Review of equations to predict methane emissions in dairy cows from milk fatty acid profiles and their application to commercial dairy farms

Greenhouse gas emission from the activities of all productive sectors is currently a topic of foremost importance. The major contributors in the livestock sector are ruminants, especially dairy cows. This study aimed to evaluate and compare 21 equations for predicting enteric methane emissions (EME) developed on the basis of milk traits and fatty acid profiles, which were selected from 46 retrieved through a literature review. We compiled a reference database of the detailed fatty acid profiles, determined by GC, of 992 lactating cows from 85 herds under 4 different dairy management systems. The cows were classified according to DIM, parity order, and dairy system. This database was the basis on which we estimated EME using the selected equations. The EME traits estimated were methane yield (20.63 ± 2.26 g/kg DMI, 7 equations), methane intensity (16.05 ± 2.76 g/kg of corrected milk, 4 equations), and daily methane production (385.4 ± 68.2 g/d, 10 equations). Methane production was also indirectly calculated by multiplying the daily corrected milk yield by the methane intensity (416.6 ± 134.7 g/d, 4 equations). We also tested for the effects of DIM, parity, and dairy system (as a correction factor) on the estimates. In general, we observed little consistency among the EME estimates obtained from the different equations, with exception of those obtained from meta-analyses of a range of data from different research centers. We found all the EME predictions to be highly affected by the sources of variation included in the statistical model: DIM significantly affected the results of 19 of the 21 equations, and parity order influenced the results of 13. Different patterns were observed for different equations with only some of them in accordance with expectations based on the cow's physiology. Finally, the best predictions of daily methane production were obtained when a measure of milk yield was included in the equation or when the estimate was indirectly calculated from daily milk yield and methane intensity.

Volatile Fatty Acids in Ruminal Fluid Can Be Used to Predict Methane Yield of Dairy Cows

The dry matter intake (DMI) of forage-fed cattle can be used to predict their methane emissions. However, many cattle are fed concentrate-rich diets that decrease their methane yield. A range of equations predicting methane yield exist, but most use information that is generally unavailable when animals are fed in groups or grazing. The aim of this research was to develop equations based on proportions of ruminal volatile-fatty-acids to predict methane yield of dairy cows fed forage-dominant as well as concentrate-rich diets. Data were collated from seven experiments with a total of 24 treatments, from 215 cows. Forage in the diets ranged from 440 to 1000 g/kg. Methane was measured either by open-circuit respiration chambers or a sulfur hexafluoride (SF6) technique. In all experiments, ruminal fluid was collected via the mouth approximately four hours after the start of feeding. Seven prediction equations were tested. Methane yield (MY) was equally best predicted by the following equations: MY = 4.08 × (acetate/propionate) + 7.05; MY = 3.28 × (acetate + butyrate)/propionate + 7.6; MY = 316/propionate + 4.4. These equations were validated against independent published data from both dairy and beef cattle consuming a wide range of diets. A concordance of 0.62 suggests these equations may be applicable for predicting methane yield from all cattle and not just dairy cows, with root mean-square error of prediction of 3.0 g CH4/kg dry matter intake.

Effects of feeding wheat or corn and of rumen fistulation on milk production and methane emissions of dairy cows

There has been little research that has quantified methane (CH4) yields when dairy cows consume diets containing wheat grain. Furthermore, although rumen-fistulated animals have been used in many experiments concerned with measuring CH4 emissions, no research has examined the effect of rumen fistulation on in vivo CH4 emissions and yield. This experiment examined the effects of including either wheat or corn grain in the diet and the effects of rumen fistulation on yields of milk and milk components, CH4 emissions, yields, and intensities. Eight rumen-fistulated and six non-fistulated Holstein dairy cows in late lactation were offered a wheat-based diet (WHT) and a corn-based diet (CRN) in a crossover design. For the WHT diet, cows were offered daily, 22.4 kg DM containing 45.5% lucerne hay, 8.9% canola meal, 0.5% mineral mix, 0.5% molasses powder and 44.6% rolled wheat. The CRN diet was similar to the WHT diet except that rolled corn replaced the wheat. There was no difference between the WHT and CRN diets on mean milk yields (27.8 vs 27.9 kg/day), but the WHT diet substantially reduced milk fat concentration (2.76 vs 4.23%) and milk fat yield (0.77 vs 1.18 kg/day). Methane emissions (218 vs 424 g/day), CH4 yield (11.1 vs 19.5 g/kg dry matter intake) and CH4 intensity (7.6 vs 15.7 g/kg milk) were all reduced ~45% by the WHT diet compared with the CRN diet. Rumen fistulation did not affect dry matter intake, milk production, milk composition or CH4 emissions, but decreased CH4 yield and intensity. Including wheat in the diet of dairy cows has the potential to be an effective strategy to reduce their greenhouse gas emissions. In addition, rumen fistulation was associated with a small reduction in CH4 yield and intensity, and this should be considered when using rumen-fistulated cows in research concerned with CH4 emissions.

Milk performance and grazing behaviour of dairy cows in response to pasture allowance

This study aimed to evaluate the effects of pasture allowances on forage production, milk yield and composition, and grazing behaviour of Holstein cows during autumn. Thirty-six Holstein cows calving in the autumn were allocated to blocks considering: calving date, bodyweight, and body score. Treatments consisted of three pasture allowances as follows: high (HA; 38.4 kg DM/cow.day), medium (MA; 30.3 kg DM/cow.day), and low (LA; 26.8 kg DM/cow.day) pasture allowances. Forage mass and forage height pre-grazing were similar (P > 0.05) for all grazing targets. Pasture-use efficiency was affected (P < 0.05) by the pasture allowance. The highest and lowest efficiency was obtained with treatments LA and HA, respectively. The neutral detergent fibre content of forage harvesting was affected (P < 0.05) by the pasture allowance, with average of 44.8, 47.0, and 49.4 to HA, MA, and LA, respectively. There was an effect of pasture allowances (P < 0.05) on the milk yield per hectare and milk yield per cow. The highest production was observed in LA (438 L/ha.day) and the lowest in HA (314 L/ha.day). The percentage of milk fat, milk protein, and milk fat (g/cow.day) did not differ (P > 0.05) among pasture allowances. There was effect (P < 0.05) of pasture allowance with higher grazing time (369 min) and lower rumination time (23.3 min) observed to HA. Pasture allowances affected (P < 0.05) the total number of bites/day and bites/min, but did not affect (P > 0.05) bite mass. The pasture managements with low (26.8 kg DM/cow.day) pasture allowances provided better conditions for milk yield per area, likely due to the better grazing efficiency. However, pasture allowance provide little measurable changes on grazing behaviour.

Methane prediction based on individual or groups of milk fatty acids for dairy cows fed rations with or without linseed

Milk fatty acids (MFA) are a proxy for the prediction of CH₄ emission from cows, and prediction differs with diet. Our objectives were (1) to compare the effect of diets on the relation between MFA profile and measured CH₄ production, (2) to predict CH₄ production based on 6 data sets differing in the number and type of MFA, and (3) to test whether additional inclusion of energy-corrected milk (ECM) yield or dry matter intake (DMI) as explanatory variables improves predictions. Twenty dairy cows were used. Four diets were used based on corn silage (CS) or grass silage (GS) without (L0) or with linseed (LS) supplementation. Ten cows were fed CS-L0 and CS-LS and the other 10 cows were fed GS-L0 and GS-LS in random order. In feeding wk 5 of each diet, CH₄ production (L/d) was measured in respiration chambers for 48 h and milk was analyzed for MFA concentrations by gas chromatography. Specific CH₄ prediction equations were obtained for L0-, LS-, GS-, and CS-based diets and for all 4 diets collectively and validated by an internal cross-validation. Models were developed containing either 43 identified MFA or a reduced set of 7 groups of biochemically related MFA plus C16:0 and C18:0. The CS and LS diets reduced CH₄ production compared with GS and L0 diets, respectively. Methane yield (L/kg of DMI) reduction by LS was higher with CS than GS diets. The concentrations of C18:1 trans and n-3 MFA differed among GS and CS diets. The LS diets resulted in a higher proportion of unsaturated MFA at the expense of saturated MFA. When using the data set of 43 individual MFA to predict CH₄ production (L/d), the cross-validation coefficient of determination (R²_CV) ranged from 0.47 to 0.92. When using groups of MFA variables, the R²_CV ranged from 0.31 to 0.84. The fit parameters of the latter models were improved by inclusion of ECM or DMI, but not when added to the data set of 43 MFA for all diets pooled. Models based on GS diets always had a lower prediction potential (R²_CV = 0.31 to 0.71) compared with data from CS diets (R²_CV = 0.56 to 0.92). Models based on LS diets produced lower prediction with data sets with reduced MFA variables (R²_CV = 0.62 to 0.68) compared with L0 diets (R²_CV = 0.67 to 0.80). The MFA C18:1 cis-9 and C24:0 and the monounsaturated FA occurred most often in models. In conclusion, models with a reduced number of MFA variables and ECM or DMI are suitable for CH₄ prediction, and CH₄ prediction equations based on diets containing linseed resulted in lower prediction accuracy.

Effects of starch-rich or lipid-supplemented diets that induce milk fat depression on rumen biohydrogenation of fatty acids and methanogenesis in lactating dairy cows

Optimizing milk production efficiency implies diets allowing low methane (CH4) emissions and high dairy performance. We hypothesize that nature of energy (starch v. lipids) and lipid supplement types (monounsaturated fatty acid (MUFA) v. polyunsaturated fatty acid (PUFA) mitigate CH4 emissions and can induce low milk fat content via different pathways. The main objective of this experiment was to study the effects of starch-rich or lipid-supplemented diets that induce milk fat depression (MFD) on rumen biohydrogenation (RBH) of unsaturated fatty acids (FA) and enteric CH4 emissions in dairy cows. Four multiparous lactating Holstein cows (days in milk=61±11 days) were used in a 4×4 Latin square design with four periods of 28 days. Four dietary treatments, three of which are likely to induce MFD, were based (dry matter basis) on 56% maize silage, 4% hay and 40% concentrates rich in: (1) saturated fatty acid (SFA) from Ca salts of palm oil (PALM); (2) starch from maize grain and wheat (MFD-Starch); (3) MUFA (cis-9 C18:1) from extruded rapeseeds (MFD-RS); and (4) PUFA (C18:2n-6) from extruded sunflower seeds (MFD-SF). Intake and milk production were measured daily. Milk composition and FA profile, CH4 emissions and total-tract digestibility were measured simultaneously when animals were in open-circuit respiration chambers. Fermentation parameters were analysed from rumen fluid samples taken before feeding. Dry matter intake, milk production, fat and protein contents, and CH4 emissions were similar among the four diets. We observed a higher milk SFA concentration with PALM and MFD-Starch, and lower milk MUFA and trans-10 C18:1 concentrations in comparison to MFD-RS and MFD-SF diets, while trans-11 C18:1 remained unchanged among diets. Milk total trans FA concentration was greater for MFD-SF than for PALM and MFD-Starch, with the value for MFD-RS being intermediate. Milk C18:3n-3 content was higher for MFD-RS than MFD-SF. The MFD seems more severe with MFD-SF and MFD-RS than PALM and MFD-Starch diets, because of a decrease in milk SFA concentration and a stronger shift from trans-11 C18:1 to trans-10 C18:1 in milk. The MFD-SF diet increased milk trans FA (+60%), trans-10 C18:1 (+31%), trans-10,cis-12 CLA (+27%) and PUFA (+36%) concentrations more than MFD-RS, which explains the numerically lowest milk fat yield and indicates that RBH pathways of PUFA differ between these two diets. Maize silage-based diets rich in starch or different unsaturated FA induced MFD with changes in milk FA profiles, but did not modify CH4 emissions.

Dairy system, parity, and lactation stage affect enteric methane production, yield, and intensity per kilogram of milk and cheese predicted from gas chromatography fatty acids

Ruminants (and milk production) contribute to global climate change through enteric methane emissions (EME), and any attempt to reduce them is complicated by the fact that they are difficult and expensive to measure directly. In the case of dairy cows, a promising indirect method of estimating EME is to use the milk fatty acid profile as a proxy, as a relationship exists between microbial activity in the rumen and the molecules available for milk synthesis in the mammary gland. In the present study, we analyzed the detailed fatty acid profiles (through gas chromatography) of a large number of milk samples from 1,158 Brown Swiss cows reared on 85 farms with the aim of testing in the field 2 equations for estimating EME taken from a published meta-analysis. The average estimated methane yield (CH₄ emission per kg of dry matter intake, 21.34 ± 1.60 g/kg) and methane intensity (per kg of corrected milk, 14.17 ± 1.78 g/kg), and the derived methane production (CH₄ emissions per day per cow, 357 ± 109 g/d) were similar to those previously published. Using data from model cheese makings from individual cows, we also calculated estimated methane intensity per kilogram of fresh cheese (99.7 ± 16.4 g/kg) and cheese solids (207.5 ± 30.9 g/kg). Dairy system affected all EME estimates. Traditional dairy farms, and modern farms including corn silage in the TMR exhibited greater estimated methane intensities. We found very wide variability in estimated EME traits among different farms within dairy system (0.33 to 0.61 of total variance), suggesting the need to modify the farms' feeding regimens and management practices to mitigate emissions. Among the individual factors, parity order affected all estimated EME traits excepted methane yield, with an increase from first lactation to the following ones. Lactation stage exhibited more favorable estimated EME traits during early lactation, concomitant with the availability of nutrients from body tissue mobilization for mammary synthesis of milk. Our results showed a coherence between the EME traits estimated from the analysis of milk fatty acids and the expectations according to current knowledge. Further research is needed to validate the results obtained in this study in other breeds and populations, to assess the magnitude of the genetic variation and the potential of these phenotypes to be exploited in breeding programs with the aim to mitigate emissions.

Challenges of feeding dairy cows in Australia and New Zealand

There is a continuing evolution of feeding systems in both Australian and New Zealand dairy industries and this presents challenges for the future. Since the turn of the century, the two countries have diverged in industry growth characteristics, with Australian dairying having contracted, with 10% less milk being produced because of 20% fewer cows producing 15% more per cow, whereas New Zealand dairying has expanded, producing 83% more milk driven by a 54% increase in cow numbers and a 31% increase in milk production per cow. Solutions to optimise feed efficiency included the common themes of (1) growing more forage on farm, (2) increasing its utilisation and (3) more efficient use of supplements resulting in increases in DM intake, and they remain relevant. In New Zealand, many of the recent research activities have aimed at improving feed supply while limiting environmental impacts driven by increasing societal concern surrounding the environmental footprint of a growing and intensifying agricultural sector. In Australia, many of the recent research activities have aimed at improving feed efficiency, with a focus on understanding situations where partial mixed ration feeding systems (Australian Farm Systems 3 and 4) are sustainable. Simply growing more feed on farm can no longer be a sole objective; farms must be operated with a view to reduce the environmental footprint, with New Zealand dairy farmers increasingly needing to farm within nitrogen limits. The present review revisits and reinforces many of the concepts developed in previous reviews, but also examines the evolution of feeding systems in both countries and opportunities to improve feed efficiency and profit, while satisfying public expectations around environmental stewardship. We also identify some of the gaps in the current knowledge that warrant further research.

Can concentrations of trans octadecenoic acids in milk fat be used to predict methane yields of dairy cows?

There is a need to develop simple, accurate methods for predicting methane emissions, yields and intensities of dairy cows. Several studies have focussed on the relationship between the concentrations of trans-10 plus trans-11 C18:1 fatty acids in milk fat and methane yield. The aim of the present study was to perform a meta-analysis to quantify relationships between the concentrations of various trans isomers of C18:1 in milk fat and methane emissions (g/day), methane yield (g/kg dry-matter intake) and methane intensity (g/kg energy-corrected milk yield). Data were from seven experiments encompassing 23 different diets and 220 observations of milk fatty acid concentrations and methane emissions. Univariate linear mixed-effects regression models were fitted to the data with the linear term as a fixed effect and with experiment and observation within experiment as random effects. Concentrations of trans-9, trans-10, trans-11 and trans-10 plus trans-11 isomers of C18:1 were poorly related to methane emissions, yields and intensities, with the best relationships being between trans-10 C18:1 and methane emissions (R2 = 0.356), trans-10 C18:1 and methane yield (R2 = 0.265) and trans-10 plus trans-11 C18:1 and methane intensity (R2 = 0.124). The data indicated that the relationships between trans-10 C18:1 and methane metrics were not linear, but were biphasic and better described by an exponential model. However, even exponential models poorly fitted the data. It is concluded that the concentrations of trans isomers of C18:1 have limited potential to accurately predict methane emissions, yields or intensities of dairy cows.

Prediction of methane emission from lactating dairy cows using milk fatty acids and mid-infrared spectroscopy

Enteric methane (CH4 ) production is among the main targets of greenhouse gas mitigation practices for the dairy industry. A simple, robust and inexpensive measurement technique applicable on a large scale to estimate CH4 emission from dairy cattle would therefore be valuable. Milk fatty acids (MFA) are related to CH4 production because of the common biochemical pathway between CH4 and fatty acids in the rumen. A summary of studies that investigated the predictive power of MFA composition for CH4 emission indicated good potential, with predictive power ranging between 47% and 95%. Until recently, gas chromatography (GC) was the principal method used to determine the MFA profile, but GC is unsuitable for routine analysis. This has led to the application of mid-infrared (MIR) spectroscopy. The major advantages of using MIR spectroscopy to predict CH4 emission include its simplicity and potential practical application at large scale. Disadvantages include the inability to predict important MFA for CH4 prediction, and the moderate predictive power for CH4 emission. It may not be sufficient to predict CH4 emission based on MIR alone. Integration with other factors, like feed intake, nutrient composition of the feed, parity, and lactation stage may improve the prediction of CH4 emission using MIR spectra. © 2016 Society of Chemical Industry.

Changes throughout lactation in phenotypic and genetic correlations between methane emissions and milk fatty acid contents predicted from milk mid-infrared spectra

The aim of this study was to estimate phenotypic and genetic correlations between methane production (Mp) and milk fatty acid contents of first-parity Walloon Holstein cows throughout lactation. Calibration equations predicting daily Mp (g/d) and milk fatty acid contents (g/100 dL of milk) were applied on milk mid-infrared spectra related to Walloon milk recording. A total of 241,236 predictions of Mp and milk fatty acids were used. These data were collected between 5 and 305 d in milk in 33,555 first-parity Holstein cows from 626 herds. Pedigree data included 109,975 animals. Bivariate (i.e., Mp and a fatty acid trait) random regression test-day models were developed to estimate phenotypic and genetic parameters of Mp and milk fatty acids. Individual short-chain fatty acids (SCFA) and groups of saturated fatty acids, SCFA, and medium-chain fatty acids showed positive phenotypic and genetic correlations with Mp (from 0.10 to 0.16 and from 0.23 to 0.30 for phenotypic and genetic correlations, respectively), whereas individual long-chain fatty acids (LCFA), and groups of LCFA, monounsaturated fatty acids, and unsaturated fatty acids showed null to positive phenotypic and genetic correlations with Mp (from -0.03 to 0.13 and from -0.02 to 0.32 for phenotypic and genetic correlations, respectively). However, these correlations changed throughout lactation. First, de novo individual and group fatty acids (i.e., C4:0, C6:0, C8:0, C10:0, C12:0, C14:0, SCFA group) showed low phenotypic or genetic correlations (or both) in early lactation and higher at the end of lactation. In contrast, phenotypic and genetic correlations between Mp and C16:0, which could be de novo synthetized or derived from blood lipids, were more stable during lactation. This fatty acid is the most abundant fatty acid of the saturated fatty acid and medium-chain fatty acid groups of which correlations with Mp showed the same pattern across lactation. Phenotypic and genetic correlations between Mp and C17:0 and C18:0 were low in early lactation and increased afterward. Phenotypic and genetic correlations between Mp and C18:1 cis-9 originating from the blood lipids were negative in early lactation and increased afterward to become null from 18 wk until the end of lactation. Correlations between Mp and groups of LCFA, monounsaturated fatty acids, and unsaturated fatty acids showed a similar or intermediate pattern across lactation compared with fatty acids that compose them. Finally, these results indicate that correlations between Mp and milk fatty acids vary following lactation stage of the cow, a fact still often ignored when trying to predict Mp from milk fatty acid profile.

Milk metabolome relates enteric methane emission to milk synthesis and energy metabolism pathways

Methane (CH4) emission of dairy cows contributes significantly to the carbon footprint of the dairy chain; therefore, a better understanding of CH4 formation is urgently needed. The present study explored the milk metabolome by gas chromatography-mass spectrometry (milk volatile metabolites) and nuclear magnetic resonance (milk nonvolatile metabolites) to better understand the biological pathways involved in CH4 emission in dairy cattle. Data were used from a randomized block design experiment with 32 multiparous Holstein-Friesian cows and 4 diets. All diets had a roughage:concentrate ratio of 80:20 (dry matter basis) and the roughage was grass silage (GS), corn silage (CS), or a mixture of both (67% GS, 33% CS; 33% GS, 67% CS). Methane emission was measured in climate respiration chambers and expressed as CH4 yield (per unit of dry matter intake) and CH4 intensity (per unit of fat- and protein-corrected milk; FPCM). No volatile or nonvolatile metabolite was positively related to CH4 yield, and acetone (measured as a volatile and as a nonvolatile metabolite) was negatively related to CH4 yield. The volatile metabolites 1-heptanol-decanol, 3-nonanone, ethanol, and tetrahydrofuran were positively related to CH4 intensity. None of the volatile metabolites was negatively related to CH4 intensity. The nonvolatile metabolites acetoacetate, creatinine, ethanol, formate, methylmalonate, and N-acetylsugar A were positively related to CH4 intensity, and uridine diphosphate (UDP)-hexose B and citrate were negatively related to CH4 intensity. Several volatile and nonvolatile metabolites that were correlated with CH4 intensity also were correlated with FPCM and not significantly related to CH4 intensity anymore when FPCM was included as covariate. This suggests that changes in these milk metabolites may be related to changes in milk yield or metabolic processes involved in milk synthesis. The UDP-hexose B was correlated with FPCM, whereas citrate was not. Both metabolites were still related to CH4 intensity when FPCM was included as covariate. The UDP-hexose B is an intermediate of lactose metabolism, and citrate is an important intermediate of Krebs cycle-related energy processes. Therefore, the negative correlation of UDP-hexose B and citrate with CH4 intensity may reflect a decrease in metabolic activity in the mammary gland. Our results suggest that an integrative approach including milk yield and composition, and dietary and animal traits will help to explain the biological metabolism of dairy cows in relation to methane CH4 emission.

Recent Advances in Measurement and Dietary Mitigation of Enteric Methane Emissions in Ruminants

Methane (CH4) emission, which is mainly produced during normal fermentation of feeds by the rumen microorganisms, represents a major contributor to the greenhouse gas (GHG) emissions. Several enteric CH4 mitigation technologies have been explored recently. A number of new techniques have also been developed and existing techniques have been improved in order to evaluate CH4 mitigation technologies and prepare an inventory of GHG emissions precisely. The aim of this review is to discuss different CH4 measuring and mitigation technologies, which have been recently developed. Respiration chamber technique is still considered as a gold standard technique due to its greater precision and reproducibility in CH4 measurements. With the adoption of recent recommendations for improving the technique, the SF6 method can be used with a high level of precision similar to the chamber technique. Short-term measurement techniques of CH4 measurements generally invite considerable within- and between-animal variations. Among the short-term measuring techniques, Greenfeed and methane hood systems are likely more suitable for evaluation of CH4 mitigation studies, if measurements could be obtained at different times of the day relative to the diurnal cycle of the CH4 production. Carbon dioxide and CH4 ratio, sniffer, and other short-term breath analysis techniques are more suitable for on farm screening of large number of animals to generate the data of low CH4-producing animals for genetic selection purposes. Different indirect measuring techniques are also investigated in recent years. Several new dietary CH4 mitigation technologies have been explored, but only a few of them are practical and cost-effective. Future research should be directed toward both the medium- and long-term mitigation strategies, which could be utilized on farms to accomplish substantial reductions of CH4 emissions and to profitably reduce carbon footprint of livestock production systems. This review presents recent developments and critical analysis on different measurements and dietary mitigation of enteric CH4 emissions technologies.

Relationships between milk fatty acid profiles and enteric methane production in dairy cattle fed grass- or grass silage-based diets

We quantified relationships between methane production and milk fatty acid (FA) profile in dairy cattle fed grass- or grass silage-based diets, and determined whether recent prediction equations for methane, based on a wide variety of diets, are applicable to grass- and grass silage-based diets. Data from three studies were used, encompassing four grass herbage and 14 grass silage treatments and 132 individual cow observations. Methane production was measured using respiration chambers and milk fatty acids (FAs) analysed using gas chromatography. The proportion of grass or grass silage (dry matter (DM) basis) was 0.80 ± 0.037. Methane yield averaged 22.3 ± 2.10 g/kg DM intake (DMI) and 14.2 ± 2.90 g/kg fat- and protein-corrected milk (FPCM). Mixed model univariate regression including a random study effect on intercept was applied to predict methane yield, with individual milk FA concentrations (g/100 g FA) as fixed effects. Of the 42 milk FAs identified, no single FA had a strong positive correlation (r; strong correlation defined as |r| ≥ 0.50) with methane yield (g/kg DMI), and cis-12 C18:1 and cis-9,12,15 C18:3 had a strong negative correlation with methane yield (g/kg DMI). C14:0 iso, C15:0, C15:0 iso, C15:0 anteiso, C16:0, C20:0, cis-11,14 C20:2, cis-5,8,11,14 C20:4, C22:0, cis-7,10,13,16,19 C22:5 and C24:0 had a strong positive correlation with methane yield (g/kg FPCM), and trans-15+cis-11 C18:1, cis-9 C18:1, and cis-11 C20:1 had a strong negative correlation with methane yield (g/kg FPCM). Observed methane yield was compared with methane yield predicted by the equations of van Lingen et al. (2014; Journal of Dairy Science 97, 7115–7132). These equations did not accurately predict methane yield as grams per kilogram DMI (concordance correlation coefficient (CCC) = 0.13) or as grams per kilogram FPCM (CCC = 0.22), in particular related to large differences in standard deviation between predicted and observed values. In conclusion, quantitative relationships between milk FA profile and methane yield in cattle fed grass- or grass silage-based diets differ from those determined for other types of diets.

Reducing the carbon footprint of Australian milk production by mitigation of enteric methane emissions

This review examines research aimed at reducing enteric methane emissions from the Australian dairy industry. Calorimeter measurements of 220 forage-fed cows indicate an average methane yield of 21.1 g methane (CH4)/kg dry matter intake. Adoption of this empirical methane yield, rather than the equation currently used in the Australian greenhouse gas inventory, would reduce the methane emissions attributed to the Australian dairy industry by ~10%. Research also indicates that dietary lipid supplements and feeding high amounts of wheat substantially reduce methane emissions. It is estimated that, in 1980, the Australian dairy industry produced ~185 000 t of enteric methane and total enteric methane intensity was ~33.6 g CH4/kg milk. In 2010, the estimated production of enteric methane was 182 000 t, but total enteric methane intensity had declined ~40% to 19.9 g CH4/kg milk. This remarkable decline in methane intensity and the resultant improvement in the carbon footprint of Australian milk production was mainly achieved by increased per-cow milk yield, brought about by the on-farm adoption of research findings related to the feeding and breeding of dairy cows. Options currently available to further reduce the carbon footprint of Australian milk production include the feeding of lipid-rich supplements such as cottonseed, brewers grains, cold-pressed canola, hominy meal and grape marc, as well as feeding of higher rates of wheat. Future technologies for further reducing methane emissions include genetic selection of cows for improved feed conversion to milk or low methane intensity, vaccines to reduce ruminal methanogens and chemical inhibitors of methanogenesis.

Milk production and composition, and methane emissions from dairy cows fed lucerne hay with forage brassica or chicory

Forage brassica and chicory crops provide an alternative to perennial grass pastures as a forage supply for grazing dairy cows during summer, but there is little information about their effects on milk production and methane (CH4) emissions. Thirty-two Holstein–Friesian cows were fed for 10 days on a diet of lucerne cubes (750 g/kg DM) and grain (250 g/kg DM) (CON) or diets in which forage brassica (410 g/kg DM, FBR) or reproductive-stage chicory (410 g/kg DM, RCH) were offered with lucerne cubes (340 g/kg DM) and grain (250 g/kg DM). Cows offered the FBR diet produced more energy-corrected milk (25.4 kg/day) than did cows offered the CON diet (22.7 kg/day, P = 0.001), even though DM intake was not different for cows between the two groups (20.6 kg/day on average). In contrast, cows offered the RCH diet produced less energy-corrected milk (19.3 kg/day) than did cows in the other two groups (P = 0.001), reflecting the lower DM intake by cows offered the RCH diet (17.7 kg/day, P < 0.01). Methane yield (g CH4/kg DMI) was lower (P < 0.01) on the CON (21.0) and FBR (20.5) diets than on the RCH diet (26.1). Methane intensity (g/kg energy-corrected milk) was different (P < 0.01) for all diets, with CON (19.4) being intermediate, FBR (17.3) lowest and RCH (23.8) the greatest. Diet type was associated with differences in the proportions of only a small number of specific milk fatty acids, and differences in proportions of specific fatty acids were not related to CH4 emissions.

An inhibitor persistently decreased enteric methane emission from dairy cows with no negative effect on milk production

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.