Charolais crossbred cattle: The difference in energy sources and ages on nutrient digestibility and methane emission

The climate impact from the useof peat for energy production in Sweden hasbeen evaluated in terms of contribution toatmospheric radiative forcing. This wasdone by attempting to answer the question`What will be the climate impact if onewould use 1 m2 of mire for peatextraction during 20 years?'. Two differentmethods of after-treatment were studied:afforestation and restoration of wetland.The climate impact from a peatland –wetland scenario and a peatland –forestation – bioenergy scenario wascompared to the climate impact from coal,natural gas and forest residues.Sensitivity analyses were performed toevaluate which parameters that areimportant to take into consideration inorder to minimize the climate impact frompeat utilisation. In a `multiple generationscenario' we investigate the climate impactif 1 Mega Joule (MJ) of energy is produced every yearfor 300 years from peat compared to otherenergy sources.The main conclusions from the study are:•The accumulated radiative forcing from the peatland – forestation – bioenergy scenario over a long time perspective (300 years) is estimated to be 1.35 mJ/m2/m2 extraction area assuming a medium-high forest growth rate and medium original methane emissions from the virgin mire. This is below the corresponding values for coal 3.13 mJ/ m2/ m2 extraction area and natural gas, 1.71 mJ/ m2/ m2 extraction area, but higher than the value for forest residues, 0.42 mJ/ m2/ m2 extraction area. A `best-best-case' scenario, i.e. with high forest growth rate combined with high `avoided' methane (CH4) emissions, will generate accumulated radiative forcing comparable to using forest residues for energy production. A `worst-worst-case' scenario, with low growth rate and low `avoided' CH4 emissions, will generate radiative forcing somewhere in between natural gas and coal.•The accumulated radiative forcing from the peatland – wetland scenario over a 300-year perspective is estimated to be 0.73 –1.80 mJ/ m2/ m2 extraction area depending on the assumed carbon (C) uptake rates for the wetland and assuming a medium-high methane emissions from a restored wetland. The corresponding values for coal is 1.88 mJ/ m2/ m2 extraction area, for natural gas 1.06 mJ/ m2/ m2 extraction area and for forest residues 0.10 mJ/ m2/ m2 extraction area. A `best-best-case' scenario (i.e. with high carbon dioxide CO2-uptake combined with high `avoided' CH4 emissions and low methane emissions from the restored wetland) will generate accumulated radiative forcing that decreases and reaches zero after 240 years. A `worst-worst-case' (i.e. with low CO2-uptake combined with low `avoided' CH4 emissions and high methane emissions from the restored wetland) will generate radiative forcing higher than coal over the entire time period.•The accumulated radiative forcing in the `multiple generations' – scenarios over a 300-year perspective producing 1 MJ/year is estimated to be 0.089 mJ/ m2 for the scenario `Peat forestation – bioenergy', 0.097 mJ/ m2 for the scenario `Peat wetland with high CO2-uptake' and 0.140 mJ/ m2 for the scenario `Peat wetland with low CO2-uptake'. Corresponding values for coal is 0.160 mJ/ m2, for natural gas 0.083 mJ/ m2 and for forest residues 0.015 mJ/ m2. Using a longer time perspective than 300 years will result in lower accumulated radiative forcing from the scenario `Peat wetland with high CO2-uptake'. This is due to the negative instantaneous forcing that occurs after 200 years for each added generation.•It is important to consider CH4 emissions from the virgin mire when choosing mires for utilization. Low original methane emissions give significantly higher total climate impact than high original emissions do.•Afforestation on areas previously used for peat extraction should be performed in a way that gives a high forest growth rate, both for the extraction area and the surrounding area. A high forest growth rate gives lower climate impact than a low forest growth rate.•There are great uncertainties related to the data used for emissions and uptake of greenhouse gases in restored wetlands. The mechanisms affecting these emissions and uptake should be studied further.

Methane emissions along biomethane and biogas supply chains are underestimated

Methane emissions from ruminant livestock contribute significantly to the large environmental footprint of agriculture. The rumen is the principal source of methane, and certain features of the microbiome are associated with low/high methane phenotypes. Despite their primary role in methanogenesis, the abundance of archaea has only a weak correlation with methane emissions from individual animals. The composition of the archaeal community appears to have a stronger effect, with animals harbouring the Methanobrevibacter gottschalkii clade tending to be associated with greater methane emissions. Ciliate protozoa produce abundant H2, the main substrate for methanogenesis in the rumen, and their removal (defaunation) results in an average 11% lower methane emissions in vivo, but the results are not consistent. Different protozoal genera seem to result in greater methane emissions, though community types (A, AB, B and O) did not differ. Within the bacteria, three different ‘ruminotypes’ have been identified, two of which predispose animals to have lower methane emissions. The two low-methane ruminotypes are generally characterized by less abundant H2-producing bacteria. A lower abundance of Proteobacteria and differences in certain Bacteroidetes and anaerobic fungi seem to be associated with high methane emissions. Rumen anaerobic fungi produce abundant H2 and formate, and their abundance generally corresponds to the level of methane emissions. Thus, microbiome analysis is consistent with known pathways for H2 production and methanogenesis, but not yet in a predictive manner. The production and utilisation of formate by the ruminal microbiota is poorly understood and may be a source of variability between animals.

It is suggested that the measurement of methane production from enteric fermentation must be done under situations similar to that of typical farming methods. It is against this background that this study measured methane emission from goats on a farm to ascertain the real situation on most farms. The objective of this study was to measure performance and methane emission from goats fed Ghanaian ruminant diets comprising of basal diets supplemented with browse leaves and to determine the effects of temperature and humidity on methane emission. Ten West African dwarf goats (5 males and 5 females; average weight 14 kg ±1.01) were fed fifteen Ghanaian ruminant diets for four months. Each diet was randomly fed twice in 24 hours for 2 days in a month. Methane emission, temperature and humidity were measured using handheld gas methane detector. Completely randomized design was used. Dry matter intake (DMI) was lowest (P<0.05) when cassava (Manihot esculenta) peels were fed and highest (P<0.05) when plantain peels were supplemented with Moringa oleifera. Weight gain, DMI and methane emission from manure increased with time. The highest enteric methane emission was recorded (P<0.05) when untreated rice straw (749 ppm) was fed and the lowest was recorded (P<0.05) when Moringa oleifera leaves (313 ppm) were fed. High environmental temperature favored low methane emission and high humidity was associated with high methane emission. In conclusion, feeding browse leaves alone and browse supplementation with basal diets resulted in lower methane emission than feeding basal diets alone. Moderate weight gains were recorded. High environmental temperature was inversely related to methane emission and high environmental humidity was directly related to methane emission. It is recommended that, browse leaves be incorporated in the feed of ruminants, especially when environmental temperatures are low and humidity is high. Keywords: Basal diets, Browse leaves, Dry matter intake, Humidity, Temperature, Weight gain.

Natural gas (NG) is a promising alternative fuel to reduce exhaust emissions of greenhouse gases (GHG), particulate matter (PM) and nitrogen oxides (NOx) from heavy-duty (HD) vehicles. Past HD NG vehicle research has focused on the fuel consumption and exhaust emission of PM and NOx. Recent global warming concerns have raised interest in methane emissions from NG vehicles. However, there is currently no model available to estimate the methane emissions from HD NG vehicles. There is also a need to project the methane emissions of HD NG vehicles in 2035.;This research developed a scenario based estimation model for methane emissions of the heavy-duty transportation sector. The methane emissions sources considered include: tailpipe; crankcase; dynamic ventilation; fueling tank; and fueling stations. The main work conducted includes (1) processing experimental data and developing model input data; (2) estimating the population scenarios of the HD transportation sector in 2035, including HD NG vehicles and NG fuel stations; (3) developing operation characteristics for each type of vehicle; (4) developing a 2035 methane emissions and fuel consumption scenario; (5) developing, coding, and demonstrating the methane emissions estimation model; (6) estimating the methane emissions of the HD transportation sector in 2035. In this research, the methane emissions and fuel consumptions measured were statistically analyzed and characterized to fuel specific methane emissions (FSME) and distance specific fuel consumption for idle activity and three driving activities noted as city, arterial, and highway operation activities. The idle activity had methane emissions and fuel consumption characterized to FSME and time specific fuel consumption. With an input of the vehicle population and operation characteristics, the model was able to estimate the total fuel consumed and total methane emissions associated with tailpipes, crankcases, dynamic ventilation, on-board fuel storage tanks, and refueling stations. The total methane emissions and fuel consumption were further processed to calculate the FSME.;The estimation model was validated using the stasis scenario developed in this research. The model was validated by comparing the estimated FSME output with the input and verifying calculations. The contribution of tailpipes, crankcases, and fuel stations to the methane emissions of HD spark ignition (SI) CNG vehicles were 33.2%, 59.4%, and 7.4%, respectively, for the stasis scenario, representing current vehicle technology. The validated model was applied to estimate the methane emissions in the HD transportation sector with the high, medium and low methane emissions and fuel consumption scenarios. It was concluded that the total methane emissions

BackgroundMitigating the effects of global warming has become the main challenge for humanity in recent decades. Livestock farming contributes to greenhouse gas emissions, with an important output of methane from enteric fermentation processes, mostly in ruminants. Because ruminal microbiota is directly involved in digestive fermentation processes and methane biosynthesis, understanding the ecological relationships between rumen microorganisms and their active metabolic pathways is essential for reducing emissions. This study analysed whole rumen metagenome using long reads and considering its compositional nature in order to disentangle the role of rumen microbes in methane emissions.ResultsThe β-diversity analyses suggested a subtle association between methane production and overall microbiota composition (0.01 < R2 < 0.02). Differential abundance analysis identified 36 genera and 279 KEGGs as significantly associated with methane production (Padj < 0.05). Those genera associated with high methane production were Eukaryota from Alveolata and Fungi clades, while Bacteria were associated with low methane emissions. The genus-level association network showed 2 clusters grouping Eukaryota and Bacteria, respectively. Regarding microbial gene functions, 41 KEGGs were found to be differentially abundant between low- and high-emission animals and were mainly involved in metabolic pathways. No KEGGs included in the methane metabolism pathway (ko00680) were detected as associated with high methane emissions. The KEGG network showed 3 clusters grouping KEGGs associated with high emissions, low emissions, and not differentially abundant in either. A deeper analysis of the differentially abundant KEGGs revealed that genes related with anaerobic respiration through nitrate degradation were more abundant in low-emission animals.ConclusionsMethane emissions are largely associated with the relative abundance of ciliates and fungi. The role of nitrate electron acceptors can be particularly important because this respiration mechanism directly competes with methanogenesis. Whole metagenome sequencing is necessary to jointly consider the relative abundance of Bacteria, Archaea, and Eukaryota in the statistical analyses. Nutritional and genetic strategies to reduce CH4 emissions should focus on reducing the relative abundance of Alveolata and Fungi in the rumen. This experiment has generated the largest ONT ruminal metagenomic dataset currently available.

Large–squish piston geometry and early pilot injection for high efficiency and low methane emission in natural gas–diesel dual fuel engine at high–load operations

ABSTRACTTwo Italian rice (Oryza sativa var. japonica) cultivars, Lido and Roma, were tested in the field for methane production, oxidation and emission. In two consecutive years, fields planted with the rice cultivar Lido showed methane emissions 24–31% lower than fields planted with the cultivar Roma. This difference was observed irrespective of fertilizer treatment. In contrast to methane emissions, differences in methane production or oxidation were not observed between fields planted with the two cultivars. Plant‐mediated transport of methane from the sediment to the atmosphere was the dominating pathway of methane emission. During the entire vegetation period, the contribution of this pathway to total methane emission amounted to c. 90%, whereas the contribution of gas bubble release and of diffusion through the water column to total methane emission was of minor significance. Results obtained from transport studies of tracer gas through the aerenchyma system of rice plants demonstrated that the root–shoot transition zone is the main site of resistance to plant‐mediated gas exchange between the soil and the atmosphere. The cultivar Lido, showing relatively low methane emissions in the field, had a significantly lower gas transport capacity through the aerenchyma system than the cultivar Roma. Thus, the observed differences in methane emissions in the field between the cultivars Lido and Roma can be explained by different gas transport capacities. Apparently, these differences in gas transport capacities are a consequence of differences in morphology of the aerenchyma systems, especially in the root–shoot transition zone. It is, therefore, concluded that identification and use of high‐yielding rice cultivars which have a low gas transport capacity represent an economically feasible, environmentally sound and promising approach to mitigating methane emissons from rice paddy fields.

The COVID-19 outbreak has significantly affected global industrial and transportation markets. Airlines, rails, and cars’ industries and their supporting energy sectors have been substantially disrupted by the pandemic. This has resulted in undermined energy demand around the world during 2019 and 2020. The organization of the Petroleum Exporting Countries (OPEC) led by Saudi Arabia failed to persuade Russia to cutback oil supplies to deal with the loss of demand from the COVID-19 pandemic. On 8 March 2020, Saudi Arabia announced a raise in its oil production and offered a large discount on its crude oil sales. By April 2020, Saudi Arabia increased its oil production to about 12 million-oil barrels/day. This rise in oil production has not only resulted in the biggest fall in oil prices since the 1991 Gulf War but also increased methane emissions over the Gulf Cooperation Council (GCC) regions. Here, we report 2019 and 2020 data set of average seasonal methane-mixing ratio retrieved from TROPOspheric Monitoring Instrument (TROPOMI) on board of S5P spacecraft over 19 refineries and oil fields in Saudi Arabia, Kuwait, Oman, United Arab Emirates, Qatar, and Bahrain. Low methane emissions were recorded over western and central Saudi Arabia compared to the eastern side of the country. In general, high methane emissions were observed in 2020 compared to 2019 around oil refineries and fields in western, central, and eastern regions of Saudi Arabia as well as over other GCC countries. This could be attributed to the oil high production associated with the oil prices fluctuation during 2020.

Cattle production is one of the key contributors to global warming due to methane emission, which is a by-product of converting feed stuff into milk and meat for human consumption. Rumen hosts numerous microbial communities that are involved in the digestive process, leading to notable amounts of methane emission. The key factors underlying differences in methane emission between individual animals are due to, among other factors, both specific enrichments of certain microbial communities and host genetic factors that influence the microbial abundances. The detection of such factors involves various biostatistical and bioinformatics methods. In this study, our main objective was to reanalyze a publicly available data set using our proprietary Synomics Insights platform that is based on novel combinatorial network and machine learning methods to detect key metagenomic and host genetic features for methane emission and residual feed intake (RFI) in dairy cattle. The other objective was to compare the results with publicly available standard tools, such as those found in the microbiome bioinformatics platform QIIME2 and classic GWAS analysis. The data set used was publicly available and comprised 1,016 dairy cows with 16S short read sequencing data from two dairy cow breeds: Holstein and Nordic Reds. Host genomic data consisted of both 50 k and 150 k SNP arrays. Although several traits were analyzed by the original authors, here, we considered only methane emission as key phenotype for associating microbial communities and host genetic factors. The Synomics Insights platform is based on combinatorial methods that can identify taxa that are differentially abundant between animals showing high or low methane emission or RFI. Focusing exclusively on enriched taxa, for methane emission, the study identified 26 order-level taxa that combinatorial networks reported as significantly enriched either in high or low emitters. Additionally, a Z-test on proportions found 21/26 (81%) of these taxa were differentially enriched between high and low emitters (p value <.05). In particular, the phylum of Proteobacteria and the order Desulfovibrionales were found enriched in high emitters while the order Veillonellales was found to be more abundant in low emitters as previously reported for cattle (Wallace et al., 2015). In comparison, using the publicly available tool ANCOM only the order Methanosarcinales could be identified as differentially abundant between the two groups. We also investigated a link between host genome and rumen microbiome by applying our Synomics Insights platform and comparing it with an industry standard GWAS method. This resulted in the identification of genetic determinants in cows that are associated with changes in heritable components of the rumen microbiome. Only four key SNPs were found by both our platform and GWAS, whereas the Synomics Insights platform identified 1,290 significant SNPs that were not found by GWAS. Gene Ontology (GO) analysis found transcription factor as the dominant biological function. We estimated heritability of a core 73 taxa from the original set of 150 core order-level taxonomies and showed that some species are medium to highly heritable (0.25–0.62), paving the way for selective breeding of animals with desirable core microbiome characteristics. We identified a set of 113 key SNPs associated with >90% of these core heritable taxonomies. Finally, we have characterized a small set (<10) of SNPs strongly associated with key heritable bacterial orders with known role in methanogenesis, such as Desulfobacterales and Methanobacteriales.

BackgroundMethane represents 16 % of total anthropogenic greenhouse gas emissions. It has been estimated that ruminant livestock produce ca. 29 % of this methane. As individual animals produce consistently different quantities of methane, understanding the basis for these differences may lead to new opportunities for mitigating ruminal methane emissions. Metagenomics is a powerful new tool for understanding the composition and function of complex microbial communities. Here we have applied metagenomics to the rumen microbial community to identify differences in the microbiota and metagenome that lead to high- and low-methane-emitting cattle phenotypes.MethodsFour pairs of beef cattle were selected for extreme high and low methane emissions from 72 animals, matched for breed (Aberdeen-Angus or Limousin cross) and diet (high or medium concentrate). Community analysis was carried out by qPCR of 16S and 18S rRNA genes and by alignment of Illumina HiSeq reads to the GREENGENES database. Total genomic reads were aligned to the KEGG genes databasefor functional analysis.ResultsDeep sequencing produced on average 11.3 Gb per sample. 16S rRNA gene abundances indicated that archaea, predominantly Methanobrevibacter, were 2.5× more numerous (P = 0.026) in high emitters, whereas among bacteria Proteobacteria, predominantly Succinivibrionaceae, were 4-fold less abundant (2.7 vs. 11.2 %; P = 0.002). KEGG analysis revealed that archaeal genes leading directly or indirectly to methane production were 2.7-fold more abundant in high emitters. Genes less abundant in high emitters included acetate kinase, electron transport complex proteins RnfC and RnfD and glucose-6-phosphate isomerase. Sequence data were assembled de novo and over 1.5 million proteins were annotated on the subsequent metagenome scaffolds. Less than half of the predicted genes matched matched a domain within Pfam. Amongst 2774 identified proteins of the 20 KEGG orthologues that correlated with methane emissions, only 16 showed 100 % identity with a publicly available protein sequence.ConclusionsThe abundance of archaeal genes in ruminal digesta correlated strongly with differing methane emissions from individual animals, a finding useful for genetic screening purposes. Lower emissions were accompanied by higher Succinovibrionaceae abundance and changes in acetate and hydrogen production leading to less methanogenesis, as similarly postulated for Australian macropods. Large numbers of predicted protein sequences differed between high- and low-methane-emitting cattle. Ninety-nine percent were unknown, indicating a fertile area for future exploitation.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-2032-0) contains supplementary material, which is available to authorized users.

The objective of this study was to obtain (co)variance components, heritability, and genetic and phenotypic correlation estimates for enteric methane emission, residual feed intake, growth and carcass trait and reproductive indicators. Data from 146 feed efficiency trials with male and female Nellore cattle born between 2008 and 2023 from 146 herds in Central Brazil were analyzed. Trial data along with diet NDF content were used to estimate the methane emission intensity (g CH4/kg ADG) for each individual, using an equation developed by Medeiros et al., 2014: CH4 (g/d) = -0.1011 + 0.02062*DMI (kg/d) + 0.001648*NDF (% of DMI). Other data included pedigree information, body weight, carcass traits and reproductive indicator traits. Numbers of records varied from 3,869 (methane) to 42,840 (carcass data). Continuous traits were analyzed using a linear animal model. Two-trait analyses were performed using the restricted maximum likelihood to estimate the variance components, heritabilities and genetic and phenotypic correlations among traits. The estimated heritability of methane emissions was 0.117 ± 0.025. The genetic correlations of methane emissions with most performance and reproductive traits were low and not different from zero: BW at 240 d (0.019 ± 0.0003), BW at 450 d (0.022 ± 0.0003), ribeye area (-0.077 ± 0.098), rib fat (-0.020 ± 0.094), rump fat (0.091 ± 0.089), intramuscular fat % (-0.008 ±0.109), scrotal circumference (0.015 ± 0.0004), and age at first calving (0,072 ± 0,187), The same was true for early calving probability (-0,139; -0,384, 0,106) and stayability (-0,079; -0,324, 0,166) (means and highest posterior density intervals). Exceptions were the moderate genetic correlations of methane emissions with DM intake (0.486 ± 0.018) and the high correlation of methane with residual feed intake (RFI; 0.808 ±0.015). Thus, selection to improve weaning and yearling weights and carcass traits would not affect methane emissions. Genetic selection to reduce methane emissions is feasible and would also reduce DMI and RFI. Conversely, selection to improve RFI can be used to identify animals with lower methane emissions. Medeiros, S. R, L. G. Barioni, A. Berndt, M. C. Freua, T. Z. Albertini, C. Costa Jr., and G. B. Feltrin (2014) Modeling enteric methane emission from beef cattle in Brazil: A proposed equation performed by principal component analyses and mixed modeling multiple regression. Anais, Livestock, Climate Change and Food Security Conference, Madrid.

Context Yields from Brazilian beef-production systems do not always match the expected potential of a forage-based beef-production system. This efficiency is dependent on adjustments of grazing intensity and supplement utilisation to achieve higher bodyweight gain and lower methane emission. Therefore, more studies are necessary to evaluate the association between pasture management and supplement doses. Aims The aim of the present study was to determine nutrient intake, nutrient digestibility, animal performance, carcass characteristics and enteric methane emissions of young Nellore bulls grazing Urochloa brizantha cv. Marandu pastures. Methods One hundred and forty-eight yearling bulls (230 ± 17 kg) were randomly assigned to a grazing-by-supplementation strategy that was designed to allocate three different sward heights with differing levels of supplementation during the wet season. Treatment combinations were (1) low sward height with high supplementation (LH-HS, 15-cm sward height and supplementation at 0.6% of bodyweight (BW)); (2) low height with moderate supplementation (LH-MS, 15 cm and 0.3% BW); (3) moderate height with moderate supplementation (MH-MS, 25 cm and 0.3% BW); (4) moderate height with low supplementation (MH-LS, 25 cm and 0.1% BW); (5) high height with low supplementation (HH-LS, 35 cm and 0.1% BW); and (6) high height with no supplementation (HH-WS, 35 cm). Key results Bulls in the HH groups had a greater herbage intake than did those in the LH groups (P &amp;lt; 0.01). Bulls in the LH-HS treatment resulted in a greater (P &amp;lt; 0.01) carcass average daily gain than that obtained with LH-MS, MH-LS or HH-WS treatment. Higher stocking rate with the LH treatment resulted in greater gains per hectare in terms of both BW and carcass (P &amp;lt; 0.01). Carcass yield was greater for bulls maintained with the LH-HS treatment (54.3% BW). Higher enteric methane emissions were observed from bulls under the HH treatments (P &amp;lt; 0.01). Conclusions Comparing carcass gains per hectare and low methane emissions, the present study indicated that pasture management towards a low sward height combined with 0.3% or 0.6% BW supplementation can result in a greater nutrient utilisation efficiency of bulls. Implications Results provided information to obtain better gains per animals and area, also decreasing methane emission of beef cattle production system.

We measured methane emissions over a two-year period (2006–08) from two 12 to 14-year-old created freshwater marshes in central Ohio, one initially planted and the other allowed to self-colonize. Overall, methane emissions in the two created wetlands were different (p < 0.05), with the plant self-colonized wetland having higher annual methane (median and mean) emissions of 19 and 68 g CH4-C m−2 y−1 than the planted wetland (6 and 17 g CH4-C m−2 y−1). Since hydrology and soil/water temperature were identical for the two wetlands, we hypothesize that differences in carbon accumulation due to higher net primary productivity in the self-colonized wetland may be causing higher methane emissions in that wetland. Net primary productivity in the self-colonized wetland was higher 7 out of 11 years prior to the study. Methane emissions from the created wetlands were lower than the average methane emission of 82 g CH4-C m−2 y−1 in a natural wetland in Ohio with similar hydrologic patterns. Methane emissions increased at a slower rate in the planted wetland (4 g CH4-C m−2 y−1) than in the self-colonized wetland (16 g CH4-C m−2 y−1) over a four-year period. Early methane emissions from created wetlands may depend as much or more on the methods used to create the wetlands, e.g. planting v. self colonization, as on their hydrogeomorphic conditions.

Ensiling grass with microbial inoculants is a promising strategy to enhance forage quality, animal performance, and environmental sustainability. This study evaluated the effects of a multi-strain inoculant (Lactobacillus plantarum, L. buchneri, Propionibacterium acidipropionici, and P. thoeni) on silage fermentation, nutrient digestibility, milk production, methane emissions, and rumen microbiota in dairy cows. In a 2 × 2 crossover design, 24 lactating Polish Holstein-Friesians were fed total mixed rations differing only in grass silage treated with or without inoculant. Inoculated silage had lower pH (4.56 vs. 5.06; p = 0.02) and higher crude protein (129 vs. 111 g/kgDM; p < 0.05). Cows fed inoculated silage showed higher ruminal propionate (28.3 vs. 26.3 mM; p = 0.03), reduced ammonia (7.61 vs. 8.67 mM; p = 0.02), and fewer protozoa (1.21 vs. 1.66 × 105/mL; p = 0.03). Nutrient digestibility improved (p < 0.05), while methane emissions declined both per cow (368 vs. 397 g/d; p = 0.01) and per kgDMI (15.1 vs. 16.5; p = 0.01). Milk yield increased (p = 0.04), and the fatty acid profile improved. Our study revealed that cows fed inoculated silage had higher nutrient digestibility, lower methane emissions, and microbial shifts in the rumen detected by 16S rRNA sequencing (p < 0.05).