Suchergebnisse

The European small ruminants (i.e. sheep and goats) farming sector (ESRS) provides economic, social and environmental benefits to society, but is also one of the most vulnerable livestock sectors in Europe. This sector has diverse livestock species, breeds, production systems and products, which makes difficult to have a clear vision of its challenges through using conventional analyses. A multi-stakeholder and multi-step approach, including 90 surveys, was used to identify and assess the main challenges for the sustainability of the ESRS to prioritize actions. These challenges and actions were identified by ESRS experts including farmers, cooperatives, breeding associations, advisers and researchers of six EU countries and Turkey. From the 30 identified challenges, the most relevant were economy-related challenges such as 'uncertainty of meat and milk prices', 'volatility of commodity prices', 'low farm income', 'high subsidy dependency' and 'uncertainty in future changes in subsidies' resulting in 'a sector not attractive to young farmers'. Most of these challenges were beyond the farmer's control and perceived as difficult to address. Challenges were prioritized using an index, calculated by multiplying the relevance and the feasibility to address measures. The identified challenges had a similar priority index across the whole sector with small differences across livestock species (sheep vs goats), type of products (meat vs dairy) and intensification levels (intensive vs semi-intensive vs extensive). The priorities were different, however, between socio-geographical regions (Southern vs Central Europe). Some of the top prioritized challenges were linked to aspects related to the production systems ('low promotion of local breeds' and 'slow adaptability of high producing breeds') and market practices ('unfair trade/lack of traceability'). The majority of the priority challenges, however, were associated with a deficient knowledge or training at farm level ('poor business management training', 'lack of professionalization', 'slow adoption of innovations'), academia ('researchers do not address real problems') and society as a whole ('low consumer education in local products', 'low social knowledge about farming', 'poor recognition of farming public services'). Thus, improved collaboration among the different stakeholders across the food chain with special implication of farmers, associations of producers, academia and governments is needed to facilitate knowledge exchange and capacity building. These actions can contribute to make ESRS economically more sustainable and to adapt the production systems and policy to the current and future societal needs in a more region-contextualized framework. ; This study was supported by the EU Horizon 2020 Research and In-novation Action (RIA) through the project'Innovation for sustainablesheep and Goat production in Europe (iSAGE)'under grant agreement 679302

Recent evidence suggests that changes in microbial colonization of the rumen prior to weaning may imprint the rumen microbiome and impact phenotypes later in life. We investigated how dietary manipulation from birth influences growth, methane production, and gastrointestinal microbial ecology. At birth, 18 female Holstein and Montbéliarde calves were randomly assigned to either treatment or control (CONT). Treatment was 3-nitrooxypropanol (3-NOP), an investigational anti-methanogenic compound that was administered daily from birth until three weeks post-weaning (week 14). Samples of rumen fluid and faecal content were collected at weeks 1, 4, 11, 14, 23, and 60 of life. Calves were tested for methane emissions using the GreenFeed system during the post-weaning period (week 11–23 and week 56–60 of life). Calf physiological parameters (BW, ADG and individual VFA) were similar across groups throughout the trial. Treated calves showed a persistent reduction in methane emissions (g CH/d) throughout the post-weaning period up to at least 1 year of life, despite treatment ceasing three weeks post-weaning. Similarly, despite variability in the abundance of individual taxa across weeks, the rumen bacterial, archaeal and fungal structure differed between CONT and 3-NOP calves across all weeks, as visualised using sparse-PLS-DA. Similar separation was also observed in the faecal bacterial community. Interestingly, despite modest modifications to the abundance of rumen microbes, the reductive effect of 3-NOP on methane production persisted following cessation of the treatment period, perhaps indicating a differentiation of the ruminal microbial ecosystem or a host response triggered by the treatment in the early development phase. ; SM received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie Grant Agreement #658126. CS received a fellowship from the Fundación Alfonso Martín Escudero. This research was partially funded by the French National Research Agency (ANR) throughmthe FACCE-JPI project RumenStability. The authors wish to thank Florence Fournier and personnel at the Herbipole for animal care, and Dominique Graviou for laboratory technical support. We are grateful to the INRAE MIGALE bioinformatics platform (http://migal e.jouy.inra.fr) for providing computational resources.

Newborn dairy ruminants are usually separated from their dams after birth and fed on milk replacer. This lack of contact with adult animals may hinder the rumen microbiological and physiological development. This study evaluates the effects of rearing newborn goat kids in contact with adult companions on the rumen development. Thirty-two newborn goat kids were randomly allocated to two experimental groups which were reared either in the absence (CTL) or in the presence of non-lactating adult goats (CMP) and weaned at 7 weeks of age. Blood and rumen samples were taken at 5, 7, and 9 weeks of age to evaluate blood metabolites and rumen microbial fermentation. Next-generation sequencing was carried out on rumen samples collected at 7 weeks of age. Results showed that CTL kids lacked rumen protozoa, whereas CMP kids had an abundant and complex protozoal community as well as higher methanogen abundance which positively correlated with the body weight and blood β-hydroxybutyrate as indicators of the physiological development. CMP kids also had a more diverse bacterial community (+132 ASVs) and a different structure of the bacterial and methanogen communities than CTL kids. The core rumen bacterial community in CMP animals had 53 more ASVs than that of CTL animals. Furthermore, the number of ASVs shared with the adult companions was over 4-fold higher in CMP kids than in CTL kids. Greater levels of early rumen colonizers Proteobacteria and Spirochaetes were found in CTL kids, while CMP kids had higher levels of Bacteroidetes and other less abundant taxa (Veillonellaceae, Cyanobacteria, and Selenomonas). These findings suggest that the presence of adult companions facilitated the rumen microbial development prior to weaning. This accelerated microbial development had no effect on the animal growth, but CMP animals presented higher rumen pH and butyrate (+45%) and ammonia concentrations than CTL kids, suggesting higher fibrolytic and proteolytic activities. CMP kids also had higher blood β-hydroxybutyrate (+79%) and lower blood glucose concentrations (-23%) at weaning, indicating an earlier metabolic development which could favor the transition from pre-ruminant to ruminant after the weaning process. Further research is needed to determine the effects of this intervention in more challenging farm conditions. ; This work was supported by the European Union's Horizon 2020 Research and Innovation program under grant agreement no. 818368 (MASTER) and by the Spanish Government through the project AGL2017-86938-R. JP-H has a grant from the Training Program for Academics, Madrid, Spain (FPU16/01981) and AB is a Ramón y Cajal Fellow [RYC2019-027764-I/AEI/10.13039/501100011033] from the Spanish Research Agency.

Ruminants are born with an undeveloped physical, metabolic, and microbial rumen. Rumen development is limited under artificial rearing systems when newborn animals are separated from the dam, fed on milk replacer, and weaned at an early age. This study aims to evaluate the effects of early-life inoculation of young ruminants with rumen fluid from adult animals. Eighty newborn goat kids were randomly allocated to 1 of 4 experimental treatments and inoculated daily from d 1 to wk 11 with autoclaved rumen fluid (AUT), fresh rumen fluid obtained from adult goats fed either a forage diet (RFF) or concentrate-rich diet (RFC), or absence of inoculation (CTL). Goat kids were artificially reared with ad libitum access to milk replacer, starter concentrate, and forage hay. Blood was sampled weekly and rumen microbial fermentation was monitored at 5 (preweaning), 7 (weaning), and 9 wk of age (postweaning). Results indicated that inoculation with fresh rumen fluid accelerated the rumen microbial and fermentative development before weaning. As a result, RFC and RFF animals had higher solid feed intake (+73%), rumen concentrations of ammonia-N (+26%), total volatile fatty acids (+46%), butyrate (+50%), and plasma β-hydroxybutyrate (+48%), and lower milk intake (−6%) than CTL and AUT animals at wk 5. Inoculation with fresh inoculum also promoted early rumen colonization by a complex and abundant protozoal community, whereas CTL animals remained protozoa free. Although all kids experienced moderate growth retardation during 1 wk after weaning, inoculation with fresh rumen fluid favored the weaning process, leading to 2.2 times higher weight gain than CTL and AUT animals during wk 8. Some of these advantages were retained during the postweaning period and RFF and RFC animals showed higher forage intake (up to +44%) than CTL and AUT animals with no detrimental effects on feed digestibility or stress levels. The superior microbial load of RFC compared with RFF inoculum tended to provide further improvements in terms of forage intake, plasma β-hydroxybutyrate, and rumen protozoa, whereas AUT inoculation provided minor (if any) advantages with respect to CTL animals. Although no differences were noted on animal growth, this study suggests that early life inoculation of goat kids with rumen microbiota can represent an effective strategy to accelerate the rumen development, facilitating a smooth transition from milk to solid feed and to the potential implementation of early weaning strategies. ; This study was funded by the Spanish government through the project AGL2017-86938-R and the Training Program for Academics grant, Madrid, Spain (FPU16/01981).

© 2014 American Institute of Chemical Engineers. Artificial slurry (4% dry matter) was prepared using fresh feces and urine obtained from four pregnant sows fed with commercial diet. Freeze-dried dairy cattle feces were used (external archaea) as co-inoculum (Co-i) and structural carbohydrates (CHO: apple pulp; sugar beet pulp; and wheat straw) as substrates. Bottles were incubated (39 ± 1°C for 56 days), and the gas production was measured (mbar) and converted to the volume. A sample of produced gas was taken and analyzed for methane concentration using a gas chromatography. Bottles were opened at days 0, 25, and 56 to determine total bacteria, total, and hydrogenotrophic methanogens archaea (HMA) concentrations using quantitative polymerase chain reaction and population biodiversity using denaturing gradient gel electrophoresis (DGGE). Incubation time reduced the titers of total bacteria and archaea (P 0.05), whereas at 10% Co inoculation, titers decreased constantly. Most of the archaeal DGGE bands were observed in all samples, suggesting a common microbial population origin but Co-i supply altered the DGGE structure of archaea populations. ; This work was supported by the Ministry of Economy and Competitiveness of Spain and the European Union Regional Development Funds (AGL2010‐20820). Ahmad Reza Seradj is a recipient of grant from the Government of Catalunya (FI‐DGR 2011) and Henris Morazan was a recipient of grant from MAEC‐AECID 2009–2011. ; Peer Reviewed

Ruminants contribute to the emissions of greenhouse gases, in particular methane, due to the microbial anaerobic fermentation of feed in the rumen. The rumen simulation technique was used to investigate the effects of the addition of different supplemental plant oils to a high concentrate diet on ruminal fermentation and microbial community composition. The control (CTR) diet was a high-concentrate total mixed ration with no supplemental oil. The other experimental diets were supplemented with olive (OLV), sunflower (SFL) or linseed (LNS) oils at 6%. Rumen digesta was used to inoculate the fermenters, and four fermentation units were used per treatment. Fermentation end-products, extent of feed degradation and composition of the microbial community (qPCR) in digesta were determined. Compared with the CTR diet, the addition of plant oils had no significant (P > 0.05) effect on ruminal pH, substrate degradation, total volatile fatty acids or microbial protein synthesis. Gas production from the fermentation of starch or cellulose were decreased by oil supplementation. Methane production was reduced by 21–28% (P < 0.001), propionate production was increased (P < 0.01), and butyrate and ammonia outputs and the acetate to propionate ratio were decreased (P < 0.001) with oil-supplemented diets. Addition of 6% OLV and LNS reduced (P < 0.05) copy numbers of total bacteria relative to the control. In conclusion, the supplementation of ruminant diets with plant oils, in particular from sunflower or linseed, causes some favorable effects on the fermentation processes. The addition of vegetable oils to ruminant mixed rations will reduce methane production increasing the formation of propionic acid without affecting the digestion of feed in the rumen. Adding vegetable fats to ruminant diets seems to be a suitable approach to decrease methane emissions, a relevant cleaner effect that may contribute to alleviate the environmental impact of ruminant production. ; This work was supported by the Consejería de Educación, Junta de Castilla y León (research project LE007A07); and the Government of Spain (CICYT project AGL2005-04760-C02-02).

13 páginas, 4 figuras, 1 tabla. ; Recent evidence suggests that changes in microbial colonization of the rumen prior to weaning may imprint the rumen microbiome and impact phenotypes later in life. We investigated how dietary manipulation from birth influences growth, methane production, and gastrointestinal microbial ecology. At birth, 18 female Holstein and Montbéliarde calves were randomly assigned to either treatment or control (CONT). Treatment was 3-nitrooxypropanol (3-NOP), an investigational anti-methanogenic compound that was administered daily from birth until three weeks post-weaning (week 14). Samples of rumen fluid and faecal content were collected at weeks 1, 4, 11, 14, 23, and 60 of life. Calves were tested for methane emissions using the GreenFeed system during the post-weaning period (week 11-23 and week 56-60 of life). Calf physiological parameters (BW, ADG and individual VFA) were similar across groups throughout the trial. Treated calves showed a persistent reduction in methane emissions (g CH4/d) throughout the post-weaning period up to at least 1 year of life, despite treatment ceasing three weeks post-weaning. Similarly, despite variability in the abundance of individual taxa across weeks, the rumen bacterial, archaeal and fungal structure differed between CONT and 3-NOP calves across all weeks, as visualised using sparse-PLS-DA. Similar separation was also observed in the faecal bacterial community. Interestingly, despite modest modifications to the abundance of rumen microbes, the reductive effect of 3-NOP on methane production persisted following cessation of the treatment period, perhaps indicating a differentiation of the ruminal microbial ecosystem or a host response triggered by the treatment in the early development phase. ; SM received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie Grant Agreement #658126. CS received a fellowship from the Fundación Alfonso Martín Escudero. This research was partially funded by the French National Research Agency (ANR) through the FACCE-JPI project RumenStability. The authors wish to thank Florence Fournier and personnel at the Her-bipole for animal care, and Dominique Graviou for laboratory technical support. We are grateful to the INRAE MIGALE bioinformatics platform (http://migal e.jouy.inra.fr) for providing computational resources ; Peer reviewed

Enteric methane (CH) production from cattle contributes to global greenhouse gas emissions. Measurement of enteric CH is complex, expensive, and impractical at large scales; therefore, models are commonly used to predict CH production. However, building robust prediction models requires extensive data from animals under different management systems worldwide. The objectives of this study were to (1) collate a global database of enteric CH production from individual lactating dairy cattle; (2) determine the availability of key variables for predicting enteric CH production (g/day per cow), yield [g/kg dry matter intake (DMI)], and intensity (g/kg energy corrected milk) and their respective relationships; (3) develop intercontinental and regional models and cross-validate their performance; and (4) assess the trade-off between availability of on-farm inputs and CH prediction accuracy. The intercontinental database covered Europe (EU), the United States (US), and Australia (AU). A sequential approach was taken by incrementally adding key variables to develop models with increasing complexity. Methane emissions were predicted by fitting linear mixed models. Within model categories, an intercontinental model with the most available independent variables performed best with root mean square prediction error (RMSPE) as a percentage of mean observed value of 16.6%, 14.7%, and 19.8% for intercontinental, EU, and United States regions, respectively. Less complex models requiring only DMI had predictive ability comparable to complex models. Enteric CH production, yield, and intensity prediction models developed on an intercontinental basis had similar performance across regions, however, intercepts and slopes were different with implications for prediction. Revised CH emission conversion factors for specific regions are required to improve CH production estimates in national inventories. In conclusion, information on DMI is required for good prediction, and other factors such as dietary neutral detergent fiber (NDF) concentration, improve the prediction. For enteric CH yield and intensity prediction, information on milk yield and composition is required for better estimation. ; This study is part of the Joint Programming Initiative on Agriculture, Food Security and Climate Change (FACCE‐JPI)'s "GLOBAL NETWORK" project and the "Feeding and Nutrition Network" (http://animalscience.psu.edu/fnn) of the Livestock Research Group within the Global Research Alliance for Agricultural Greenhouse Gases (www.globalresearchalliance.org). Authors gratefully acknowledge funding for this project from: USDA National Institute of Food and Agriculture Grant no. 2014‐67003‐21979) University of California, Davis Sesnon Endowed Chair Program, USDA, and Austin Eugene Lyons Fellowship (University of California, Davis); Funding from USDA National Institute of Food and Agriculture Federal Appropriations under Project PEN 04539 and Accession number 1000803, DSM Nutritional Products (Basel, Switzerland), Pennsylvania Soybean Board (Harrisburg, PA, USA), Northeast Sustainable Agriculture Research and Education (Burlington, VT, USA), and PMI Nutritional Additives (Shoreview, MN, USA); the Ministry of Economic Affairs (the Netherlands; project BO‐20‐007‐006; Global Research Alliance on Agricultural Greenhouse Gases), the Product Board Animal Feed (Zoetermeer, the Netherlands) and the Dutch Dairy Board (Zoetermeer, the Netherlands); USDA National Institute of Food and Agriculture (Hatch Multistate NC‐1042 Project Number NH00616‐R; Project Accession Number 1001855) and the New Hampshire Agricultural Experiment Station (Durham, NH); French National Research Agency through the FACCE‐JPI program (ANR‐13‐JFAC‐0003‐01), Agricultural GHG Research Initiative for Ireland (AGRI‐I), Academy of Finland (No. 281337), Helsinki, Finland; Swiss Federal Office of Agriculture, Berne, Switzerland; the Department for Environment, Food and Rural Affairs (Defra; UK); Defra, the Scottish Government, DARD, and the Welsh Government as part of the UK's Agricultural GHG Research Platform projects (www.ghgplatform.org.uk); INIA (Spain, project MIT01‐GLOBALNET‐EEZ); German Federal Ministry of Food and Agriculture (BMBL) through the Federal Office for Agriculture and Food (BLE); Swedish Infrastructure for Ecosystem Science (SITES) at Röbäcksdalen Research Station; Comisión Nacional de Investigación Científica y Tecnológica, Fondo Nacional de Desarrollo Científico y Tecnológico (Grant Nos. 11110410 and 1151355) and Fondo Regional de Tecnología Agropecuaria (FTG/RF‐1028‐RG); European Commission through SMEthane (FP7‐SME‐262270). The authors are thankful to all colleagues who contributed data to the GLOBAL NETWORK project and especially thank Luis Moraes, Ranga Appuhamy, Henk van Lingen, James Fadel, and Roberto Sainz for their support on data analysis. All authors read and approved the final manuscript. The authors declare that they have no competing interests. ; Peer Reviewed

The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages. These microbes interact closely to breakdown plant material that cannot be digested by humans, whilst providing metabolic energy to the host and, in the case of archaea, producing methane. Consequently, ruminants produce meat and milk, which are rich in high-quality protein, vitamins and minerals, and therefore contribute to food security. As the world population is predicted to reach approximately 9.7 billion by 2050, an increase in ruminant production to satisfy global protein demand is necessary, despite limited land availability, and whilst ensuring environmental impact is minimized. Although challenging, these goals can be met, but depend on our understanding of the rumen microbiome. Attempts to manipulate the rumen microbiome to benefit global agricultural challenges have been ongoing for decades with limited success, mostly due to the lack of a detailed understanding of this microbiome and our limited ability to culture most of these microbes outside the rumen. The potential to manipulate the rumen microbiome and meet global livestock challenges through animal breeding and introduction of dietary interventions during early life have recently emerged as promising new technologies. Our inability to phenotype ruminants in a high-throughput manner has also hampered progress, although the recent increase in >omic> data may allow further development of mathematical models and rumen microbial gene biomarkers as proxies. Advances in computational tools, high-throughput sequencing technologies and cultivation-independent >omics> approaches continue to revolutionize our understanding of the rumen microbiome. This will ultimately provide the knowledge framework needed to solve current and future ruminant livestock challenges. ; SH, DM, MP, RM-T, SW, IT, HS, JE, SK, GA, and CC acknowledge the support of ERA-net gas co-fund for funding (Project name: RumenPredict). SH, HM and CC acknowledge support from BBSRC (BBL/L026716/1 and BBL/L026716/2) and a British Council Newton Institutional Links funding (Grant 172629373). IM acknowledges funding from the European Research Council under the European Union's Horizon 2020 research and innovation program (Grant 640384). JE acknowledges funding from an EU H2020 Marie Curie Fellowship (706899). CC, AK-S, and EH were supported by the Biotechnology and Biological Sciences Research Council (Grants BBS/OS/GC/000011B and BBS/E/W/0012843D). CN and OM acknowledge the support of the British Council Newton Institutional Links funding (Grant 216425215). SRUC receives financial support from the Scottish Government's Rural and Environment Science and Analytical Services Division (RESAS). RD and RR acknowledge financial support from the Biotechnology and Biological Sciences Research Council (BBSRC BB/N01720X/1). DY-R and AB acknowledge funding from MINECO, Spain (Grant AGL2017-86938-R). GS acknowledges funding from the U.S. Department of Agriculture National Institute of Food and Agriculture foundational (Grant 2015-67015-23246). EP acknowledges funding from CNPq (Grant 401590/2014-3). All authors are also members of the Global Research Alliance Rumen Microbial Genomics network. ; Peer Reviewed

Enteric methane (CH4 ) production from cattle contributes to global greenhouse gas emissions. Measurement of enteric CH4 is complex, expensive, and impractical at large scales; therefore, models are commonly used to predict CH4 production. However, building robust prediction models requires extensive data from animals under different management systems worldwide. The objectives of this study were to (1) collate a global database of enteric CH4 production from individual lactating dairy cattle; (2) determine the availability of key variables for predicting enteric CH4 production (g/day per cow), yield [g/kg dry matter intake (DMI)], and intensity (g/kg energy corrected milk) and their respective relationships; (3) develop intercontinental and regional models and cross-validate their performance; and (4) assess the trade-off between availability of on-farm inputs and CH4 prediction accuracy. The intercontinental database covered Europe (EU), the United States (US), and Australia (AU). A sequential approach was taken by incrementally adding key variables to develop models with increasing complexity. Methane emissions were predicted by fitting linear mixed models. Within model categories, an intercontinental model with the most available independent variables performed best with root mean square prediction error (RMSPE) as a percentage of mean observed value of 16.6%, 14.7%, and 19.8% for intercontinental, EU, and United States regions, respectively. Less complex models requiring only DMI had predictive ability comparable to complex models. Enteric CH4 production, yield, and intensity prediction models developed on an intercontinental basis had similar performance across regions, however, intercepts and slopes were different with implications for prediction. Revised CH4 emission conversion factors for specific regions are required to improve CH4 production estimates in national inventories. In conclusion, information on DMI is required for good prediction, and other factors such as dietary neutral detergent fiber (NDF) concentration, improve the prediction. For enteric CH4 yield and intensity prediction, information on milk yield and composition is required for better estimation.

© 2015 Macmillan Publishers Limited. Ruminant livestock are important sources of human food and global greenhouse gas emissions. Feed degradation and methane formation by ruminants rely on metabolic interactions between rumen microbes and affect ruminant productivity. Rumen and camelid foregut microbial community composition was determined in 742 samples from 32 animal species and 35 countries, to estimate if this was influenced by diet, host species, or geography. Similar bacteria and archaea dominated in nearly all samples, while protozoal communities were more variable. The dominant bacteria are poorly characterised, but the methanogenic archaea are better known and highly conserved across the world. This universality and limited diversity could make it possible to mitigate methane emissions by developing strategies that target the few dominant methanogens. Differences in microbial community compositions were predominantly attributable to diet, with the host being less influential. There were few strong co-occurrence patterns between microbes, suggesting that major metabolic interactions are non-selective rather than specific. ; We thank Ron Ronimus, Paul Newton, and Christina Moon for reading and commenting on the manuscript. We thank all who provided assistance that allowed Global Rumen Census collaborators to supply samples and metadata (Supplemental Text 1). AgResearch was funded by the New Zealand Government as part of its support for the Global Research Alliance on Agricultural Greenhouse Gases. The following funding sources allowed Global Rumen Census collaborators to supply samples and metadata, listed with the primary contact(s) for each funding source: Agencia Nacional de Investigación e Innovación, Martín Fraga; Alberta Livestock and Meat Agency, Canada, Tim A. McAllister; Area de Ciencia y Técnica, Universidad Juan A Maza (Resolución Proy. N° 508/2012), Diego Javier Grilli; Canada British Columbia Ranching Task Force Funding Initiative, John Church; CNPq, Hilário Cuquetto Mantovani, Luiz Gustavo Ribeiro Pereira; FAPEMIG, Hilário Cuquetto Mantovani; FAPEMIG, PECUS RumenGases, Luiz Gustavo Ribeiro Pereira; Cooperative Research Program for Agriculture Science & Technology Development (project number PJ010906), Rural Development Administration, Republic of Korea, Sang-Suk Lee; Dutch Dairy Board & Product Board Animal Feed, André Bannink, Kasper Dieho, Jan Dijkstra; Ferdowsi University of Mashhad, Vahideh Heidarian Miri; Finnish Ministry of Agriculture and Forestry, Ilma Tapio; Instituto Nacional de Tecnología Agropecuaria, Argentina (Project PNBIO1431044), Silvio Cravero, María Cerón Cucchi; Irish Department of Agriculture, Fisheries and Food, Alexandre B. De Menezes; Meat & Livestock Australia; and Department of Agriculture, Fisheries & Forestry (Australian Government), Chris McSweeney; Ministerio de Agricultura y desarrollo sostenible (Colombia), Olga Lucía Mayorga; Montana Agricultural Experiment Station project (MONB00113), Carl Yeoman; Multistate project W-3177 Enhancing the competitiveness of US beef (MONB00195), Carl Yeoman; NSW Stud Merino Breeders' Association, Alexandre Vieira Chaves; Queensland Enteric Methane Hub, Diane Ouwerkerk; RuminOmics, Jan Kopecny, Ilma Tapio; Rural and Environment Science and Analytical Services Division (RESAS) of the Scottish Government and the Technology Strategy Board, UK, R. John Wallace; Science Foundation Ireland (09/RFP/GEN2447), Sinead Waters; Secretaría de Agricultura, Ganadería, Desarrollo Rural, Pesca y Alimentación, Mario A. Cobos-Peralta; Slovenian Research Agency (project number J1-6732 and P4-0097), Blaz Stres; Strategic Priority Research Program, Climate Change: Carbon Budget and Relevant Issues (Grant No.XDA05020700), ZhiLiang Tan; The European Research Commission Starting Grant Fellowship (336355—MicroDE), Phil B. Pope; The Independent Danish Research Council (project number 4002-00036), Torsten Nygaard Kristensen; and The Independent Danish Research Council (Technology and Production, project number 11-105913), Jan Lassen. These funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. ; Peer Reviewed