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Automated measurements of the ratio of concentrations of methane and carbon dioxide, [CH 4 ]:[CO 2 ], in breath from individual animals (the so-called "sniffer technique") and estimated CO 2 production can be used to estimate CH 4 production, provided that CO 2 production can be reliably calculated. This would allow CH 4 production from individual cows to be estimated in large cohorts of cows, whereby ranking of cows according to their CH 4 production might become possible and their values could be used for breeding of low CH 4 -emitting animals. Estimates of CO 2 production are typically based on predictions of heat production, which can be calculated from body weight (BW), energy-corrected milk yield, and days of pregnancy. The objectives of the present study were to develop predictions of CO 2 production directly from milk production, dietary, and animal variables, and furthermore to develop different models to be used for different scenarios, depending on available data. An international dataset with 2,244 records from individual lactating cows including CO 2 production and associated traits, as dry matter intake (DMI), diet composition, BW, milk production and composition, days in milk, and days pregnant, was compiled to constitute the training dataset. Research location and experiment nested within research location were included as random intercepts. The method of CO 2 production measurement (respiration chamber [RC] or GreenFeed [GF]) was confounded with research location, and therefore excluded from the model. In total, 3 models were developed based on the current training dataset: model 1 ("best model"), where all significant traits were included; model 2 ("on-farm model"), where DMI was excluded; and model 3 ("reduced on-farm model"), where both DMI and BW were excluded. Evaluation on test dat sets with either RC data (n = 103), GF data without additives (n = 478), or GF data only including observations where nitrate, 3-nitrooxypropanol (3-NOP), or a combination of nitrate and 3-NOP were fed to the cows (GF+: n = 295), showed good precision of the 3 models, illustrated by low slope bias both in absolute values (-0.22 to 0.097) and in percentage (0.049 to 4.89) of mean square error (MSE). However, the mean bias (MB) indicated systematic overprediction and underprediction of CO 2 production when the models were evaluated on the GF and the RC test datasets, respectively. To address this bias, the 3 models were evaluated on a modified test dataset, where the CO 2 production (g/d) was adjusted by subtracting (where measurements were obtained by RC) or adding absolute MB (where measurements were obtained by GF) from evaluation of the specific model on RC, GF, and GF+ test datasets. With this modification, the absolute values of MB and MB as percentage of MSE became negligible. In conclusion, the 3 models were precise in predicting CO 2 production from lactating dairy cows., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Fermentation of pasture grasses and grains in the rumen of dairy cows and other ruminants produces methane as a by-product, wasting energy and contributing to the atmospheric load of greenhouse gasses. Many feeding trials in farmed ruminants have tested the impact of dietary components on feed efficiency, productivity and methane yield (MeY). Such diets remodel the rumen microbiome, altering bacterial, archaeal, fungal and protozoan populations, with an altered fermentation outcome. In dairy cows, some dietary grains can reduce enteric methane production. This is especially true of wheat, in comparison to corn or barley. Using a feeding trial of cows fed rolled wheat, corn or barley grain, in combination with hay and canola, we identified wheat-associated changes in the ruminal microbiome. Ruminal methane production, pH and VFA concentration data together with 16S rRNA gene amplicon sequences were used to compare ruminal bacterial and archaeal populations across diets. Differential abundance analysis of clustered sequences (OTU) identified members of the bacterial families Lachnospiraceae, Acidaminococcaceae, Eubacteriaceae, Prevotellaceae, Selenomonadaceae, Anaerovoracaceae and Fibrobacteraceae having a strong preference for growth in wheat-fed cows. Within the methanogenic archaea, (at >99% 16S rRNA sequence identity) the growth of Methanobrevibacter millerae was favoured by the non-wheat diets, while Methanobrevibacter olleyae was unaffected. From the wheat-preferring bacteria, correlation analysis found OTU strongly linked to reduced MeY, reduced pH and raised propionic acid levels. OTU from the genera Shuttleworthia and Prevotella_7 and especially Selenomonadaceae had high anti-methane correlations. An OTU likely representing (100% sequence identity) the fumarate-reducing, hydrogen-utilising, rumen bacterium Mitsuokella jalaludinii, had an especially high negative correlation coefficient (-0.83) versus MeY and moderate correlation (-0.6) with rumen pH, strongly suggesting much of the MeY suppression is due to reduced hydrogen availablity. Other OTU, representing as yet unknown species from the Selenomonadaceae family and the genera Prevotella_7, Fibrobacter and Syntrophococcus also had high to moderate negative MeY correlations, but low correlation with pH. These latter likely represent bacterial species able to reduce MeY without causing greater ruminal acidity, making them excellent candidates, provided they can be isolated, for development as anti-methane probiotics., Competing Interests: No authors have competing interests.

Selecting for lower methane (CH 4 ) emitting animals is one of the best approaches to reduce CH 4 given that genetic progress is permanent and cumulative over generations. As genetic selection requires a large number of animals with records and few countries actively record CH 4 , combining data from different countries could help to expedite accurate genetic parameters for CH 4 traits and build a future genomic reference population. Additionally, if we want to include CH 4 in the breeding goal, it is important to know the genetic correlations of CH 4 traits with other economically important traits. Therefore, the aim of this study was first to estimate genetic parameters of 7 suggested methane traits, as well as genetic correlations between methane traits and production, maintenance, and efficiency traits using a multicountry database. The second aim was to estimate genetic correlations within parities and stages of lactation for CH 4 . The third aim was to evaluate the expected response of economically important traits by including CH 4 traits in the breeding goal. A total of 15,320 methane production (MeP, g/d) records from 2,990 cows belonging to 4 countries (Canada, Australia, Switzerland, and Denmark) were analyzed. Records on dry matter intake (DMI), body weight (BW), body condition score, and milk yield (MY) were also available. Additional traits such as methane yield (MeY; g/kg DMI), methane intensity (MeI; g/kg energy-corrected milk), a genetic standardized methane production, and 3 definitions of residual methane production (g/d), residual feed intake, metabolic BW (MBW), BW change, and energy-corrected milk were calculated. The estimated heritability of MeP was 0.21, whereas heritability estimates for MeY and MeI were 0.30 and 0.38, and for the residual methane traits heritability ranged from 0.13 to 0.16. Genetic correlations between different methane traits were moderate to high (0.41 to 0.97). Genetic correlations between MeP and economically important traits ranged from 0.29 (MY) to 0.65 (BW and MBW), being 0.41 for DMI. Selection index calculations showed that residual methane had the most potential for inclusion in the breeding goal when compared with MeP, MeY, and MeI, as residual methane allows for selection of low methane emitting animals without compromising other economically important traits. Inclusion of residual feed intake in the breeding goal could further reduce methane, as the correlation with residual methane is moderate and elicits a favorable correlated response. Adding a negative economic value for methane could facilitate a substantial reduction in methane emissions while maintaining an increase in milk production., (The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).)

There has been considerable interest in the use of red seaweed, and in particular Asparagopsis taxiformis, to increase production of cattle and to reduce greenhouse gas emissions. We hypothesized that feeding seaweed or seaweed derived products would increase beef or dairy cattle performance as indicated by average daily gain (ADG), feed efficiency measures, milk production, and milk constituents, and reduce methane emissions. We used meta-analytical methods to evaluate these hypotheses. A comprehensive search of Google Scholar, Pubmed and ISI Web of Science produced 14 experiments from which 23 comparisons of treatment effects could be evaluated. Red seaweed (Asparagopsis taxiformis) and brown seaweed (Ascophyllum nodosum) were the dominant seaweeds used. There were no effects of treatment on ADG or dry matter intake (DMI). While there was an increase in efficiency for feed to gain by 0.38 kg per kg [standardized mean difference (SMD) = 0.56; P = 0.001] on DerSimonian and Laird (D&L) evaluation, neither outcome was significant using the more rigorous robust regression analysis (P >0.06). The type of seaweed used was not a significant covariable for ADG and DMI, but A. nodosum fed cattle had lesser feed to gains efficiency compared to those fed A. taxiformis. Milk production was increased with treatment on weighted mean difference (WMD; 1.35 ± 0.44 kg/d; P <0.001); however, the SMD of 0.45 was not significant (P = 0.111). Extremely limited data suggest the possibility of increased percentages of milk fat (P = 0.040) and milk protein (P = 0.001) on (D&L) WMD evaluation. The limited data available indicate dietary supplementation with seaweed produced a significant and substantial reduction in methane yield by 5.28 ± 3.5 g/kg DMI (P = 0.003) on D&L WMD evaluation and a D&L SMD of -1.70 (P = 0.001); however, there was marked heterogeneity in the results (I2 > 80%). In one comparison, methane yield was reduced by 97%. We conclude that while there was evidence of potential for benefit from seaweed use to improve production and reduce methane yield more in vivo experiments are required to strengthen the evidence of effect and identify sources of heterogeneity in methane response, while practical applications and potential risks are evaluated for seaweed use., Competing Interests: The authors have declared that no competing interests exist.

Background: Marked increases in atmospheric CO 2 concentrations are largely associated with the release of sequestered carbon in fossil fuels. While emissions of green-house gasses (GHG) from cattle have significant global warming potential, these are biogenic sources and substantially involve carbon in natural cycles, rather than fossil fuel. Cattle use human inedible feeds and by-products of human food production to produce nutrient-dense foods of great value to humans., Interventions to Reduce Ghg Production: Reductions in land clearing and burning of grasslands and increased carbon sequestration in soils and trees have potential to substantially reduce GHG emissions. Increased efficiencies of production through intensified feeding and enteric modification have markedly reduced intensity of GHG emissions for cattle in Australia. Genetic selection for lower emissions has modest, but cumulative potential to reduce GHG (mostly CH 4 ) emissions and intensity. Improved reproductive performance can reduce intensity of GHG emissions, especially in beef production. Feeds and technologies that reduce GHG production and intensity include improved pastures, grain feeding, dietary lipids, nitrates, ionophores, seaweed, 3-NOP, hormonal growth promotants in beef, and improved diets for peri-parturient dairy cattle. There is considerable potential to further reduce emissions from cattle using the technologies reviewed., Interventions to Reduce Heat Stress: Cattle are susceptible to heat stress and ameliorating interventions include tree and shelter belts, shade, housing, cooling with fans and water and dietary manipulations., Conclusions: Numerous interventions can reduce GHG emissions and intensity from cattle. There are opportunities to increase carbon capture and maintain biodiversity in Australia's extensive rangelands, but these require quantification and application. We can reduce the intensity of CH 4 emissions for cattle in Australia and simultaneously improve their well-being., (© 2021 Australian Veterinary Association.)

Methane is a greenhouse gas of high interest to the dairy industry, with 57% of Australia's dairy emissions attributed to enteric methane. Enteric methane emissions also constitute a loss of approximately 6.5% of ingested energy. Genetic selection offers a unique mitigation strategy to decrease the methane emissions of dairy cattle, while simultaneously improving their energy efficiency. Breeding objectives should focus on improving the overall sustainability of dairy cattle by reducing methane emissions without negatively affecting important economic traits. Common definitions for methane production, methane yield, and methane intensity are widely accepted, but there is not yet consensus for the most appropriate method to calculate residual methane production, as the different methods have not been compared. In this study, we examined 9 definitions of residual methane production. Records of individual cow methane, dry matter intake (DMI), and energy corrected milk (ECM) were obtained from 379 animals and measured over a 5-d period from 12 batches across 5 yr using the SF 6 tracer method and an electronic feed recording system, respectively. The 9 methods of calculating residual methane involved genetic and phenotypic regression of methane production on a combination of DMI and ECM corrected for days in milk, parity, and experimental batch using phenotypes or direct genomic values. As direct genomic values (DGV) for DMI are not routinely evaluated in Australia at this time, DGV for FeedSaved, which is derived from DGV for residual feed intake and estimated breeding value for bodyweight, were used. Heritability estimates were calculated using univariate models, and correlations were estimated using bivariate models corrected for the fixed effects of year-batch, days in milk, and lactation number, and fitted using a genomic relationship matrix. Residual methane production candidate traits had low to moderate heritability (0.10 ± 0.09 to 0.21 ± 0.10), with residual methane production corrected for ECM being the highest. All definitions of residual methane were highly correlated phenotypically (>0.87) and genetically (>0.79) with one another and moderately to highly with other methane candidate traits (>0.59), with high standard errors. The results suggest that direct selection for a residual methane production trait would result in indirect, favorable improvement in all other methane traits. The high standard errors highlight the importance of expanding data sets by measuring more animals for their methane emissions and DMI, or through exploration of proxy traits and combining data via international collaboration., (The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).)

Addition of fats to the diets of ruminants has long been known to result in a reduction in enteric methane emissions. Tannins have also been used to reduce methane emissions but with mixed success. However, the effect of feeding fat in combination with tannin is unknown. Eight ruminally cannulated Holstein-Friesian cows were fed four diets in a double Latin-square, full crossover sequence. The treatments were 800 ml/day of water (CON), 800 g/day of cottonseed oil, 400 g/day of tannin, and 800 g/day of cottonseed oil and 400 g/day of tannin in combination (fat- and tannin-supplemented diet). Methane emissions were measured using open-circuit respiration chambers. Intake of basal diets was not different between treatments. Cows fed cottonseed oil had greater milk yield (34.9 kg/day) than those fed CON (32.3 kg/day), but the reduced concentration of milk fat meant there was no difference in energy-corrected milk between treatments. Methane yield was reduced when either cottonseed oil (14%) or tannin (11%) was added directly to the rumen, and their effect was additive when given in combination (20% reduction). The mechanism of the anti-methanogenic effect remains unclear but both fat and tannin appear to cause a reduction in fermentation in general rather than cause a change in the type of fermentation.

Wheat is the most common concentrate fed to grazing dairy cows in Australia, but no studies have examined the effects of wheat proportion in a pasture-based diet on milk production and methane emissions. In this 47-d experiment, 32 Holstein dairy cows were offered 1 of 4 diets during d 1 to 36. Cows in each of the dietary treatment groups were individually offered no wheat (W0) or wheat at 3 kg of dry matter (DM)/d (W3), 6 kg of DM/d (W6), or 9 kg of DM/d (W9). The remainder of the diet was 2.2 kg of DM of concentrate mix and freshly harvested perennial ryegrass (Lolium perenne) such that all individual cows were offered a total diet of approximately 20.2 kg of DM/d. From d 37 to 47 the diets of cows receiving treatments W0 and W3 remained unchanged, but cows in treatments W6 and W9 received the W3 diet. Individual cow feed intakes, milk yields, milk compositions, and methane emissions were measured for d 31 to 35 (period 1) and d 45 to 47 (period 2). During period 1, the mean intakes of cows offered the W0, W3, W6, and W9 diets were 19.2, 20.4, 20.2, and 19.8 kg of DM/d. Diet caused differences in energy-corrected milk, and means for W0, W3, W6, and W9 were 29.5, 32.4, 33.0, and 32.9 kg/d, respectively. Milk fat percentage differed with respective means of 3.93, 3.94, 3.69, and 3.17. Diets also caused differences in methane emissions, with means for W0, W3, W6, and W9 of 440, 431, 414, and 319 g/d. During period 1, the cows fed the W9 diet produced less methane and had lower methane yields (g/kg of DMI) and intensities (g/kg of energy-corrected milk) than cows fed the W3 diet. However, in period 2 when the wheat intake of cows in the W9 treatment was reduced to the same level as in the W3 treatment, their methane emissions, yields, and intensities were similar to those offered the W3 treatment, yet protozoa numbers in ruminal fluid were still much lower than those in cows offered the W3 treatment. Our research shows that for diets based on perennial ryegrass and crushed wheat, only the diet containing more than 30% crushed wheat resulted in substantially depressed milk fat concentration and reduced methane emissions, methane yield, and methane intensity. Thus, although feeding a diet with a high proportion of wheat can cause substantial methane mitigation, it can come at the cost of depression in milk fat concentration., (Copyright © 2020 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

There is a need to quantify methane (CH 4 ) emissions with alternative methods. For the past decade, milk fatty acids (MFA) could be used as proxies to predict CH 4 emissions from dairy cows because of potential common rumen biochemical pathways. However, equations have been developed based on a narrow range of diets and with limited data. The objectives of this study were to (1) construct a set of empirical models based on individual data of CH 4 emissions and MFA from a large number of lactating dairy cows fed a wide range of diets; (2) further increase the models' level of complexity (from farm to research level) with additional independent variables such as dietary chemical composition (organic matter, neutral detergent fiber, crude protein, starch, and ether extract), dairy performance (milk yield and composition), and animal characteristics (days in milk or body weight); and (3) evaluate the performance of the developed models on independent data sets including measurements from individual animals or average measurements of groups of animals. Prediction equations based only on MFA [C10:0, iso C17:0 + trans-9 C16:1,cis-11 C18:1, and trans-11,cis-15 C18:2 for CH 4 production (g/d); iso C16:0, cis-11 C18:1, trans-10 C18:1, and cis-9,cis-12 C18:2 for CH 4 yield (g/kg of dry matter intake, DMI); and iso C16:0, cis-15 C18:1, and trans-10 + trans-11 C18:1 for CH 4 intensity (g/kg of milk)] had a root mean squared error of 65.1 g/d, 2.8 g/kg of DMI, and 2.9 g/kg of milk, respectively, whereas complex equations that additionally used DMI, dietary neutral detergent fiber, ether extract, days in milk, and body weight had a lower root mean squared error of 46.6 g/d, 2.6 g/kg of DMI, and 2.7 g/kg of milk, respectively). External evaluation with individual or mean data not used for equation development led to variable results. When evaluations were performed using individual cow data from an external data set, accurate predictions of CH 4 production (g/d) were obtained using simple equations based on MFA. Better performance was observed on external evaluation with individual data for the simple equation of CH 4 production (g/d, based on MFA), whereas better performance was observed on external evaluation mean data for the simple equation of CH 4 yield (g/kg of DMI). The performance of evaluation of the models is dependent on the domain of validity of the evaluation data sets used (individual or mean)., (The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).)

Background: Supplementation of ruminant diets with wheat and corn grains influences ruminal fermentation. In vitro fermentation is a methodology that can be used to screen feeds for their potential to produce enteric methane. However, there is evidence that the diet of the donor cows could impact the results of in vitro analysis. This research investigated the in vitro fermentation of wheat and corn grain when incubated in ruminal fluid from cows fed different grain types and different forage-to-grain ratios., Results: The type of grain fed to the donor cows, as well as forage-to-grain ratio, affected the outcome of fermentation of wheat and corn grain. Differences in methane production (MP) between grains were only observed when incubated with ruminal fluid adapted to each specific grain type. Increasing proportions of wheat but not of corn decreased in vitro MP in a linear manner compared with MP produced from forage only., Conclusions: Wheat grain has a greater in vitro antimethanogenic effect than corn. However, to detect the different fermentations between wheat and corn, grains should be incubated in ruminal fluid from cows adapted to that specific grain type. © 2019 Society of Chemical Industry., (© 2019 Society of Chemical Industry.)

Diets that contain high proportions of either wheat or supplementary fat have been individually reported to reduce enteric methane production. The objective of this research was to determine the effect of dietary fat supplementation on methane emissions and milk yield from cows fed diets containing either corn or wheat grains. It was hypothesized that cows fed a diet containing wheat would produce less methane and have lower methane yield (methane per kg of dry matter intake; MY) than cows fed a diet containing corn and that methane mitigation from fat supplementation would occur irrespective of the type of grain in the basal diet. The experiment involved 32 Holstein-Friesian dairy cows allocated to 1 of 4 treatment groups (n = 8) and individually fed different diets restricted to approximately 90% of their mean ad libitum intake measured during a covariate period. All animals were offered 11.5 kg of dry matter/d of alfalfa hay, 1.8 kg of dry matter/d of solvent-extracted canola meal, and 1 of 4 dietary supplements. Dietary supplements were 8 kg of dry matter/d of either corn or wheat, or these same treatments with the addition of 0.8 kg of canola oil. In this 5-wk experiment, d 1 to 7 served as the covariate period, d 8 to 14 as the transition period, d 15 to 28 as the adaptation period, and d 29 to 35 as the experimental period. Cows were fed their full treatment diets from d 15 to 35 during which time milk production and feed intake were measured daily. During d 29 to 35, methane production was measured for individual cows daily using the sulfur hexafluoride tracer method. The resulting averages for milk production and feed intake were analyzed by analysis of covariance with factorial grain by fat as treatment structure, animal as the unit within blocks, and the corresponding milk production or feed intake covariate averages as principal covariate. Data on milk fatty acids, ruminal fluid data on pH, ammonia, volatile fatty acids, protozoa, and methane were analyzed by ANOVA using the same treatment and blocking structures excluding the principal covariate. Cows fed a diet containing wheat had greater MY than cows fed a diet containing corn. Irrespective of the type of grain in the diet, increasing the fat concentration from 2 to 6% dry matter reduced MY. It is concluded that the grain component in the basal diet does not affect the mitigating effects of dietary fat supplements on MY., (Copyright © 2019 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Background: There are several methods for estimating methane production (MP) from feedstuffs in vented in vitro systems. One method (A; 'gold standard') measures methane proportions in the incubation bottle's headspace (HS) and in the vented gas collected in gas bags. Four other methods (B, C, D and E) measure methane proportion in a single gas sample from the HS. Method B assumes the same methane proportion in the vented gas as in the HS, method C assumes constant methane to carbon dioxide ratio, method D has been developed based on empirical data, and method E assumes constant individual venting volumes. This study aimed to compare the MP predictions from these methods to that of the gold standard method under different incubation scenarios, to validate these methods based on their concordance with a gold-standard method., Results: Methods C, D and E had greater concordance (0.85, 0.88 and 0.81), lower root-mean-square error (RMSE; 0.80, 0.72 and 0.85) and lower mean bias (0.20, 0.35, -0.35) with the gold standard than did method B (concordance 0.67, RMSE 1.49 and mean bias 1.26). Methods D and E were simpler to perform than method C, and method D was slightly more accurate than method E., Conclusion: Based on precision, accuracy and simplicity of implementation, it is recommended that, when method A cannot be used, methods D and E are preferred to estimate MP from vented in vitro systems. © 2018 Society of Chemical Industry., (© 2018 Society of Chemical Industry.)

Enteric methane (CH 4 ) production from cattle contributes to global greenhouse gas emissions. Measurement of enteric CH 4 is complex, expensive, and impractical at large scales; therefore, models are commonly used to predict CH 4 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 4 production from individual lactating dairy cattle; (2) determine the availability of key variables for predicting enteric CH 4 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 4 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 4 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 4 emission conversion factors for specific regions are required to improve CH 4 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 4 yield and intensity prediction, information on milk yield and composition is required for better estimation., (© 2018 John Wiley & Sons Ltd.)

Short-term studies have shown that feeding dairy cows diets containing a high proportion (>40%) of wheat may result in reduced milk fat concentration and reduced CH 4 emissions (g of CH 4 /cow per d), but no long-term studies have been done on these responses. This study compared the milk production and CH 4 responses when 24 dairy cows were fed diets containing high proportions of either wheat or corn over 16 wk. Cows were assigned to 2 groups and offered a diet (CRN) containing 10.0 kg of dry matter/d of crushed corn grain, 1.8 kg of dry matter/d of canola meal, 0.2 kg of dry matter/d of minerals, and 11.0 kg of dry matter/d of chopped alfalfa hay or a similar diet (WHT) in which wheat replaced the corn. Dry matter intake and milk yields of individual cows were measured daily. Methane emissions from individual cows were measured using controlled climate respiration chambers over 2 consecutive days during each of wk 4, 10, and 16. Milk composition was measured on the 2 d when cows were in chambers during wk 4, 10, and 16. Over the 16-wk experimental period, total dry matter intake remained relatively constant and similar for the 2 dietary treatment groups. At wk 4, CH 4 emission, CH 4 yield (g of CH 4 /kg of dry matter intake), milk fat yield, and milk fat concentration were substantially less in cows fed the WHT diet compared with the same metrics in cows fed the CRN diet; but these differences were not apparent at wk 10 and 16. The responses over time in these metrics were not similar in all cows. In 4 cows fed the WHT diet, CH 4 yield, milk fat concentration, and milk fat yield remained relatively constant from wk 4 to 16, whereas for 5 fed the WHT diet, their CH 4 emissions, milk fat yields, and milk fat concentrations almost doubled between wk 4 and 16. In the short term (4 wk), the inclusion of approximately 45% wheat instead of corn in the diet of cows resulted in reductions of 39% in CH 4 yield, 35% in milk fat concentration, and 40% in milk fat yield. However, these reductions did not persist to wk 10 or beyond. Our data indicate that cows do not all respond in the same way with some "adaptive" cows showing a marked increase in CH 4 yield, milk fat concentration, and milk fat yield after wk 4, whereas in other "nonadaptive" cows, these metrics were persistently inhibited to 16 wk. This research shows that short-term studies on dietary interventions to mitigate enteric CH 4 emissions may not always predict the long-term effects of such interventions., (Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Ruminant production systems are important contributors to anthropogenic methane (CH 4 ) emissions, but there are large uncertainties in national and global livestock CH 4 inventories. Sources of uncertainty in enteric CH 4 emissions include animal inventories, feed dry matter intake (DMI), ingredient and chemical composition of the diets, and CH 4 emission factors. There is also significant uncertainty associated with enteric CH 4 measurements. The most widely used techniques are respiration chambers, the sulfur hexafluoride (SF 6 ) tracer technique, and the automated head-chamber system (GreenFeed; C-Lock Inc., Rapid City, SD). All 3 methods have been successfully used in a large number of experiments with dairy or beef cattle in various environmental conditions, although studies that compare techniques have reported inconsistent results. Although different types of models have been developed to predict enteric CH 4 emissions, relatively simple empirical (statistical) models have been commonly used for inventory purposes because of their broad applicability and ease of use compared with more detailed empirical and process-based mechanistic models. However, extant empirical models used to predict enteric CH 4 emissions suffer from narrow spatial focus, limited observations, and limitations of the statistical technique used. Therefore, prediction models must be developed from robust data sets that can only be generated through collaboration of scientists across the world. To achieve high prediction accuracy, these data sets should encompass a wide range of diets and production systems within regions and globally. Overall, enteric CH 4 prediction models are based on various animal or feed characteristic inputs but are dominated by DMI in one form or another. As a result, accurate prediction of DMI is essential for accurate prediction of livestock CH 4 emissions. Analysis of a large data set of individual dairy cattle data showed that simplified enteric CH 4 prediction models based on DMI alone or DMI and limited feed- or animal-related inputs can predict average CH 4 emission with a similar accuracy to more complex empirical models. These simplified models can be reliably used for emission inventory purposes., (The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).)

Almond hulls and citrus pulp have been fed to dairy cows with variable responses for milk production, but no information exists on their effect on enteric methane emissions. This experiment examined the effects of dietary supplementation with either almond hulls or ensiled citrus pulp on the milk yield, milk composition, and enteric methane emissions of dairy cows. Thirty-two Holstein dairy cows in mid lactation were offered 1 of 3 diets over a 28-d experiment. Twelve cows received a control (CON) diet, 10 cows a diet containing almond hulls (ALH), and 10 cows a diet containing ensiled citrus pulp (CIT). All cows were offered 6.0 kg of dry matter (DM)/d of crushed corn, 2.0 kg of DM/d of cold-pressed canola, and 0.2 kg of DM/d of a mineral mix. In addition, cows fed the CON diet were offered 14.5 kg of DM/d of alfalfa cubes; cows fed the ALH diet were offered 10.5 kg of DM/d of alfalfa cubes and 4.0 kg of DM/d of almond hulls; and cows on the CIT diet were offered 11.5 kg of DM/d of alfalfa cubes and 3.0 kg of DM/d of ensiled citrus pulp. Milk yield was measured daily and milk composition was measured on 4 d of each week. Individual cow methane emissions were measured by a sulfur hexafluoride tracer technique on d 24 to 28 of the experiment. The mean milk yield of cows fed the CON diet (27.4 kg/d) was greater than the mean milk yield of cows fed the ALH diet (24.6 kg/cow per day), whereas the mean milk yield of cows fed the CIT diet (26.2 kg/cow per day) was not different from the mean milk yield from cows fed the other 2 diets. Dietary treatment did not influence the concentrations of milk fat, protein, and lactose or fat yields, but the mean protein yield from cows fed the CON diet (0.87 kg/d) was greater than that from cows fed the ALH diet (0.78 kg/d) but not different to those fed the CIT diet (0.85 kg/d). In general, we found no differences in the proportion of individual fatty acids in milk. The mean pH of ruminal fluid from cows offered the CON diet was not different to the pH in the ruminal fluids of cows offered the ALH or the CIT diets. The mean methane emissions (g/d) and yields (g/kg of DM intake) were not influenced by dietary treatment. These findings indicate that, although almond hulls and ensiled citrus pulp can be used as a low-cost feed supplement, almond hulls did negatively affect milk production and neither inhibited enteric methane emissions., (Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Wheat is the most common concentrate fed to dairy cows in Australia, but few studies have examined the effects of wheat feeding on enteric methane emissions, and no studies have compared the relative potencies of wheat, corn, and barley for their effects on enteric methane production. In this 35-d experiment, 32 Holstein dairy cows were offered 1 of 4 diets: a corn diet (CRN) of 10.0 kg of dry matter (DM)/d of single-rolled corn grain, 1.8 kg of DM/d of canola meal, 0.2 kg of DM/d of minerals, and 11.0 kg of DM/d of chopped alfalfa hay; a wheat diet (WHT) similar to the CRN diet but with the corn replaced by single-rolled wheat; a barley diet (SRB) similar to the CRN diet but with the corn replaced by single-rolled barley; and a barley diet (DRB) similar to the CRN diet but with the corn replaced by double-rolled barley. Individual cow feed intakes, milk yields, and milk compositions were measured daily but reported for the last 5 d of the experiment. During the last 5 d of the experiment, individual cow methane emissions were measured using the SF 6 tracer technique for all cows, and ruminal fluid pH was continuously measured by intraruminal sensors for 3 cows in each treatment group. The average DM intake of cows offered the CRN, WHT, SRB, and DRB diets was 22.2, 21.1, 22.6, and 22.6 kg/d. The mean energy-corrected milk of cows fed the WHT diet was less than that of cows fed the other diets. This occurred because the milk fat percentage of cows fed the WHT diet was significantly less than that of cows fed the other diets. The mean methane emissions and methane yields of cows fed the WHT diet were also significantly less than those of cows fed the other diets. Indeed, the CRN, SRB, and DRB diets were associated with 49, 73, and 78% greater methane emissions, respectively, compared with the emissions from the WHT diet. Methane yield was found to be most strongly related to the minimum daily ruminal fluid pH. This study showed that although the inclusion of wheat in the diet of dairy cows could be an effective strategy for substantially reducing their methane emissions, it also reduced their milk fat percentage and production of milk fat and energy-corrected milk., (Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

The objective of this study was to compare 2 commonly used techniques for measuring methane emissions from ruminant animals: the GreenFeed (GF) system and the sulfur hexafluoride (SF6) technique. The study was part of a larger experiment in which a methane inhibitor, 3-nitrooxypropanol, fed at 4 application rates (0, 40, 60, and 80 mg/kg of feed dry matter) decreased enteric methane emission by an average of 30% (measured by both GF and SF6) in a 12-wk experiment with 48 lactating Holstein cows fed a total mixed ration. The larger experiment used a randomized block design and was conducted in 2 phases (February to May, phase 1, and June to August, phase 2), with 2 sets of 24 cows in each phase. Using both GF and SF6 techniques, methane emission data were collected simultaneously during experimental wk 2, 6, and 12 (phase 1) and 2, 9, and 12 (phase 2), which corresponded to a total of 6 sampling periods. During each sampling period, 8 spot samples of gas emissions (staggered over a 3-d period) were collected from each cow using GF, as well as 3×24-h collections using the SF6 technique. Methane emission data were averaged per cow for the statistical analysis. The mean methane emission was 373 (standard deviation=96.3) and 405 (standard deviation=156) g/cow per day for GF and SF6, respectively. Coefficients of variation for the 2 methods were 25.8 and 38.6%, respectively; correlation and concordance between the 2 methods were 0.40 and 0.34, respectively. The difference in methane emission between the 2 methods (SF6 - GF) within treatment was from 46 to 144 and 24 to 27 g/d for phases 1 and 2, respectively. In the conditions of this experiment, the SF6 technique produced larger variability in methane emissions than the GF method. The overall difference between the 2 methods was on average about 8%, but was not consistent over time, likely influenced by barn ventilation and background methane and SF6 concentrations., (Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

A quarter of all anthropogenic methane emissions in the United States are from enteric fermentation, primarily from ruminant livestock. This study was undertaken to test the effect of a methane inhibitor, 3-nitrooxypropanol (3NOP), on enteric methane emission in lactating Holstein cows. An experiment was conducted using 48 cows in a randomized block design with a 2-wk covariate period and a 12-wk data collection period. Feed intake, milk production, and fiber digestibility were not affected by the inhibitor. Milk protein and lactose yields were increased by 3NOP. Rumen methane emission was linearly decreased by 3NOP, averaging about 30% lower than the control. Methane emission per unit of feed dry matter intake or per unit of energy-corrected milk were also about 30% less for the 3NOP-treated cows. On average, the body weight gain of 3NOP-treated cows was 80% greater than control cows during the 12-wk experiment. The experiment demonstrated that the methane inhibitor 3NOP, applied at 40 to 80 mg/kg feed dry matter, decreased methane emissions from high-producing dairy cows by 30% and increased body weight gain without negatively affecting feed intake or milk production and composition. The inhibitory effect persisted over 12 wk of treatment, thus offering an effective methane mitigation practice for the livestock industries.

Background: Ruminants produce large quantities of methane in their rumen as a by-product of microbial digestion of feed. Antibiotics are added to ruminant feed to reduce wasteful production of methane; however, this practice has some downsides. A search for safer and natural feed additives with anti-methanogenic properties is under way. The objective of this research was to examine selected feed additives, plant essential oils and plant extracts for their anti-methanogenic potential in the rumen using an in vitro batch fermentation system., Results: A significant reduction (P < 0.05) in methane production was observed with nine feed additives (up to 40% reduction), all eight essential oils (up to 75% reduction) and two plant extracts (14% reduction) when compared to their respective controls. Amongst these, only an algal meal high in docosahexaenoic acid, preparations of Nannochloropsis oculata, calcareous marine algae, yeast metabolites and two tannins did not inhibit microbial gas and volatile acid production., Conclusions: The current study identified some potent dietary ingredients or plant compounds that can assist in developing novel feed additives for methane mitigation from the rumen., (© 2013 Society of Chemical Industry.)

Grape marc (the skins, seeds, stalk, and stems remaining after grapes have been pressed to make wine) is currently a by-product used as a feed supplement by the dairy and beef industries. Grape marc contains condensed tannins and has high concentrations of crude fat; both these substances can reduce enteric methane (CH4) production when fed to ruminants. This experiment examined the effects of dietary supplementation with either dried, pelleted grape marc or ensiled grape marc on yield and composition of milk, enteric CH4 emissions, and ruminal microbiota in dairy cows. Thirty-two Holstein dairy cows in late lactation were offered 1 of 3 diets: a control (CON) diet; a diet containing dried, pelleted grape marc (DGM); and a diet containing ensiled grape marc (EGM). The diet offered to cows in the CON group contained 14.0kg of alfalfa hay dry matter (DM)/d and 4.3kg of concentrate mix DM/d. Diets offered to cows in the DGM and EGM groups contained 9.0kg of alfalfa hay DM/d, 4.3kg of concentrate mix DM/d, and 5.0kg of dried or ensiled grape marc DM/d, respectively. These diets were offered individually to cows for 18d. Individual cow feed intake and milk yield were measured daily and milk composition measured on 4d/wk. Individual cow CH4 emissions were measured by the SF6 tracer technique on 2d at the end of the experiment. Ruminal bacterial, archaeal, fungal, and protozoan communities were quantified on the last day of the experiment. Cows offered the CON, DGM, and EGM diets, ate 95, 98, and 96%, respectively, of the DM offered. The mean milk yield of cows fed the EGM diet was 12.8kg/cow per day and was less than that of cows fed either the CON diet (14.6kg/cow per day) or the DGM diet (15.4kg/cow per day). Feeding DGM and EGM diets was associated with decreased milk fat yields, lower concentrations of saturated fatty acids, and enhanced concentrations of mono- and polyunsaturated fatty acids, in particular cis-9,trans-11 linoleic acid. The mean CH4 emissions were 470, 375, and 389g of CH4/cow per day for cows fed the CON, DGM, and EGM diets, respectively. Methane yields were 26.1, 20.2, and 21.5g of CH4/kg of DMI for cows fed the CON, DGM, and EGM diets, respectively. The ruminal bacterial and archaeal communities were altered by dietary supplementation with grape marc, but ruminal fungal and protozoan communities were not. Decreases of approximately 20% in CH4 emissions and CH4 yield indicate that feeding DGM and EGM could play a role in CH4 abatement., (Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Variation in the composition of microorganisms in the rumen (the rumen microbiome) of dairy cattle (Bos taurus) is of great interest because of possible links to methane emission levels. Feed additives are one method being investigated to reduce enteric methane production by dairy cattle. Here we report the effect of 2 methane-mitigating feed additives (grapemarc and a combination of lipids and tannin) on rumen microbiome profiles of Holstein dairy cattle. We used untargeted (shotgun) massively parallel sequencing of microbes present in rumen fluid to generate quantitative rumen microbiome profiles. We observed large effects of the feed additives on the rumen microbiome profiles using multiple approaches, including linear mixed modeling, hierarchical clustering, and metagenomic predictions. The effect on the fecal microbiome profiles was not detectable using hierarchical clustering, but was significant in the linear mixed model and when metagenomic predictions were used, suggesting a more subtle effect of the diets on the lower gastrointestinal microbiome. A differential representation analysis (analogous to differential expression in RNA sequencing) showed significant overlap in the contigs (which are genome fragments representing different microorganism species) that were differentially represented between experiments. These similarities suggest that, despite the different additives used, the 2 diets assessed in this investigation altered the microbiomes of the samples in similar ways. Contigs that were differentially represented in both experiments were tested for associations with methane production in an independent set of animals. These animals were not treated with a methane-mitigating diet, but did show substantial natural variation in methane emission levels. The contigs that were significantly differentially represented in response to both dietary additives showed a significant enrichment for associations with methane production. This suggests that these methane-mitigating diets have altered the rumen microbiome toward naturally low methane-emitting microbial profiles. The contig sequences are predominantly new and include Faecalibacterium spp. The contigs we have identified here are potential biomarkers for low-methane-emitting cattle., (Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

This study examined effects on milk yield and composition, milk fatty acid concentrations and methane (CH4) emissions when dairy cows were offered diets containing different amounts of algal meal. The algal meal contained 20% docosahexaenoic acid (DHA) and cows were offered either 0, 125, 250, or 375 g/cow per d of algal meal corresponding to 0, 25, 50, or 75 g of DHA/cow per d. Thirty-two Holstein cows in mid lactation were allocated to 4 treatment groups, and cows in all groups were individually offered 5.9k g of dry matter (DM) per day of concentrates [683 g/kg of cracked wheat (Triticum aestivum), 250 g/kg of cold-pressed canola, 46 g/kg of granulated dried molasses, and 21 g/kg of mineral mix] and ad libitum alfalfa (Medicago sativa) hay. The algal meal supplement was added to the concentrate allowance and was fed during the morning and afternoon milking, whereas the alfalfa hay was fed individually in pens. Cows were gradually introduced to their diets over 7d and then fed their treatment diets for a further 16d. Dry matter intake and milk yield were measured daily, and milk composition was measured on a sample representative of the daily milk yield on Thursday of each week. For the last 2d of the experiment, cows were individually housed in respiration chambers to allow measurement of CH4 emissions. Dry matter intake, milk yield and milk composition were also measured while cows were in the respiration chambers. Cows ate all their offered concentrates, but measured intake of alfalfa decreased with increasing dose of DHA by 16.2, 16.4, 15.1, and 14.3 kg of DM/d, respectively. Milk yield (22.6, 23.5, 22.6, and 22.6 kg/cow per d) was not affected by DHA dose, but milk fat concentrations (49.7, 37.8, 37.0, and 38.3g/kg) and, consequently, milk fat yields (1.08, 0.90, 0.83, and 0.85 kg/d) decreased with addition of DHA. The feeding of algal meal high in DHA was associated with substantial increases in the concentrations of DHA (0.04, 0.36, 0.60, and 0.91 g/100g of milk fatty acids) and conjugated linoleic acid C18:2 cis-9,trans-11 (0.36, 1.09, 1.79, and 1.87 g/100g of milk fatty acids). Addition of DHA did not affect total emissions of CH4 (543, 563, 553, and 520 g/cow per d), nor emissions in terms of milk production (24.9, 22.1, 24.3, and 23.4 g of CH4/kg of milk), but emissions were increased with respect to total intake (22.6, 23.5, 24.5, and 24.4 g of CH4/kg of DM). These findings indicate that CH4 emissions were not reduced when dairy cows were fed a forage-based diet supplemented with DHA from algal meal., (Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)