Search

Context Cattle and sheep emit methane, a potent greenhouse gas, as part of the fermentation process of feed digestion in their gut; however, the mechanisms explaining differences among animals in enteric methane production are not fully understood. Aim To investigate whether variation among animals in their ability to digest their test ration was associated with phenotypic and genetic variation in methane production. Methods The experiment used 135 Angus beef cattle measured for their phenotypic and genetic merit for methane production. The extent of digestion of the dry matter (DMD) in the test ration by individual cattle was determined using silica as a naturally present indigestible marker. Its concentration in feed consumed and faeces was determined using rapid portable X-ray fluorescence spectroscopy, from which DMD was calculated. Key results Higher daily methane-production rate (MPR), higher methane produced per unit of feed consumed (methane yield; MY) and higher methane produced than the predicted daily production (residual MPR; RMP) by animals was accompanied by higher DMD. Higher genetic merit for MPR was also accompanied by higher DMD, but DMD had no detectable association with genetic variation in the other two methane emission traits. The regression coefficients for change in MPR (g/day), MY (g/kg DMI), RMP (g/day) with change in DMD (%) were 2.6 ± 1.1 (s.e.; P

This experiment investigated phenotypic and genetic relationships between carbon dioxide production, methane emission, feed intake, and postweaning traits in Angus cattle. Respiration chamber data on 1096 young bulls and heifers from 2 performance recording research herds of Angus cattle were analyzed to provide phenotypic and genetic parameters for carbon dioxide production rate (CPR; n = 425, mean 3,010 ± SD 589 g/d) and methane production rate (MPR; n = 1,096, mean 132.8 ± SD 25.2 g/d) and their relationships with dry matter intake (DMI; n = 1,096, mean 6.15 ± SD 1.33 kg/d), body weight (BW) and body composition traits. Heritability estimates were moderate to high for CPR (0.53 [SE 0.17]), MPR (0.31 [SE 0.07]), DMI (0.49 [SE 0.08]), yearling BW (0.46 [SE 0.08]), and scanned rib fat depth (0.42 [SE 0.07]). There was a strong phenotypic (0.83 [SE 0.02]) and genetic (0.75 [SE 0.10]) correlation between CPR and MPR. The correlations obtained for DMI with CPR and with MPR were high, both phenotypically (rp) and genetically (rg) (rp: 0.85 [SE 0.01] and 0.71 [SE 0.02]; rg (0.95 [SE 0.03] and 0.83 [SE 0.05], respectively). Yearling BW was strongly correlated phenotypically (rp ≥ 0.60) and genetically (rg > 0.80) with CPR, MPR, and DMI, whereas scanned rib fat was weakly correlated phenotypically (rp < 0.20) and genetically (rg ≤ 0.20) with CPR, MPR, and DMI. The strong correlation between both CPR and MPR with DMI confirms their potential use as proxies for DMI in situations where direct DMI recording is not possible such as on pasture.

Angus cattle from 2 beef cattle projects on which carbon dioxide production rate (CPR) was measured were used in this study to examine the relationships among BW, DMI, and carbon dioxide traits of beef cattle fed ad libitum on a roughage diet or a grain-based feedlot diet, and to evaluate potential proxies for DMI and feed efficiency. In both projects, the GreenFeed Emission Monitoring system, which provides multiple short-term breath measures of carbon dioxide production, was used as a tool to measure CPR. The data 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 CPR was 5760 ± 644 g/d for heifers and 8939 ± 1212 g/d for steers. Other traits studied included carbon dioxide yield (CY; CPR/DMI) and intensity (CI; CPR/BW) and 5 forms of residual carbon dioxide production (RCP), which is a measure of actual minus predicted CPR. Feed efficiency traits studied included feed conversion ratio (FCR) and residual feed intake (RFI). The relationship between CPR and DMI, and between CPR and BW was both positive and linear, for the heifers and also for the steers. For the combined heifer and steer datasets, the R2 for the relationship between CPR and BW, and between CPR and DMI was 0.82 and 0.78, respectively. The correlation between CPR and DMI (r = 0.84 for heifers; r = 0.83 for steers) was similar to that between CPR and BW (r = 0.84 for heifers; r = 0.87 for steers). Most of the carbon dioxide traits were significantly (P < 0.05) correlated with one or both feed efficiency traits. One of the RCP traits (RCPMA) was computed by maintaining metabolic BW (M) and average daily gain (A) in the formula for RFI, but substituting the DMI with CPR. The correlation (r = 0.27) between RCPMA and RFI, though significantly different from zero, was not strong enough for its use as proxy for RFI. On the other hand, a strong correlation (r = 0.73) was obtained between the CPR to gain ratio (CGR) and FCR. This indicates that, where DMI is not available, CPR could be used in its place to compute a feed efficiency trait similar to FCR, since the computation of CGR was similar to that for FCR, except that DMI was substituted with CPR in the FCR formula.

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.

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.

Ruminants contribute 80% of the global livestock greenhouse gas (GHG) emissions mainly through the production of methane, a byproduct of enteric microbial fermentation primarily in the rumen. Hence, reducing enteric methane production is essential in any GHG emissions reduction strategy in livestock. Data on 1,046 young bulls and heifers from 2 performance-recording research herds of Angus cattle were analyzed to provide genetic and phenotypic variance and covariance estimates for methane emissions and production traits and to examine the interrelationships among these traits. The cattle were fed a roughage diet at 1.2 times their estimated maintenance energy requirements and measured for methane production rate (MPR) in open circuit respiration chambers for 48 h. Traits studied included DMI during the methane measurement period, MPR, and methane yield (MY; MPR/DMI), with means of 6.1 kg/d (SD 1.3), 132 g/d (SD 25), and 22.0 g/kg (SD 2.3) DMI, respectively. Four forms of residual methane production (RMP), which is a measure of actual minus predicted MPR, were evaluated. For the first 3 forms, predicted MPR was calculated using published equations. For the fourth (RMP), predicted MPR was obtained by regression of MPR on DMI. Growth and body composition traits evaluated were birth weight (BWT), weaning weight (WWT), yearling weight (YWT), final weight (FWT), and ultrasound measures of eye muscle area, rump fat depth, rib fat depth, and intramuscular fat. Heritability estimates were moderate for MPR (0.27 [SE 0.07]), MY (0.22 [SE 0.06]), and the RMP traits (0.19 [SE 0.06] for each), indicating that genetic improvement to reduce methane emissions is possible. The RMP traits and MY were strongly genetically correlated with each other (0.99 ± 0.01). The genetic correlation of MPR with MY as well as with the RMP traits was moderate (0.32 to 0.63). The genetic correlation between MPR and the growth traits (except BWT) was strong (0.79 to 0.86). These results indicate that selection for lower MPR may have undesired effect on animal productivity. On the other hand, MY and the RMPR were either not genetically correlated or weakly correlated with BWT, YWT, and FWT (-0.06 to 0.23) and body composition traits (-0.18 to 0.18). Therefore, selection for lower MY or RMPR would lead to lower MPR without impacting animal productivity. Where the use of a ratio trait (e.g., MY) is not desirable, selection on any of the forms of RMP would be an alternative.

Enteric methane emissions from beef cattle are a significant component of total greenhouse gas emissions from agriculture. The variation between beef cattle in methane emissions is partly genetic, whether measured as methane production, methane yield (methane production/DMI), or residual methane production (observed methane production - expected methane production), with heritabilities ranging from 0.19 to 0.29. This suggests methane emissions could be reduced by selection. Given the high cost of measuring methane production from individual beef cattle, genomic selection is the most feasible approach to achieve this reduction in emissions. We derived genomic EBV (GEBV) for methane traits from a reference set of 747 Angus animals phenotyped for methane traits and genotyped for 630,000 SNP. The accuracy of GEBV was tested in a validation set of 273 Angus animals phenotyped for the same traits. Accuracies of GEBV ranged from 0.29 ± 0.06 for methane yield and 0.35 ± 0.06 for residual methane production. Selection on GEBV using the genomic prediction equations derived here could reduce emissions for Angus cattle by roughly 5% over 10 yr.

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.

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.

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.

Ruminants contribute up to 80% of greenhouse gas (GHG) emissions from livestock, and enteric methane production by ruminants is the main source of these GHG emissions. Hence, reducing enteric methane production is essential in any GHG emissions reduction strategy in livestock. Data from 2 performance-recording research herds of Angus cattle were used to evaluate a number of methane measures that target methane production (MPR) independent of feed intake and to examine their phenotypic relationships with growth and body composition. The data comprised 777 young bulls and heifers that were fed a roughage diet (ME of 9 MJ/kg DM) at 1.2 times their maintenance energy requirements and measured for MP in open circuit respiration chambers for 48 h. Methane traits evaluated included DMI during the methane measurement period, MPR, and methane yield (MY; MPR/DMI), with means (± SD) of 6.2 ± 1.4 kg/d, 187 ± 38 L/d, and 30.4 ± 3.5 L/kg, respectively. Four forms of residual MPR (RMP), which is a measure of actual minus predicted MPR, were evaluated. For the first 3 forms, predicted MPR was calculated using published equations. For the fourth (RMPR), predicted MPR was obtained by regression of MPR on DMI. Growth traits evaluated were BW at birth, weaning (200 d of age), yearling age (400 d of age), and 600 d of age, with means (± SD) of 34 ± 4.6, 238 ± 37, 357 ± 45, and 471 ± 53 kg, respectively. Body composition traits included ultrasound measures (600 d of age) of rib fat, rump fat, and eye muscle area, with means (± SD) of 3.8 ± 2.6 mm, 5.4 ± 3.8 mm, and 61 ± 7.7 cm(2), respectively. Methane production was positively correlated (r ± SE) with DMI (0.65 ± 0.02), MY (0.72 ± 0.02), the RMP traits (r from 0.65 to 0.79), the growth traits (r from 0.19 to 0.57), and the body composition traits (r from 0.13 to 0.29). Methane yield was, however, not correlated (r ± SE) with DMI (-0.02 ± 0.04) as well as the growth (r from -0.03 to 0.11) and body composition (r from 0.01 to 0.06) traits. All the RMP traits were strongly correlated to MY (r from 0.82 to 0.95). These results indicate that reducing MPR per se can have a negative impact on growth and body composition of cattle. Reducing MY, however, will likely have the effect of reducing MPR without impacting productivity. Where a ratio trait is undesirable, as in animal breeding, any of the RMP traits can be used instead of MY. However, where independence from DMI is desired, RMPR should be a trait worth considering.

Ruminants contribute 80% of the global livestock greenhouse gas (GHG) emissions mainly through the production of methane, a byproduct of enteric microbial fermentation primarily in the rumen. Hence, reducing enteric methane production is essential in any GHG emissions reduction strategy in livestock. Data on 1,046 young bulls and heifers from 2 performance-recording research herds of Angus cattle were analyzed to provide genetic and phenotypic variance and covariance estimates for methane emissions and production traits and to examine the interrelationships among these traits. The cattle were fed a roughage diet at 1.2 times their estimated maintenance energy requirements and measured for methane production rate (MPR) in open circuit respiration chambers for 48 h. Traits studied included DMI during the methane measurement period, MPR, and methane yield (MY; MPR/DMI), with means of 6.1 kg/d (SD 1.3), 132 g/d (SD 25), and 22.0 g/kg (SD 2.3) DMI, respectively. Four forms of residual methane production (RMP), which is a measure of actual minus predicted MPR, were evaluated. For the first 3 forms, predicted MPR was calculated using published equations. For the fourth (RMP), predicted MPR was obtained by regression of MPR on DMI. Growth and body composition traits evaluated were birth weight (BWT), weaning weight (WWT), yearling weight (YWT), final weight (FWT), and ultrasound measures of eye muscle area, rump fat depth, rib fat depth, and intramuscular fat. Heritability estimates were moderate for MPR (0.27 [SE 0.07]), MY (0.22 [SE 0.06]), and the RMP traits (0.19 [SE 0.06] for each), indicating that genetic improvement to reduce methane emissions is possible. The RMP traits and MY were strongly genetically correlated with each other (0.99 ± 0.01). The genetic correlation of MPR with MY as well as with the RMP traits was moderate (0.32 to 0.63). The genetic correlation between MPR and the growth traits (except BWT) was strong (0.79 to 0.86). These results indicate that selection for lower MPR may have undesired effect on animal productivity. On the other hand, MY and the RMPR were either not genetically correlated or weakly correlated with BWT, YWT, and FWT (-0.06 to 0.23) and body composition traits (-0.18 to 0.18). Therefore, selection for lower MY or RMPR would lead to lower MPR without impacting animal productivity. Where the use of a ratio trait (e.g., MY) is not desirable, selection on any of the forms of RMP would be an alternative.

Enteric methane emissions from beef cattle are a significant component of total greenhouse gas emissions from agriculture. The variation between beef cattle in methane emissions is partly genetic, whether measured as methane production, methane yield (methane production/DMI), or residual methane production (observed methane production - expected methane production), with heritabilities ranging from 0.19 to 0.29. This suggests methane emissions could be reduced by selection. Given the high cost of measuring methane production from individual beef cattle, genomic selection is the most feasible approach to achieve this reduction in emissions. We derived genomic EBV (GEBV) for methane traits from a reference set of 747 Angus animals phenotyped for methane traits and genotyped for 630,000 SNP. The accuracy of GEBV was tested in a validation set of 273 Angus animals phenotyped for the same traits. Accuracies of GEBV ranged from 0.29 ± 0.06 for methane yield and 0.35 ± 0.06 for residual methane production. Selection on GEBV using the genomic prediction equations derived here could reduce emissions for Angus cattle by roughly 5% over 10 yr.

Records on 1043 young Angus heifer and bull progeny from 73 sires, measured for methane production in respiration chambers, were used to evaluate the accuracy of a 1-day measurement relative to 2-day measurement duration. The traits assessed were dry matter intake (DMI, kg/day), methane-production rate (MPR, g/day), methane yield (MY, MPR per unit DMI) and four residual methane (RMP, g/day) traits. The RMP traits were computed as actual MPR minus expected MPR, where the expected MPR were calculated from three widely used equations. The expected MPR for the fourth RMP trait was computed by regressing MPR on DMI, using the data from the study. Variance components, heritability, phenotypic and genetic correlations, and the efficiency of selection using 1-day compared with 2-day measurement were used as assessment criteria. The environmental variance for the 2-day measurement was slightly lower than that of the 1-day measurement for all the traits studied, indicating that the addition of an extra day of data was effective in reducing the amount of unexplained variation in each trait. However, these minor reductions did not have a major impact on accuracy; hence, very high phenotypic (rp of 0.91–0.99) and genetic (rg of 0.99 for each trait) correlations were obtained between the two measurement durations. The very high genetic correlation between the two durations of measurement indicated that, at the genetic level, the 1-day duration is measuring the same trait as the 2-day measurement duration. Any enteric-methane emission-abatement strategy that seeks to reduce MPR per se, may have a detrimental impact on ruminant productivity through a correlated reduction in feed intake; hence, MY and the RMP traits are likely to be the traits of interest for genetic improvement. Efficiency of selection for MY and the RMP traits ranged from 0.96 to 0.99, which implies that there would be less than 5% loss in efficiency by adopting a 1-day relative to a 2-day methane-measurement duration. While the throughput of the respiration-chamber facility can be increased by adopting a 1-day measurement duration, additional resources, such as holding pens, would be required to take advantage of the extra day.

Ruminants contribute up to 80% of greenhouse gas (GHG) emissions from livestock, and enteric methane production by ruminants is the main source of these GHG emissions. Hence, reducing enteric methane production is essential in any GHG emissions reduction strategy in livestock. Data from 2 performance-recording research herds of Angus cattle were used to evaluate a number of methane measures that target methane production (MPR) independent of feed intake and to examine their phenotypic relationships with growth and body composition. The data comprised 777 young bulls and heifers that were fed a roughage diet (ME of 9 MJ/kg DM) at 1.2 times their maintenance energy requirements and measured for MP in open circuit respiration chambers for 48 h. Methane traits evaluated included DMI during the methane measurement period, MPR, and methane yield (MY; MPR/DMI), with means (± SD) of 6.2 ± 1.4 kg/d, 187 ± 38 L/d, and 30.4 ± 3.5 L/kg, respectively. Four forms of residual MPR (RMP), which is a measure of actual minus predicted MPR, were evaluated. For the first 3 forms, predicted MPR was calculated using published equations. For the fourth (RMPR), predicted MPR was obtained by regression of MPR on DMI. Growth traits evaluated were BW at birth, weaning (200 d of age), yearling age (400 d of age), and 600 d of age, with means (± SD) of 34 ± 4.6, 238 ± 37, 357 ± 45, and 471 ± 53 kg, respectively. Body composition traits included ultrasound measures (600 d of age) of rib fat, rump fat, and eye muscle area, with means (± SD) of 3.8 ± 2.6 mm, 5.4 ± 3.8 mm, and 61 ± 7.7 cm(2), respectively. Methane production was positively correlated (r ± SE) with DMI (0.65 ± 0.02), MY (0.72 ± 0.02), the RMP traits (r from 0.65 to 0.79), the growth traits (r from 0.19 to 0.57), and the body composition traits (r from 0.13 to 0.29). Methane yield was, however, not correlated (r ± SE) with DMI (-0.02 ± 0.04) as well as the growth (r from -0.03 to 0.11) and body composition (r from 0.01 to 0.06) traits. All the RMP traits were strongly correlated to MY (r from 0.82 to 0.95). These results indicate that reducing MPR per se can have a negative impact on growth and body composition of cattle. Reducing MY, however, will likely have the effect of reducing MPR without impacting productivity. Where a ratio trait is undesirable, as in animal breeding, any of the RMP traits can be used instead of MY. However, where independence from DMI is desired, RMPR should be a trait worth considering.

Records on 175 young Angus heifer and bull progeny from 46 sires, measured for methane production in respiration chambers, were used to evaluate the repeatability of methane measurement over short- and long-term periods. The traits assessed were dry matter intake (DMI), methane production rate (MPR), methane yield (MPR per unit DMI), and four residual methane (RMP) traits. The RMP traits were computed as actual MPR minus expected MPR, where the expected MPR for the first three RMP traits were calculated from three different published and widely used equations. The expected MPR for the fourth was computed by regressing MPR on DMI, using the data from the study. Animals underwent an initial (first) methane measurement test for 48 h, and one repeat methane measurement test up to 450 days after the first test. Repeat tests were classified into four different time periods: tested across consecutive days; re-tested within 60 days of first test; re-tested 61–120 days after first test; and re-tested 121–450 days after first test. Repeatabilities were calculated for all traits across all time periods, and phenotypic correlations for the same trait measured over time were obtained from bivariate analyses. Methane traits from tests conducted over consecutive days were highly repeatable (0.75–0.94) and highly phenotypically correlated (0.85–0.95). Repeatabilities from tests conducted within 60 days of the first test were moderate to high (0.59–0.91), whereas phenotypic correlations were, in general, moderate (0.30–0.44), with the exception of MPR (0.78). Results for both longer-term time periods (61–120 days and 121–450 days after the first test) were very similar, with low estimates of repeatabilities (0.16–0.27) and phenotypic correlations (0.12–0.27). Correlations between sire progeny means from the first and repeat methane test were moderate (0.46–0.77) for all traits except RMPR (0.19). Results from this study indicate that methane traits from tests conducted either on consecutive days or within a short-term time frame afterward (~60 days) are highly repeatable and highly phenotypically correlated. However, methane tests conducted over longer-term time frames are substantially, but consistently, less repeatable and are lowly phenotypically correlated, which indicates that multiple measures may be required to accurately record methane traits over the life time of an animal.