Use of methane production data for genetic prediction in beef cattle: A review

Methane (CH4) is a greenhouse gas that is produced and emitted from ruminant animals through enteric fermentation. Methane production from cattle has an environmental impact and is an energetic inefficiency. In the beef industry, CH4 production from enteric fermentation impacts all three pillars of sustainability: environmental, social, and economic. A variety of factors influence the quantity of CH4 produced during enteric fermentation, including characteristics of the rumen and feed composition. There are several methodologies available to either quantify or estimate CH4 production from cattle, all with distinct advantages and disadvantages. Methodologies include respiration calorimetry, the sulfur-hexafluoride tracer technique, infrared spectroscopy, prediction models, and the GreenFeed system. Published studies assess the accuracy of the various methodologies and compare estimates from different methods. There are advantages and disadvantages of each technology as they relate to the use of these phenotypes in genetic evaluation systems. Heritability and variance components of CH4 production have been estimated using the different CH4 quantification methods. Agreement in both the amounts of CH4 emitted and heritability estimates of CH4 emissions between various measurement methodologies varies in the literature. Using greenhouse gas traits in selection indices along with relevant output traits could provide producers with a tool to make selection decisions on environmental sustainability while also considering productivity. The objective of this review was to discuss factors that influence CH4 production, methods to quantify CH4 production for genetic evaluation, and genetic parameters of CH4 production in beef cattle.

Relationship between residual feed intake and digestive traits of fattening bulls fed grass silage- or maize silage-based diets

Several studies tried to identify digestive determinants of individual variation in feed efficiency between fattening bulls, because of their importance for breeding and management strategies. Most studies focused on single traits or single diet. Little is known about diet-dependent differences in digestive determinants and on their relative importance in distinguishing divergent residual feed intake (RFI) bulls. This research aimed (i) to identify digestive traits that differed between bulls diverging in RFI and fed a maize silage- or a grass silage-based diets; (ii) to highlight the relationships between RFI and digestive traits, and (iii) to explore the hierarchy among digestive traits in discriminating RFI divergent bulls. After an initial RFI test of 84 days on 100 Charolais growing bulls fed two different diets based on grass silage (GS), or maize silage (MS), the 32 most RFI divergent bulls were selected (eight efficient RFI- and eight inefficient RFI+ bulls per diet) and measured thereafter for total tract apparent digestibility and transit rate, enteric gas emissions (CH4 and H2), rumen pH, and feeding behaviour. Rumen particle size and visceral organ and reticulo-omasal orifice (ROO) sizes and rumen and ileum histology were measured at slaughter on the 32 selected extreme RFI bulls. Irrespective of the diet, efficient bulls (RFI-) had lower rumen size, CH4 yield (g/kg DM intake; tendency), lower number of cells in the ileal crypts, tended to have longer time of rumen pH below 5.8 and lower proportion of small size particles in rumen content than non-efficient bulls (RFI+). A long-term test for feed efficiency (197 d on average) was performed on the whole experimental period until slaughter for the 100 animals. The long-term RFI value was negatively related to time spent in activity other than ingestion, rumination, and resting, and positively related (tendency) to the duration of ingestion events, to rumen and abomasum size, irrespective of the diet. Diet-dependent effects were noted: with GS, efficient (RFI-) bulls showed a slower transit rate, whereas with MS, efficient (RFI-) bulls tended to have shorter resting events and a smaller ROO than inefficient bulls (RFI+). The transit rate and the ROO size tended to be positively related, while total tract apparent digestibility of nitrogen was negatively related to long-term RFI value, but only in GS. Rumen size appeared as the most discriminating digestive variable between RFI divergent bulls, but this result should be validated on a larger number of animals and diets.

Enteric methane research and mitigation strategies for pastoral-based beef cattle production systems

Ruminant livestock play a key role in global society through the conversion of lignocellulolytic plant matter into high-quality sources of protein for human consumption. However, as a consequence of the digestive physiology of ruminant species, methane (CH₄), which originates as a byproduct of enteric fermentation, is accountable for 40% of global agriculture's carbon footprint and ~6% of global greenhouse gas (GHG) emissions. Therefore, meeting the increasing demand for animal protein associated with a growing global population while reducing the GHG intensity of ruminant production will be a challenge for both the livestock industry and the research community. In recent decades, numerous strategies have been identified as having the potential to reduce the methanogenic output of livestock. Dietary supplementation with antimethanogenic compounds, targeting members of the rumen methanogen community and/or suppressing the availability of methanogenesis substrates (mainly H₂ and CO₂), may have the potential to reduce the methanogenic output of housed livestock. However, reducing the environmental impact of pasture-based beef cattle may be a challenge, but it can be achieved by enhancing the nutritional quality of grazed forage in an effort to improve animal growth rates and ultimately reduce lifetime emissions. In addition, the genetic selection of low-CH₄-emitting and/or faster-growing animals will likely benefit all beef cattle production systems by reducing the methanogenic potential of future generations of livestock. Similarly, the development of other mitigation technologies requiring minimal intervention and labor for their application, such as anti-methanogen vaccines, would likely appeal to livestock producers, with high uptake among farmers if proven effective. Therefore, the objective of this review is to give a detailed overview of the CH₄ mitigation solutions, both currently available and under development, for temperate pasture-based beef cattle production systems. A description of ruminal methanogenesis and the technologies used to estimate enteric emissions at pastures are also presented.

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.

The potential for mitigation of methane emissions in ruminants through the application of metagenomics, metabolomics, and other -OMICS technologies

Ruminant supply chains contribute 5.7 gigatons of CO_2-eq per annum, which represents approximately 80% of the livestock sector emissions. One of the largest sources of emission in the ruminant sector is methane (CH₄), accounting for approximately 40% of the sectors total emissions. With climate change being a growing concern, emphasis is being put on reducing greenhouse gas emissions, including those from ruminant production. Various genetic and environmental factors influence cattle CH₄ production, such as breed, genetic makeup, diet, management practices, and physiological status of the host. The influence of genetic variability on CH₄ yield in ruminants indicates that genomic selection for reduced CH₄ emissions is possible. Although the microbiology of CH₄ production has been studied, further research is needed to identify key differences in the host and microbiome genomes and how they interact with one another. The advancement of “-omics” technologies, such as metabolomics and metagenomics, may provide valuable information in this regard. Improved understanding of genetic mechanisms associated with CH₄ production and the interaction between the microbiome profile and host genetics will increase the rate of genetic progress for reduced CH₄ emissions. Through a systems biology approach, various “-omics” technologies can be combined to unravel genomic regions and genetic markers associated with CH₄ production, which can then be used in selective breeding programs. This comprehensive review discusses current challenges in applying genomic selection for reduced CH₄ emissions, and the potential for “-omics” technologies, especially metabolomics and metagenomics, to minimize such challenges. The integration and evaluation of different levels of biological information using a systems biology approach is also discussed, which can assist in understanding the underlying genetic mechanisms and biology of CH₄ production traits in ruminants and aid in reducing agriculture’s overall environmental footprint.

Review: Markers and proxies to monitor ruminal function and feed efficiency in young ruminants

Developing the rumen's capacity to utilise recalcitrant and low-value feed resources is important for ruminant production systems. Early-life nutrition and management practices have been shown to influence development of the rumen in young animals with long-term consequences on their performance. Therefore, there has been increasing interest to understand ruminal development and function in young ruminants to improve feed efficiency, health, welfare, and performance of both young and adult ruminants. However, due to the small size, rapid morphological changes and low initial microbial populations of the rumen, it is difficult to study ruminal function in young ruminants without major invasive approaches or slaughter studies. In this review, we discuss the usefulness of a range of proxies and markers to monitor ruminal function and nitrogen use efficiency (a major part of feed efficiency) in young ruminants. Breath sulphide and methane emissions showed the greatest potential as simple markers of a developing microbiota in young ruminants. However, there is only limited evidence for robust indicators of feed efficiency at this stage. The use of nitrogen isotopic discrimination based on plasma samples appeared to be the most promising proxy for feed efficiency in young ruminants. More research is needed to explore and refine potential proxies and markers to indicate ruminal function and feed efficiency in young ruminants, particularly for neonatal ruminants.

Genetic variance and covariance components for carbon dioxide production and postweaning traits in Angus cattle

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.

Repeatabilities, heritabilities and correlations of methane and feed intake of sheep in respiration and portable chambers

Context Knowledge of genetic and phenotypic variation and the accuracy of different measurement techniques is needed to successfully reduce livestock methane (CH4) emissions. Aims To estimate repeatabilities, heritabilities and genetic correlations of respiration-chamber (RC) and portable accumulation-chamber (PAC) measurements using two different protocols but the same management and feeding conditions. Methods Australian Information Nucleus Flock ewes were measured in seven test-batches. The 510 ewes were removed from pasture and habituated to chaffed alfalfa and cereal hay at 1.5–1.6 times maintenance. Methane was measured in RC for two 22-h periods approximately 14 days apart, and 40 min in PAC, either immediately after removal from individual pens (with feed as described above, PAC0), or 1-h after withdrawing feed (PAC1). There were up to 48 PAC0 tests per day (at 0930 hours, 1100 hours, 1230 hours, 1400 hours in 12 PAC) and 24 PAC1 tests per day (at 1100 hours and 1300 hours). Test methods (RC, PAC0, PAC1) were analysed as different traits in a multi-trait repeated-measures model. Key results Before adjustment for liveweight (Lwt) or feed intake (FI), CH4 was highly repeatable (RC 78%, PAC0 83%, PAC1 82%), with heritabilities of 39–55%, permanent environmental (PE) animal variances 23–43% of phenotypic variances (Vp), high genetic correlations between methods (98–100%), and lower PE correlations (44–58%). A second PAC test on the same day decreased CH4 by 8–12% compared with the ewe’s first test that day. Heritabilities of FI from 0800 hours until the test was complete (FIOD) were 16–17% (PAC) and 25% (RC) before adjusting for Lwt, with high PE variances (PAC 67–73%, RC 41% of Vp). FI in the previous 24 h was highly heritable and much less variable than was FIOD in the RC, suggesting that testing introduced additional variation by disrupting feeding patterns. After adjusting CH4 for Lwt, FIOD and FI in the previous 24 h and Lwt, some additive genetic variation remained, averaging 17% of Vp. Multivariate models of CH4 and FI, fitting a single animal term (representing genetic+PE variation) showed high animal correlations between FI and CH4, namely, 90–95% before, and 86–95% after adjusting for Lwt. Conclusions PAC measurements are heritable and highly correlated with RC measurements under similar management conditions. The high genetic and animal correlations of PAC CH4 and FI imply that CH4 is a useful proxy for FI of grazing animals.

Methane and Carbon Dioxide Emission of Beef Heifers in Relation with Growth and Feed Efficiency

Simple Summary

For sustainable meat production, beef farmers must make the best use of grass and roughage while limiting the carbon footprint of their herds. The genetic improvement in feed efficiency and enteric methane production of replacement heifers is possible if the recorded phenotypes are available. Intuitively, the relationship between the two traits should be negative, i.e., favorable, since the energy lost with the methane is not available for heifer metabolism. The measurement of feed efficiency requires several weeks of feed intake recording. The enteric methane emission rate can also be recorded over several weeks. The two traits of 326 beef heifers from two experimental farms were measured simultaneously for 8 to 12 weeks. The correlations between roughage intake, daily gain, and methane were all positive. The enteric methane emission rate was positively related to body weight, daily gain, and dry matter intake. The relationship with feed efficiency was slightly positive, i.e., unfavorable. Therefore, the two traits should be recorded simultaneously to evidence low-emitting and efficient heifers. This study also showed that replacing the feed intake recording with the carbon dioxide emission rate appeared potentially beneficial for selecting these low-emitting and efficient heifers.

Abstract

Reducing enteric methane production and improving the feed efficiency of heifers on roughage diets are important selection objectives for sustainable beef production. The objective of the current study was to assess the relationship between different methane production and feed efficiency criteria of beef heifers fed ad libitum roughage diets. A total of 326 Charolais heifers aged 22 months were controlled in two farms and fed either a grass silage (n = 252) or a natural meadow hay (n = 74) diet. Methane (CH₄) and carbon dioxide (CO₂) emission rates (g/day) were measured with GreenFeed systems. The dry matter intake (DMI), average daily gain (ADG), CH₄ and CO₂ were measured over 8 to 12 weeks. Positive correlations were observed among body weight, DMI, ADG, CH₄ and CO₂. The residual feed intake (r_wgDMI) was not related to CH₄ or residual methane (r_wiCH₄). It was negatively correlated with methane yield (CH₄/DMI): R_p = −0.87 and −0.83. Residual gain (r_wiADG) and ADG/DMI were weakly and positively related to residual methane (r_wiCH₄): R_p = 0.21 on average. The ratio ADG/CO₂ appeared to be a useful proxy of ADG/DMI (R_p = 0.64 and 0.97) and CH₄/CO₂ a proxy of methane yield (R_p = 0.24 and 0.33) for selecting low-emitting and efficient heifers.

Combining information from genome-wide association and multi-tissue gene expression studies to elucidate factors underlying genetic variation for residual feed intake in Australian Angus cattle

BACKGROUND

Genome-wide association studies (GWAS) are extensively used to identify single nucleotide polymorphisms (SNP) underlying the genetic variation of complex traits. However, much uncertainly often still exists about the causal variants and genes at quantitative trait loci (QTL). The aim of this study was to identify QTL associated with residual feed intake (RFI) and genes in these regions whose expression is also associated with this trait. Angus cattle (2190 steers) with RFI records were genotyped and imputed to high density arrays (770 K) and used for a GWAS approach to identify QTL associated with RFI. RNA sequences from 126 Angus divergently selected for RFI were analyzed to identify the genes whose expression was significantly associated this trait with special attention to those genes residing in the QTL regions.

RESULTS

The heritability for RFI estimated for this Angus population was 0.3. In a GWAS, we identified 78 SNPs associated with RFI on six QTL (on BTA1, BTA6, BTA14, BTA17, BTA20 and BTA26). The most significant SNP was found on chromosome BTA20 (rs42662073) and explained 4% of the genetic variance. The minor allele frequencies of significant SNPs ranged from 0.05 to 0.49. All regions, except on BTA17, showed a significant dominance effect. In 1 Mb windows surrounding the six significant QTL, we found 149 genes from which OAS2, STC2, SHOX, XKR4, and SGMS1 were the closest to the most significant QTL on BTA17, BTA20, BTA1, BTA14, and BTA26, respectively. In a 2 Mb windows around the six significant QTL, we identified 15 genes whose expression was significantly associated with RFI: BTA20) NEURL1B and CPEB4; BTA17) RITA1, CCDC42B, OAS2, RPL6, and ERP29; BTA26) A1CF, SGMS1, PAPSS2, and PTEN; BTA1) MFSD1 and RARRES1; BTA14) ATP6V1H and MRPL15.

CONCLUSIONS

Our results showed six QTL regions associated with RFI in a beef Angus population where five of these QTL contained genes that have expression associated with this trait. Therefore, here we show that integrating information from gene expression and GWAS studies can help to better understand the genetic mechanisms that determine variation in complex traits.

Differences in methane production, yield and intensity and its effects on metabolism of dairy heifers

The effects of divergent phenotypic classification in crossbreed Holstein × Gyr dairy heifers for methane emissions in relation to performance, digestibility, energy and nitrogen partition, blood metabolites and temperature of body surface were evaluated. Thirty-five heifers were classified as high and low emission for CH₄ production (g/day), yield (g/kg dry matter intake) and intensity (g/kg average daily gain). Digestibility was evaluated by total collection of feces and urine. Gas exchanges were obtained in open-circuit respiratory chambers. A completely randomized design was used and divergent groups were compared by Fisher's test. No differences were found in intake traits between groups of CH₄ production and intensity. The low yield group had higher intake. For digestibility and temperature at different body sites were no differences between variables. High production group had higher energy losses as methane and heat production. Low intensity group had higher digestible energy, energy balance and ratio between metabolizable and digestible energy. Urinary nitrogen was 14.3% lower for low production group. There was a difference between methane yield divergent groups for nitrogen intake, digestible and retained. Energy and nitrogen partitioning traits are correlated to the animals divergent for methane production and yield. The low production group presented lower blood insulin concentration. It was not possible to identify divergent animals for CH₄ emission using the infrared thermography technique.

Genetic variation in residual feed intake is associated with body composition, behavior, rumen, heat production, hematology, and immune competence traits in Angus cattle1

This experiment was to evaluate a suite of biological traits likely to be associated with genetic variation in residual feed intake (RFI) in Angus cattle. Twenty nine steers and 30 heifers bred to be divergent in postweaning RFI (RFIp) and that differed in midparent RFIp-EBV (RFIp-EBVmp) by more than 2 kg DMI/d were used in this study. A 1-unit (1 kg DM/d) decrease in RFIp-EBVmp was accompanied by a 0.08 kg (SE = 0.03; P < 0.05) increase in ADG, a 0.58 kg/d (0.17; P < 0.01) decrease in DMI, a 0.89 kg/kg (0.22; P < 0.001) decrease in FCR, and a 0.62 kg/d (0.12; P < 0.001) decrease in feedlot RFI (RFIf). Ultrasonically scanned depths of subcutaneous fat at the rib and rump sites, measured at the start and end of the RFI test, all had strong positive correlations with RFIp-EBVmp, DMI, and RFIf (all r values ≥0.5 and P < 0.001). Variation in RFIp-EBVmp was significantly correlated (P < 0.05) with flight speed (r = -0.32), number of visits to feed bins (r = 0.45), and visits to exhaled-emission monitors (r = -0.27), as well as the concentrations of propionate (r = -0.32) and valerate (r = -0.31) in rumen fluid, white blood cell (r = -0.51), lymphocyte (r = -0.43), and neutrophil (r = -0.31) counts in blood. RFIp-EBVmp was also correlated with the cellular immune response to vaccination (r = 0.25; P < 0.1) and heat production in fasted cattle (r = -0.46; P < 0.001). Traits that explained significant variation (P < 0.05) in DMI over the RFI test were midtest metabolic-BW (44.7%), rib fat depth at the end of test (an additional 18%), number of feeder visits (additional 5.7%), apparent digestibility of the ration by animals (additional 2.4%) and white blood-cell count (2.1%), and the cellular immune response to vaccine injection (additional 1.1%; P < 0.1), leaving ~23% of the variation in DMI unexplained. The same traits (BW excluded) explained 33%, 12%, 3.6%, 3.7%, and 3.1%, and together explained 57% of the variation in RFIf. This experiment showed that genetic variation in RFI was accompanied by variation in estimated body composition, behavior, rumen, fasted heat production, hematology, and immune competence traits, and that variation in feedlot DMI and RFIf was due to differences in BW, scanned fatness, and many other factors in these cattle fed ad libitum and able to display any innate differences in appetite, temperament, feeding behavior, and activity.

Could the breed composition improve performance and change the enteric methane emissions from beef cattle in a tropical intensive production system?

Crossbreeding has been used to improve performance in beef cattle, however the effects of breed composition on methane (CH₄) production, yield and intensity from cattle raised in tropical intensive and integrated systems remain unknown. To assess the impact of breed composition on performance and methane emissions, Nellore (NEL; yr 1: BW = 171.5 ± 19.4 kg; n = 10; yr 2: BW = 215.8 ± 32.3 kg, n = 25) and Angus x Nellore crossbred (AN; yr 1: BW = 214.2 ± 26.4 kg, n = 10; yr 2: BW = 242.5 ± 32.2 kg, n = 25) were compared. The animals grazed on integrated crop-livestock system in the growing phase (stocking rate 2452 kg BW/ha, herbage mass 4,884 kg dry matter (DM)/ha, forage allowance 5.9 kg DM/100kg BW) and then were finished in a feedlot. Steers (n = 8) from each breed composition were randomly selected in each phase to measure CH₄ production using a sulfur hexafluoride (SF₆) tracer technique and DM intake (DMI) using titanium dioxide. Compared with NEL, AN had both superior total gain and average daily gain (ADG) in the grazing period. The AN presented greater ADG in the feedlot with a shorter finishing period and resulted in greater carcass yield and carcass ADG. Methane production (kg/period) was lower in NEL (19% less) than AN in grazing (P<0.01), and no difference was observed in feedlot. The NEL had less CH₄ intensity (CH₄/BW) in grazing but greater CH₄ per unit of ADG in the feedlot compared to AN. Breed composition did not influence the CH₄ yield (CH₄/DMI) in either phase, despite the difference in feedlot DMI (kg/day). In conclusion, crossbreeding may be an option to improve performance and reduce the CH₄ per ADG in tropical climate conditions, resulting in lower methane emission per kg of meat produced.

Methods and consequences of including reduction in greenhouse gas emission in beef cattle multiple-trait selection

Background

Societal pressures exist to reduce greenhouse gas (GHG) emissions from farm animals, especially in beef cattle. Both total GHG and GHG emissions per unit of product decrease as productivity increases. Limitations of previous studies on GHG emissions are that they generally describe feed intake inadequately, assess the consequences of selection on particular traits only, or examine consequences for only part of the production chain. Here, we examine GHG emissions for the whole production chain, with the estimated cost of carbon included as an extra cost on traits in the breeding objective of the production system.

Methods

We examined an example beef production system where economic merit was measured from weaning to slaughter. The estimated cost of the carbon dioxide equivalent (CO₂-e) associated with feed intake change is included in the economic values calculated for the breeding objective traits and comes in addition to the cost of the feed associated with trait change. GHG emission effects on the production system are accumulated over the breeding objective traits, and the reduction in GHG emissions is evaluated, for different carbon prices, both for the individual animal and the production system.

Results

Multiple-trait selection in beef cattle can reduce total GHG and GHG emissions per unit of product while increasing economic performance if the cost of feed in the breeding objective is high. When carbon price was $10, $20, $30 and $40/ton CO₂-e, selection decreased total GHG emissions by 1.1, 1.6, 2.1 and 2.6% per generation, respectively. When the cost of feed for the breeding objective was low, selection reduced total GHG emissions only if carbon price was high (~ $80/ton CO₂-e). Ignoring the costs of GHG emissions when feed cost was low substantially increased emissions (e.g. 4.4% per generation or ~ 8.8% in 10 years).

Conclusions

The ability to reduce GHG emissions in beef cattle depends on the cost of feed in the breeding objective of the production system. Multiple-trait selection will reduce emissions, while improving economic performance, if the cost of feed in the breeding objective is high. If it is low, greater growth will be favoured, leading to an increase in GHG emissions that may be undesirable.

Electronic supplementary material

The online version of this article (10.1186/s12711-019-0459-5) contains supplementary material, which is available to authorized users.

The potential impact of breeding strategies to reduce methane output from beef cattle

The present paper provides an indication (using selection index theory) of the contribution of genetics to a reduction in methane emissions through the current selection for productivity traits (defined as the inherent rate). This is then compared with potential new approaches that incorporate measurements or estimates of methane production as selection criteria. The predicted value of the inherent reduction in methane at a price (all costs and prices are in Australian dollars) of $25/t carbon dioxide equivalent (CO2-e; methane × 25) is $0.38/cow mated per year. The direct value of the estimated annual genetic gain in productivity (about $3/cow mated) is about eight times the value of the savings in methane. The value of the carbon savings doubles to ~$0.75 if methane yield (methane per unit feed intake) is included in the index. This is due to a reduction in methane emissions of 0.78% of the mean (1.20 kg methane/cow mated per year at a carbon cost of $25/t CO2-e) which increases to 1.0% at $50/t CO2-e. If selection is on methane alone, the annual response is ~1.45%, which is valued at $1.39 at a price of $25/t CO2-e. However, adoption is less than 100% at the breeder level, so that realised gains will be less than predicted here.

Review: Biological determinants of between-animal variation in feed efficiency of growing beef cattle

Animal's feed efficiency in growing cattle (i.e. the animal ability to reach a market or adult BW with the least amount of feed intake), is a key factor in the beef cattle industry. Feeding systems have made huge progress to understand dietary factors influencing the average animal feed efficiency. However, there exists a considerable amount of animal-to-animal variation around the average feed efficiency observed in beef cattle reared in similar conditions, which is still far from being understood. This review aims to identify biological determinants and molecular pathways involved in the between-animal variation in feed efficiency with particular reference to growing beef cattle phenotyped for residual feed intake (RFI). Moreover, the review attempts to distinguish true potential determinants from those revealed through simple associations or indirectly linked to RFI through their association with feed intake. Most representative and studied biological processes which seem to be connected to feed efficiency were reviewed, such as feeding behaviour, digestion and methane production, rumen microbiome structure and functioning, energy metabolism at the whole body and cellular levels, protein turnover, hormone regulation and body composition. In addition, an overall molecular network analysis was conducted for unravelling networks and their linked functions involved in between-animal variation in feed efficiency. The results from this review suggest that feeding and digestive-related mechanisms could be associated with RFI mainly because they co-vary with feed intake. Although much more research is warranted, especially with high-forage diets, the role of feeding and digestive related mechanisms as true determinants of animal variability in feed efficiency could be minor. Concerning the metabolic-related mechanisms, despite the scarcity of studies using reference methods it seems that feed efficient animals have a significantly lower energy metabolic rate independent of the associated intake reduction. This lower heat production in feed efficient animals may result from a decreased protein turnover and a higher efficiency of ATP production in mitochondria, both mechanisms also identified in the molecular network analysis. In contrast, hormones and body composition could not be conclusively related to animal-to-animal variation in feed efficiency. The analysis of potential biological networks underlying RFI variations highlighted other significant pathways such as lipid metabolism and immunity and stress response. Finally, emerging knowledge suggests that metabolic functions underlying genetic variation in feed efficiency could be associated with other important traits in animal production. This emphasizes the relevance of understanding the biological basis of relevant animal traits to better define future balanced breeding programmes.

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.