gaps in animal agriculture on how to best mitigate greenhouse gas emissions while maintaining animal productivity. One reason for these gaps is the uncertainties associated with methods used to derive emission rates. This study compared emission rates of methane (CH4) and carbon dioxide (CO2) measured by a commercially available GreenFeed (GF) system with those from (1) a mass flow controller (MFC) that released known quantities of gas over time (i.e., emission rate) and (2) a respiration chamber (RC). The GF and MFC differed by only 1% for CH4 (P = 0.726) and 3% for CO2 (P = 0.013). The difference between the GF and RC was 1% (P = 0.019) for CH4 and 2% for CO2 (P = 0.007). Further investigation revealed that the difference in emission rate for CO2 was due to a small systematic offset error indicating a correction factor could be applied. We conclude that the GF system accurately estimated enteric CH4 and CO2 emission rates of cattle over a short measurement period, but additional factors would need to be considered in determining the 24-hr emission rate of an animal.

3-Nitrooxypropanol Decreased Enteric Methane Production From Growing Beef Cattle in a Commercial Feedlot: Implications for Sustainable Beef Cattle Production

Effects of the investigational methane (CH4) inhibitor 3-nitrooxypropanol (3-NOP) on animal performance, health and enteric CH4 production of beef cattle were evaluated in a commercial feedlot. Two concurrent studies were conducted: a large pen study (4,048 cattle, eight pen replicates per experimental group) to measure animal performance and health and a small pen study (a subset of 50 cattle from the large pen study, n = 25 per experimental group) to measure enteric CH4 emissions. Within the study, animals (body weight ± SD, 282 ± 8 kg) were assigned in a completely randomized design to one of two groups: control, fed a backgrounding diet (70% corn or barley silage, 30% steam-flaked barley grain concentrate; dry matter (DM) basis) and 3-NOP, fed the backgrounding diet containing 3-NOP. The treatment group in the large pen study was adapted to 3-NOP (12 ± 3 d) before receiving the final target level of 200 mg/kg of DM, which was fed for 108 ± 8 d. Animals in the small pen CH4 emissions study received a basal diet or a basal diet with 3-NOP, with the dose increased every 28 d: low (150 mg/kg DM; 1.27 g/d), medium (175 mg/kg DM; 2.25 g/d), and high (200 mg/kg DM; 2.75 g/d). Intake in the small pens was monitored by electronic feeding bunks and CH4 was measured using the GreenFeed system. In the large pen study, total weight gained, average daily gain, and animal health variables were not affected by 3-NOP, but DM intake (DMI) tended to decrease (P = 0.06) by 2.6% relative to control (8.07 kg/d), while gain:feed ratio tended to be improved (P = 0.06) by 2.5% relative to control (0.161 kg weight gain/kg DMI). In the small pen study, average daily consumption of 3-NOP increased with inclusion rate whereas average DMI was decreased by 5.4% (P = 0.02) compared with control (10.4 kg/d). On average, addition of 3-NOP decreased (P = 0.001) CH4 emissions (g/d) by 25.7% and yield (g CH4/kg DMI) by 21.7%. In conclusion, supplementing a backgrounding diet with 3-NOP decreased CH4 yield and tended to improve feed efficiency of beef cattle fed in a commercial feedlot with no negative impacts on animal health.

Use of 3-nitrooxypropanol in a commercial feedlot to decrease enteric methane emissions from cattle fed a corn-based finishing diet

The present study evaluated enteric CH4 production, dry matter (DM) intake (DMI), and rumen fermentation in feedlot cattle supplemented with increasing concentrations of 3-nitrooxypropanol (3-NOP). A total of 100 crossbred steers (body weight, 421 ± 11 kg) was randomly assigned to one of four treatments (n = 25/treatment): control (no 3-NOP) or low (100 mg/kg DM), medium (125 mg/kg DM), and high (150 mg/kg DM) doses of 3-NOP. The study was comprised of 28 d of adaptation followed by three 28-d periods, with CH4 measured for 7 d per period and cattle remaining on their respective diets throughout the 112-d study. Each treatment group was assigned to a pen, with the cattle and diets rotated among pens weekly to allow the animals to access the GreenFeed emission monitoring (GEM) system stationed in one of the pens for CH4 measurement. Measured concentration (mg/kg DM) of 3-NOP in the total diet consumed (basal diet + GEM pellet) was 85.6 for low, 107.6 for medium, and 124.5 for high doses of 3-NOP. There was a treatment × period interaction (P < 0.001) for DMI; compared with control, the DMI was less for the low and high doses in period 1, with no differences thereafter. Compared with control (10.78 g/kg DMI), CH4 yield (g/kg DMI) was decreased (P < 0.001) by 52%, 76%, and 63% for low, medium, and high doses of 3-NOP, respectively. A treatment × period effect (P = 0.048) for CH4 yield indicated that the low dose decreased in efficacy from 59% decrease in periods 1 and 2 to 37% decrease in period 3, while the efficacy of the medium and high doses remained consistent over time. Irrespective of dose, hydrogen emissions increased by 4.9-fold (P < 0.001), and acetate:propionate ratio in rumen fluid decreased (P = 0.045) with 3-NOP supplementation, confirming that other hydrogen-utilizing pathways become more important in the CH4-inhibited rumen. The study indicates that supplementation of corn-based finishing diets with 3-NOP using a medium dose is an effective CH4 mitigation strategy for commercial beef feedlots with a 76% decrease in CH4 yield. Further research is needed to determine the effects of 3-NOP dose on weight gain, feed conversion efficiency, and carcass characteristics of feedlot cattle at a commercial scale.

Predicting metabolisable energy intake by free-ranging cattle using multiple short-term breath samples and applied to a pasture case-study

Context Research into improving feed efficiency by ruminant animals grazing pastures has historically been restrained by an inability to measure feed intake by large numbers of individual animals. Recent advances in portable breath measurement technology could be useful for this purpose but methodologies need to be developed. Aims To evaluate predictive models for metabolisable energy intake (MEI) by free-ranging cattle using multiple short-term breath samples and then apply these to predict MEI by free-ranging cattle in a historic grazing experiment with cattle genetically divergent for residual feed intake (feed efficiency). Methods Predictive models for MEI were developed using bodyweight (BW) data, and carbon dioxide production rate (CPR) and methane production rate (MPR) from multiple short-term breath measurements, from an experiment with long-fed Angus steers on a grain-based diet, and an experiment with short-fed Angus heifers on a roughage diet. Heat production was calculated using CPR and MPR. Energy retained (ER) in body tissue gain by steers was calculated from BW, ADG, initial and final subcutaneous fat depths, and for both groups using feeding-standards equations. Key results Metabolic mid-test BW (MBW) explained 49 and 47% of the variation in MEI in the steer and heifer experiment, respectively, and for the steers adding ADG and then subcutaneous fat gain resulted in the models accounting for 60 and then 65% of the variation in MEI. In the steer experiment, MBW with CPR explained 57% of the variation in MEI, and including MPR did not account for any additional variation. In the heifer experiment, MBW with CPR explained 50%, and with MPR accounted for 52% of the variation in MEI. Heat production plus ER explained 60, 35 and 85% of the variation in MEI in the steer and the heifer experiments, and in the pooled data from both experiments, respectively. Conclusions Multiple short-term breath measurements, together simple BW data, can be used to predict MEI by free-ranging cattle in studies in which animals do not have feed-intake or ADG recorded. Implications This methodology can be used for research into improving feed efficiency by farm animals grazing pastures.

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.

Methane and carbon dioxide emissions from yearling beef heifers and mature cows classified for residual feed intake under drylot conditions

This study quantified methane (CH4) and carbon dioxide (CO2) production from beef heifers and cows classified for residual feed intake adjusted for off-test backfat thickness (RFIfat) and reared in drylot during cold winter temperatures. Individual performance, daily feed intake, and RFIfat were obtained for 1068 crossbred and purebred yearling heifers (eight trials) as well as 176 crossbred mature cows (six trials) during the winters of 2015–2017 at two locations. A portion of these heifers (147 high RFIfat; 167 low RFIfat) and cows (69 high RFIfat; 70 low RFIfat) was monitored for enteric CH4 and CO2 emissions using the GreenFeed Emissions Monitoring (GEM) system (C-Lock Inc., Rapid City, SD, USA). Low RFIfat cattle consumed less feed [heifers, 7.80 vs. 8.48 kg dry matter (DM) d−1; cows, 11.64 vs. 13.16 kg DM d−1] and emitted less daily CH4 (2.5% for heifers; 3.7% for cows) and CO2 (1.4% for heifers; 3.4% for cows) compared with high RFIfat cattle. However, low RFIfat heifers and cows had higher CH4 (6.2% for heifers; 9.9% for cows) and CO2 yield (7.3% for heifers; 9.8% for cows) per kilogram DM intake compared with their high RFIfat pen mates. The GEM system performed at air temperatures between +20 and −30 °C. Feed intake of heifers and mature cows was differently affected by ambient temperature reduction between +20 and −15 °C and similarly increased their feed intake at temperatures below −15 °C. In conclusion, low RFIfat animals emit less daily enteric CH4 and CO2, due mainly to lower feed consumption at equal body weight, gain, and fatness.

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.

A meta-analysis comparing four measurement methods to determine the relationship between methane emissions and dry-matter intake in New Zealand dairy cattle

Enteric methane (CH4) emissions and dry-matter intake (DMI) can be accurately and precisely measured in respiration chambers (RC), whereas automated head chambers (GreenFeed; GF) and the SF6 tracer method can provide estimates of CH4 emissions from grazing cattle. In New Zealand, most dairy cattle graze pasture and, under these conditions, DMI also has to be estimated. The objective of the current study was to compare the relationship between CH4 production and DMI of New Zealand dairy cattle fed forages using the following four measurement methods: RC with measured DMI (RC); sulfur hexafluoride (SF6) with measured DMI (SF6-DMI); SF6 with DMI estimated from prediction equations or indigestible markers (SF6); GF with measured or estimated DMI (GF). Data were collected from published literature from New Zealand trials with growing and lactating dairy cattle fed forage-based diets and data were analysed using a mixed-effect model. The intercept of the linear regression between CH4 production and DMI was not significantly different from zero and was omitted from the model. However, residual variance (observed–predicted values) increased with an increasing DMI, which was addressed by log-transforming CH4 per unit of DMI and this model was used for final data analysis. The accuracy of the four methods for predicting log CH4 per unit of DMI was similar (P = 0.55), but the precision (indicated by residuals) differed (P &lt; 0.001) among methods. The residual standard deviations for SF6, GF and SF6-DMI were 4.6, 3.4 and 2.1 times greater than the residuals for RC. Hence, all methods enabled accurate prediction of CH4 per unit of DMI, but methodology for determining both CH4 and DMI affected their precision (residuals).

Methane and carbon dioxide emissions from lactating dairy cows grazing mature ryegrass/white clover or a diverse pasture comprising ryegrass, legumes and herbs

There is a growing interest in forage mixtures (Diverse pasture; e.g. containing grasses, legumes and herbs), especially those with a greater tolerance of dry conditions and a decreased nitrogen (N) content (reducing N losses), compared with ryegrass (Lolium perenne L and Lolium multiflorum L)/white clover (Trifolium repens L) pastures (RyeWC), which dominate New Zealand pastoral systems for dairy production. However, the effect of alternative forages on enteric methane (CH4) emissions is not known. The objective of the present trial was to compare CH4 emissions and milk production from dairy cows grazing either mature RyeWC or mature Diverse pasture (both approximately with pasture mass of 5600 kg DM/ha). The Diverse mixture comprised ryegrass, white clover, lucerne (Medicago sativa L), chicory (Cichorium intybus L) and plantain (Plantago lanceolata L). Milk production, measured from cows commencing at ~162 days of lactation, was less when cows grazed RyeWC than Diverse pastures (15.4 vs 16.7 kg/day; P &lt; 0.001), whereas CH4 production (g/day) was similar for the respective treatments (411 g/day; P = 0.16). Milk composition was not affected by diet and CH4 intensity was similar for both diets (22 g/kg fat- and protein-corrected milk; P = 0.31). Methane yield [g/kg predicted dry matter intake (DMI)] averaged 22.6 and 24.9 for cows grazing RyeWC and Diverse pastures, respectively (P = 0.006). In conclusion, although the CH4 yield was greater when Diverse pasture was grazed, relative to RyeWC, there were no differences in emissions intensity or total CH4 emissions.

Comparison of 3 methods for estimating enteric methane and carbon dioxide emission in nonlactating cows

Among techniques for estimating enteric methane (CH4) emission by ruminants, open-circuit respiration chambers (OC), the use of a gas tracer (SF6), and the GreenFeed (GF) device are the most commonly used. In this study, we compared these techniques in 8 dry cows receiving a diet made of 70% hay and 30% concentrates given in limited and constant amounts, in a 15-wk experiment. Two periods in free stalls for SF6 and GF and in chambers for OC were used; in addition, SF6 was determined in chambers for 1 period. Methane emission (g/d) and CH4 yield (g/kg DMI) were higher (P < 0.0001) for OC than for SF6 and GF (367, 310, and 319 g/d for OC, SF6, and GF, respectively). The difference between OC and GF was related to a difference in post-prandial rate of gas emission. The between-animal coefficient of variation of CH4 emission was higher for SF6 than for OC and GF (20.8, 13.5, and 12.0% on average, respectively). Correlation coefficients between OC and SF6 were high and significant for CH4 emission and CH4 yield (r = 0.782 and r = 0.717, respectively; P < 0.05), but not significant between OC and GF, or between SF6 and GF. Correlation coefficients were highly significant for SF6 determined either in free stalls or in chambers (r = 0.908 and 0.903 for CH4 in g/d and g/kg DMI, respectively; P < 0.01). Carbon dioxide (CO2) emission and CO2 yield were similar for GF and OC (10,003 and 9,887 g/d, 752 and 746 g/kg DMI, respectively); CO2 data obtained with SF6 were lower (7,718 g/d and 606 g/kg DMI; P < 0.0001), but this technique is not relevant for CO2 emission determination. Correlation coefficients between OC and GF were not significant for CO2 emission and CO2 yield. This set of results shows that differences between methods are minor for average values, but that individual correlations may limit their interchangeability for determining gas emissions of individual animals. This study also shows the reliability of GF on-farm determination of CH4 and CO2 emissions for groups of animals.

Phenotypic relationships among methane production traits assessed under ad libitum feeding of beef cattle

Angus cattle from 2 beef cattle projects in which daily methane production (MPR) was measured were used in this study to examine the nature of the relationships among BW, DMI, and methane traits of beef cattle fed ad libitum on a roughage diet or a grain-based feedlot diet. In both projects methane was measured using the GreenFeed Emission Monitoring system, which provides multiple short-term breath measures of methane production. The data used for this study were from 119 Angus heifers over 15 d on a roughage diet and 326 Angus steers over 70 d on a feedlot diet. Mean (±SD) age, BW, and DMI were 372 ± 28 d, 355 ± 37 kg, and 8.1 ± 1.3 kg/d for the heifers and 554 ± 86 d, 577 ± 69 kg, and 13.3 ± 2.0 kg/d for the steers, respectively. The corresponding mean MPR was 212 g/d for heifers and 203 g/d for steers. Additional traits studied included methane yield (MY; MPR/DMI), methane intensity (MPR/BW), and 3 forms of residual methane production (RMP), which is a measure of actual minus predicted MPR. For RMP, RMP, and RMP predicted MPR were obtained by regression of MPR on BW, on DMI, and on both DMI and BW, respectively. The 2 data sets were analyzed separately using the same statistical procedures. For both feed types the relationships between MPR and DMI and between MPR and BW were both positive and linear. The correlation between MPR and DMI was similar to that between MPR and BW, although the correlations were stronger for the roughage diet ( = 0.75 for MPR vs. DMI; = 0.74 for MPR vs. BW) than the grain-based diet ( = 0.62 for MPR vs. DMI; = 0.66 for MPR vs. BW). The correlation between MY and DMI was negative and moderate for the roughage ( = -0.68) and grain-based ( = -0.59) diets, a finding that is different from the nonsignificant correlations reported in studies of cattle on a restricted roughage diet. The 3 RMP traits were strongly correlated ( values from 0.76 to 0.99) with each other for both the roughage and the grain-based diets, which indicates that using RMP to lower MPR could provide a result similar to using RMP in cattle. As feed intake (DMI) is more difficult to measure than BW, this result implies that under ad libitum feeding situations in which DMI cannot be measured, RMP can be used to identify higher- or lower-RMP animals with similar levels of effectiveness as RMP.

Enteric methane emissions from low- and high-residual feed intake beef heifers measured using GreenFeed and respiration chamber techniques

The objectives of this study were to evaluate the relationship between residual feed intake (RFI; g/d) and enteric methane (CH) production (g/kg DM) and to compare CH and carbon dioxide (CO) emissions measured using respiration chambers (RC) and the GreenFeed emission monitoring (GEM) system (C-Lock Inc., Rapid City, SD). A total of 98 crossbred replacement heifers were group housed in 2 pens and fed barley silage ad libitum and their individual feed intakes were recorded by 16 automated feeding bunks (GrowSafe, Airdrie, AB, Canada) for a period of 72 d to determine their phenotypic RFI. Heifers were ranked on the basis of phenotypic RFI, and 16 heifers (8 with low RFI and 8 with high RFI) were randomly selected for enteric CH and CO emissions measurement. Enteric CH and CO emissions of individual animals were measured over two 25-d periods using RC (2 d/period) and GEM systems (all days when not in chambers). During gas measurements metabolic BW tended to be greater ( ≤ 0.09) for high-RFI heifers but ADG tended ( = 0.09) to be greater for low-RFI heifers. As expected, high-RFI heifers consumed 6.9% more feed ( = 0.03) compared to their more efficient counterparts (7.1 vs. 6.6 kg DM/d). Average CH emissions were 202 and 222 g/d ( = 0.02) with the GEM system and 156 and 164 g/d ( = 0.40) with RC for the low- and high-RFI heifers, respectively. When adjusted for feed intake, CH yield (g/kg DMI) was similar for high- and low-RFI heifers (GEM: 27.7 and 28.5, = 0.25; RC: 26.5 and 26.5, = 0.99). However, CH yield differed between the 2 measurement techniques only for the high-RFI group ( = 0.01). Estimates of CO yield (g/kg DMI) also differed between the 2 techniques ( ≤ 0.03). Our study found that high- and low-efficiency cattle produce similar CH yield but different daily CH emissions. The 2 measurement techniques differ in estimating CH and CO emissions, partially because of differences in conditions (lower feed intakes of cattle while in chambers, fewer days measured in chambers) during measurement. We conclude that when intake of animals is known, the GEM system offers a robust and accurate means of estimating CH emissions from animals under field conditions.

Rapid Communication: Ranking dairy cows for methane emissions measured using respiration chamber or GreenFeed techniques during early, peak, and late lactation

Our objective was to compare the ranking of dairy cows according to their methane (CH) emissions as measured by a respiration chamber (RC) technique and the GreenFeed (GF) technique during 3 periods in second lactation. Two-day CH measurements in a RC performed in wk 3, 14, and 42 of lactation were flanked by GF measurements for 20 (period 1 [P1]), 35 (period 2 [P2]), and 35 (period 3 [P3]) days, respectively, before and after RC measurement. This gave the total duration of CH measurements using the GF system of 40, 70, and 70 d for P1, P2, and P3, respectively. Mean daily CH production (g/d) of the 8 dairy cows was 346, 439, and 430 using the RC technique and 338, 378, and 416 using the GF system during P1, P2, and P3, respectively. Average daily CH production determined by the GF technique was 2.4, 13.8, and 3.2% lower in P1, P2, and P3, respectively. Methane normalized to DMI continuously increased from P1 to P3 when measured in a RC, whereas it was lowest during P2 when measured by the GF method. Ranking of the cows according to CH production, CH/energy-corrected milk yield (ECM; CH/ECM), and CH/DMI differed between periods no matter which method was used. Cluster analysis including all 3 periods, however, identified the same cows with the highest and lowest CH production determined either by the RC technique or the GF system. In conclusion, multiple CH measurements at different stages of lactation are necessary for reliable discrimination of highest and lowest CH emitting cows and the GF system may be used to discriminate the extremes.

Global beef cattle methane emissions: yield prediction by cluster and meta-analyses

Methane yield values (MY; g methane/kg dry-matter intake) in beef cattle reported in the global literature (expanded MitiGate database of methane-mitigation studies) were analysed by cluster and meta-analyses. The Ward and k means cluster analyses included accounting for the categorical effects of methane measurement method, cattle breed type, country or region of study, age and sex of cattle, and proportion of grain in the diet and the standardised continuous variables of number of animals, liveweight and MY. After removal of data from outlier studies, meta-analyses were conducted on subsets of data to produce prediction equations for MY. Removing outliers with absolute studentised residual values of >1, followed by meta-analysis of data accounting for categorical effects, is recommended as a method for predicting MY. The large differences among some countries in MY values were significant but difficult to interpret. On the basis of the datasets available, a single, global MY or percentage of gross energy in feed converted to methane (Ym) value is not appropriate for use in Intergovernmental Panel on Climate Change (IPCC) greenhouse accounting methods around the world. Therefore, ideally country-specific MY values should be used in each country’s accounts (i.e. an IPCC Tier 2 or 3 approach) from data generated within that country.

Optimizing test procedures for estimating daily methane and carbon dioxide emissions in cattle using short-term breath measures

Respiration chambers are considered the reference method for quantifying the daily CH production rate (MPR) and CO production rate (CPR) of cattle; however, they are expensive, labor intensive, cannot be used in the production environment, and can be used to assess only a limited number of animals. Alternative methods are now available, including those that provide multiple short-term measures of CH and CO, such as the GreenFeed Emission Monitoring (GEM) system. This study was conducted to provide information for optimizing test procedures for estimating MPR and CPR of cattle from multiple short-term CH and CO records. Data on 495 Angus steers on a 70-d ad libitum feedlot diet with 46,657 CH and CO records and on 121 Angus heifers on a 15-d ad libitum roughage diet with 7,927 CH and CO records were used. Mean (SD) age and BW were 554 d (SD 92) and 506 kg (SD 73), respectively, for the steers and 372 d (SD 28) and 348 kg (SD 37), respectively, for the heifers. The 2 data sets were analyzed separately but using the same procedures to examine the reduction in variance as more records are added and to evaluate the level of precision with 2 vs. 3 min as the minimum GEM visit duration for a valid record. The moving averages procedure as well as the repeated measures procedure were used to calculate variances for both CH and CO, starting with 5 records and progressively increasing to a maximum of 80 records. For both CH and CO and in both data sets, there was a sharp reduction in the variances obtained by both procedures as more records were added. However, there was no substantial reduction in the variance after 30 records had been added. Inclusion of records with a minimum of 2-min GEM visit duration resulted in reduction in precision relative to a minimum of 3 min, as indicated by significantly ( < 0.05) more heterogeneous variances for all cases except CH4 in steers. In addition, more records were required to achieve the same level of precision relative to data with minimum GEM visit durations of 3 min. For example, in the steers, 72% reduction in initial variance was achieved with 30 records for both CH and CO when minimum GEM visit duration was 3 min, relative to 45 records when data with a minimum visit duration of 2 min were included. It is concluded from this study that when using records of multiple short-term breath measures of CH or CO for the computation of an animal's MPR or CPR, a minimum of 30 records, each record obtained from a minimum GEM visit duration of 3 min, are required.

Benefits of including methane measurements in selection strategies

Estimates of genetic/phenotypic covariances and economic values for slaughter weight, growth, feed intake and efficiency, and three potential methane traits were compiled to explore the effect of incorporating methane measurements in breeding objectives for cattle and meat sheep. The cost of methane emissions was assumed to be zero (scenario A), A$476/t (based on A$14/t CO equivalent and methane's 100-yr global warming potential [GWP] of 34; scenario B), or A$2,580/t (A$30/t CO equivalent combined with methane's 20-yr GWP of 86; scenario C). Methane traits were methane yield (MY; methane production divided by feed intake based on measurements over 1 d in respiration chambers) or short-term measurements of methane production adjusted for live weight (MPadjWt) in grazing animals, e.g., 40-60 min measurements in portable accumulation chambers (PAC) on 1 or 3 occasions, or measurements for 1 wk using a GreenFeed Emissions Monitor (GEM) on 1 or 3 occasions. Feed costs included the cost of maintaining the breeding herd and growth from weaning to slaughter. Sheep were assumed to be grown and finished on pasture (A$50/t DM). Feed costs for cattle included 365 d on pasture for the breeding herd and averages of 200 d postweaning grow-out on pasture and 100 d feedlot finishing. The greatest benefit of including methane in the breeding objective for both sheep and cattle was as a proxy for feed intake. For cattle, 3 GEM measurements were estimated to increase profit from 1 round of selection in scenario A (no payment for methane) by A$6.24/animal (from A$20.69 to A$26.93) because of reduced feed costs relative to gains in slaughter weight and by A$7.16 and A$12.09/animal, respectively, for scenarios B and C, which have payments for reduced methane emissions. For sheep, the improvements were more modest. Returns from 1 round of selection (no methane measurements) were A$5.06 (scenario A), A$4.85 (scenario B), and A$3.89 (scenario C) compared to A$5.26 (scenario A), A$5.12 (scenario B), and A$4.72 (scenario C) for 1 round of selection with 3 PAC measurements. Including MY in the selection index was less profitable because it did not reduce feed costs relative to weight gain. Consequently, for strategies measuring MY but not MPadjWt (and with no estimate of feed intake in the production environment), proportionately greater emphasis was placed on increasing slaughter weight, and as a result, the decreases in methane emissions per animal and per unit of feed intake were smaller than for strategies that measured MPadjWt.

Recent Advances in Measurement and Dietary Mitigation of Enteric Methane Emissions in Ruminants

Methane (CH4) emission, which is mainly produced during normal fermentation of feeds by the rumen microorganisms, represents a major contributor to the greenhouse gas (GHG) emissions. Several enteric CH4 mitigation technologies have been explored recently. A number of new techniques have also been developed and existing techniques have been improved in order to evaluate CH4 mitigation technologies and prepare an inventory of GHG emissions precisely. The aim of this review is to discuss different CH4 measuring and mitigation technologies, which have been recently developed. Respiration chamber technique is still considered as a gold standard technique due to its greater precision and reproducibility in CH4 measurements. With the adoption of recent recommendations for improving the technique, the SF6 method can be used with a high level of precision similar to the chamber technique. Short-term measurement techniques of CH4 measurements generally invite considerable within- and between-animal variations. Among the short-term measuring techniques, Greenfeed and methane hood systems are likely more suitable for evaluation of CH4 mitigation studies, if measurements could be obtained at different times of the day relative to the diurnal cycle of the CH4 production. Carbon dioxide and CH4 ratio, sniffer, and other short-term breath analysis techniques are more suitable for on farm screening of large number of animals to generate the data of low CH4-producing animals for genetic selection purposes. Different indirect measuring techniques are also investigated in recent years. Several new dietary CH4 mitigation technologies have been explored, but only a few of them are practical and cost-effective. Future research should be directed toward both the medium- and long-term mitigation strategies, which could be utilized on farms to accomplish substantial reductions of CH4 emissions and to profitably reduce carbon footprint of livestock production systems. This review presents recent developments and critical analysis on different measurements and dietary mitigation of enteric CH4 emissions technologies.