C05a_Attachment 2 - Julian et al. 2015.pdf

Trends Enteric CH4 emissions from ruminants are a significant source of greenhouse gas.

Enteric CH4 is also associated with farming productivity.

Various enteric CH4 measurement methods have been developed, ran-ging from tracers and capsules, for individual ruminants, to whole farm systems.

Further development of enteric CH4 measurement technologies is required to enable reliable, feasible, and low-cost assessments.

1Centre for Environmental Sustainability and Remediation, School of Applied Sciences, RMIT University, Melbourne, VIC, Australia 2Ternes Agricultural Consulting Pty Ltd, Upwey, Melbourne, VIC, Australia 3Commonwealth Scientific and Industrial Research Organisation (CSIRO), Brisbane, QLD, Australia 4School of Animal and Comparative Biomedical Sciences, The University of Arizona, Tucson, AZ, USA 5School of Electrical and Computer Engineering, RMIT University, Melbourne, VIC, Australia

*Correspondence:

kourosh.kalantar@rmit.edu.au (K. Kalantar-zadeh).

TIBTEC 1309 No. of Pages 10 Review Measuring Methane Production from Ruminants Julian Hill,1,2 Chris McSweeney,3 André-Denis G. Wright,4

Greg Bishop-Hurley,3 and Kourosh Kalantar-zadeh5,*

Radiative forcing of methane (CH4) is significantly higher than carbon dioxide (CO2) and its enteric production by ruminant livestock is one of the major sources of greenhouse gas emissions. CH4 is also an important marker of farming productivity, because it is associated with the conversion of feed to product in livestock. Consequently, measurement of enteric CH4 is emerging as an important research topic. In this review, we briefly describe the conversion of carbohydrate to CH4 by the bacterial community within gut, and highlight some of the key host–microbiome interactions. We then provide a picture of current progress in techniques for measuring enteric CH4, the context in which these technologies are used, and the challenges faced. We also discuss solutions to existing problems and new approaches currently in development.

Significance of Enteric Methane Production by Ruminants CH4 is the most abundant organic trace gas in the atmosphere, which has a significant impact on the global heat budget and national greenhouse inventories [1,2]. Biogenic methanogenesis is a major contributor to global atmospheric CH4 stocks (estimated at 1–3% of net primary production) [3]. Global anthropogenic CH4 sources are estimated to account for 50–55% of the total emissions since the year 2000 (approximately 331 Tg/year of a total of 678 Tg/year with livestock production contributing between 87 and 94 Tg/year) [4,5].

It is estimated that the half-life of CH4 in the atmosphere is 12.4 years, making this an important factor when considering radiative forcing and global warming potential (GWP100) [5–7]. CH4 reacts with the hydroxyl radical in the troposphere. Oxidation of CH4 by hydroxyl (OH-) leads to the formation of formaldehyde (CH2O: 90% of sink), carbon monoxide (CO), and, with sufficient nitrogen oxides (NOx), ozone (O3) [8]. These processes also affect water vapor and O3 concentrations in the stratosphere, augmenting the radiative forcing of CH4 and, hence, its GWP100. Oxidation of CH4 in the stratosphere results in the formation of water vapor and, hence, increased radiative forcing. It has been estimated that 25% of the increase in stratospheric water vapor observed between 1980 and 2010 resulted from an increased CH4 concentration [9]. The current estimate of the GWP100 of CH4 with carbon-climate feedback is 34 (without feedback calculations, 28), whereas the global temperature potential of the gas (GTP100) is 11 [10].

Methanogenesis is an important part of the energy metabolism in ruminants and measuring its production is critical in understanding ruminant livestock productivity. CH4 emissions data can be combined with information relating to the rumen microbiome, metabolic processes, and digestion to provide invaluable insights into the efficiency of livestock systems. However, to date, improvements in livestock efficiency have mostly been made through advances in gut microbiol-ogy, nutrition, genetics, andhealth of the host animal andnot through the inclusionofCH4 emission information. Through a better understanding of enteric methanogenesis and the fate of microbial products yielded during the fermentation processes, further productivity gains may be possible Trends in Biotechnology, Month Year, Vol. xx, No. yy http://dx.doi.org/10.1016/j.tibtech.2015.10.004 1 © 2015 Elsevier Ltd. All rights reserved.

mailto:kourosh.kalantar@rmit.edu.au http://dx.doi.org/10.1016/j.tibtech.2015.10.004

TIBTEC 1309 No. of Pages 10 [11–16]. For instance, increase in productivity can be achieved by reducing CH4 through an increase capture of metabolic hydrogen (H2) into volatile fatty acids (VFA) or through a change in biochemical processes that result in alternatebiochemical pathwaysbecoming thermodynamically more favorable [17].

Primary enteric fermentation yields VFAs (acetate, propionate, and butyrate), fermentation acids (lactate), alcohols (e.g., ethanol), succinate, and other branched chain VFAs. In addition, CH4, CO2, H2, and ammonia (NH3) gases are produced. CH4 production is the major route for H2 clearance from fermentation [18]. Most CH4 is directly eructed from the rumen head space.

However, approximately 10–15% is emitted through the respiration pathway and via flatus as a result of hindgut fermentation of digesta [19]. If the CH4 emitted from the animal is estimated as digestible energy, between 2% and 12% of such metabolizable energy is voided [20].

Reductions in greenhouse gas emissions through CH4 mitigation strategies and more efficient production systems via CH4 assessment techniques have influenced anthropogenic climate change and farming. For instance, it has been demonstrated that reductions in enteric CH4 production can be achieved through the genetic selection of more feed-efficient [9_TD$DIFF] beef cattle with low residual feed intake (RFI, which is the difference between the actual feed intake of an animal and its expected feed requirements) [2_TD$DIFF] [21]. This approach is attractive because it reduces the costs of production through lowered feed intake, reducing CH4 emissions (and potentially lower nitrous oxide emissions) without compromising the growth rate. In this regard, the expected reduction in CH4 emissions from the Australian beef herd, based on animals of lower RFI, has been modeled in a single herd configuration in southern Australia [22]. In the process, a gene flow model was[10_TD$DIFF] used to simulate the spread of improved RFI genes through a breeding herd over 25 years (2002–2026). The data suggest that, for an individual adopting herd, the annual CH4 abatement in year 25 of selection would be 15.9% lower than in year 1. A similar example has recently been adopted by the Government of the province of Alberta, Canada [23] for an emissions reduction protocol based on the selection of low RFI beef cattle.

Altogether, if we fail to accurately measure enteric CH4, the strategies to reduce greenhouse gas emissions and increase farming productivity are likely to remain vague, random, and conse-quently inefficient [24–27]. In this review, we provide an overview of current methods to measure livestock CH4 production. We include a critique of current approaches and provide an opinion on where the new advances in measurement technologies may emerge.

Fundamentals of Ruminant Methanogenesis Ruminants have evolved a symbiotic association with their gut microbiome that can synthesize a range of cellulose- and hemicellose-digesting enzymes [28]. This association allows the animal to obtain nutrients through herbivory. In ruminants, digestion of feed is a two-stage process [26,29,30]: (i) enzymatic degradation of feed sources in the rumen with the release of a range of monomers (sugars, amino acids, glycerol, and fatty acids); and (ii) the fermentation of those compounds by rumen microbiota (bacteria, methanogenic Archaea, Protozoa, and fungi).

The pregastric fermentation of cellulose-rich feeds in the reticulo-rumen-omasal complex (forest-omach) environment is intrinsically tightly regulated (redox potential of –300 to –350 mV; 38–42[11_TD$DIFF]8C and pH 6–7). These conditions maintain ruminal microbial system functionality but clearance of VFAs, H2, and CO2 must occur. VFAs are transported across the rumen and omasal walls and utilized by the animal, whereas CO2 is released to the head space of the rumen and lost through eructation or transported via circulation to the lungs and respired.ClearanceofmetabolicH2 is either through VFA production or, predominantly, conversion to CH4. This latter process is facilitated by methanogenic Archaea. Three major (Methanobrevibacter, Methanomicrobium, and Methanos-phaera) and three minor (Methanosarcina, Methanobacterium, and rumen cluster C) genera of 2 Trends in Biotechnology, Month Year, Vol. xx, No. yy methanogenic Archaea have been identified throughpopulation size and functionality [31–33]. They utilize metabolic hydrogen to facilitate the reduction and reoxidation in rumen microorganisms of NADH, NADPH, and FADH toNAD+, NADP+, and FAD+, respectively, thereby yielding ATP [3,34].

The methanogen community has a degree of plasticity in its response to metabolic H2 through five potential metabolic pathways and additional biohydrogenation reactions [31]. The main pathway is generally classified as hydrogenotrophic, but there are at least four additional pathways that have roles in the removal of hydrogen (Figure 1). The extent of these alternative Capture of reductant Energy conserva�onReduc�on of CO2

MF

Formyl-MF

Formyl-H4MPT

Methenyl-H4MPT

Methylene-H4MPT

Methyl-H4MPT

CH4

Methyl-S-CoM

CO2

Fdred?

H2O

H2

H4MPT

HSCoM

CoBS-SCoM

HSCoM HSCoB

Fdox?

H2

H2

H2

Fdox?

F420 H2

F420

F420 H2

Fdox?

Fdred?

pool

Fdred?

pool

F420 H2 pool

F420

F420

F420

F420

H4MPT

MF

ADP+Pi

ATP

V

V

V

H+/Na+

NADP+

+H+

Na+

H+

Na+

Na+

NADPH

Formate

Figure 1. The Predicted Pathways of Methane (CH4) Production inMethanobrevibacter ruminantiumwithout Cytochromes. The schematic is divided into three parts, showing the capture of reductant, the reduction of carbon dioxide (CO2), and conservation of energy at the methyltransfer step. The main reactions are shown by thick arrows and cofactor participation is indicated by thin arrows. Protons are not shown and the overall reaction is not balanced. Membrane-located proteins are shown by light-brown boxes and potential vaccine is labeled with a circled V. Abbreviations: CoMS-SCoB, coenzyme B-coenzymeM heterodisulfide; F420, coenzyme F420 oxidized; F420H2, coenzyme F420 reduced; Fdox?, unknown oxidized ferredoxin; Fdred?, unknown reduced ferredoxin; H4MPT, tetrahydromethanopterin; HSCoB, reduced coenzyme B; HSCoM, reduced coenzyme M; MF, methanofuran. Reproduced, with permission, from [36].

Trends in Biotechnology, Month Year, Vol. xx, No. yy 3 processes (methylotrophic and acetoclastic) alters the overall stoichiometry of CH4 production and the utilization of hydrogen by the rumen microbiome. The relation between CH4 yield and intake of digestible organic matter by the animal is nonlinear and not predictable [22]. To this point, it is not possible to link CH4 production and the structure and functionality of the rumen microbiome.

Themajor metabolic pathways are as follows [28,35] (a more comprehensive metabolic pathway based on Methanobrevibacter ruminantium is presented in Figure 1 [36]):

Hydrogenotrophic : CO2 þ 4H2 ! CH4 þ 2H2O

Methylotrophic : CH3OH þ H2 ! CH4 þH2O

4CH3OH ! 3CH4 þCO2 þ 2H2O

CH3NH2 þH2 ! CH4 þNH3

Aceticlastic : CH3COOH ! CO2 þCH4ðminor in the rumenÞ In addition, recent research has identified that newly [3_TD$DIFF] recognized [3_TD$DIFF] methanogens [3_TD$DIFF] (e.g., rumen cluster C) use a range of methyl donor compounds and CO2, suggesting that there are other, yet to be identified, pathways that produce CH4 [31].

Different Measurement and Estimation Methods of Enteric CH4

The emphasis on measurement of CH4 emitted by animals has formed the basis of more than 100 years of research on ruminant energetics and the impact of livestock on greenhouse gas emissions. Here, we present and discuss the major approaches to enteric CH4 measurement (schematics of several measurement methods are presented in Figure 2).

Respiration and Accumulation Chambers Direct measurement techniques include total or partial enclosure of animals (e.g., respiration chambers and head or face masks [37]). They are among the two most widely used techniques to measure CH4 emissions from ruminants.

Open-circuit direct calorimetry or respiration chambers have been used for determining heat balance and gaseous exchange in animals for many years [37]. These measurements are viewed as the ‘gold standard’ because they are used to develop predictive models and equations to estimate ruminant livestock emissions for national greenhouse gas inventories.

These methods enable complete measurements of production of CH4, gaseous exchanges (O2 consumption and CO2 production) and assessment of other trace gases, and quantifi-cation of heat production that occurs simultaneously, therefore permittingwhole-bodymetabolic rate to be estimated [38]. In respiration chambers, the designmay also enable themeasurement of total tract digestibility and total urine collections to be made concurrent to the measurements of gaseous exchange, providing an opportunity to determine the net energy yielded from known quantities of feeds. The criticism of the approach is that the animal is often fed at maintenance, measurements aremade over short periods (hours to nomore than 3 days), and the eating and/or behaviorof the animal doesnot reflect the free-rangingpattern [37]. It is feasible to feed theanimal in the chamber with dried forage [or potentially fresh forage (cut/carry protocols) [39]] and to align the patterns of voluntary food intake (albeit at restricted levels of feeding) with the individual gas fluxes. However, a lack of knowledge of the steady-state conditions in the rumen, the impacts of the arrival of ingesta in the rumen, and patterns of water consumption on microbial processes compromises the usefulness of suchmeasurements. It should be also considered that the feeding protocolsmay not reflect those of the grazing animal and the chambermay also result in an artificial environment that still produces a coefficient of variation (% CV) between days ranging from 4% to 7% [40,41].

4 Trends in Biotechnology, Month Year, Vol. xx, No. yy

Airflow outlet

Air outlet

Airflow meter

Airflow

RFID reader

Intake manifold

Fan

Air collec�on pipe

Feed inlet

CH4 and CO2 sensors – to electronics

CH4 and CO2 sensors – to electronics

Airinlet

Flow meter and air pump

Sealed entrance

Valve and tube to access the canister and halter

Capillary tube Collec�on canister

Strap to hold the canister and tubing

Gas measurement capsule

Gas sensorPermea�on membrane

Micro controller

Transmission circuit and antenna

Power source

SF6 container with the permea�on membrane

(A) (C)

(D)(B)

Figure 2. Schematics of Different (A) Respiration and (B) Accumulation Chambers and In Situ Gas Measure-ment Techniques, Including (C) Tracers and (D) Gas Sensor Capsules. Abbreviations: CH4, methane; CO2, carbon dioxide; SF6, sulfur hexafluoride.

Estimates of CH4 emissionsmade from grazing animals using amodified headmaskmethod rely on ‘spot sampling’ protocols [42]. These techniques depend on the animal consuming feed at the in-field measurement device and measurement of CH4 concentration in exhaled breath over several minutes of sampling periods to estimate total emissions. All ‘spot sampling’ protocols result in highly variable data sets and only provide a short-term emission rate [19]. However, if enough data are collected from a large number of animals, greater uniformity in sample frequency throughout the 24-h measurement day is gained, and a representative flux can be calculated.

In Situ Gas Measurement: Tracers There has been considerable interest in developing indirect tracer methods because they can be used when the animal is grazing freely and their behavioral processes are not limited by a chamber. Two methods are generally based on the constant release of sulfur hexafluoride (SF6) [35,43,44] and deuterated CH4 (

[7_TD$DIFF]CH3D) [45] tracer gases in the rumen. In theory, 13CH3D is the ideal marker because it is an easily traceable marker that mimics the behavior of CH4 in the liquid fraction of the rumen, the rumen head space, and during eructation. It is also an important tracer gas for discriminating between CH4 that is formed through interfering nonmicrobial methano-genesis (e.g., coal seam gases) and that produced through microbial processes [46]. However, it is prohibitively expensive and, as such, has not been adopted widely. With the upsurge in climate-related livestock research, the SF6method is increasing becoming the favored approach used to estimate CH4 emission from grazing ruminants [47]. To ensure that a gaseous tracer is suitable for the estimation of CH4, the difference between background concentrations and those released must be as large as possible. This is a quality that SF6 provides. SF6 is a gas that is easily measureable and traceable at low concentrations. Additionally, it is synthetic in origin and Trends in Biotechnology, Month Year, Vol. xx, No. yy 5 not produced as part of any biological process. SF6 is also ideal because its background concentration is naturally low (6 pmol/day [48]), while its concentration as a tracer typically ranges from 0.01 to 0.03 mmol/day [47]. In the SF6 tracer gas method, CH4 is measured as the ratio of this gas using themethodology demonstrated in Figure 2. SF6 tracer gas is delivered via a permeation tube, which is placed in the rumen, and the ratio of CH4 to SF6 in the breath of an animal is measured and corrected with reference to the background concentration. As such, if the concentration of the tracer is known, the rate of production of CH4 can be calculated. The technique is difficult to use in practice, but standard operating procedures have been estab-lished [49]. Paradoxically, SF6 is a persistent greenhouse gas with a GWP100 of 22 800 [40]. The difference between measurements using SF6 and respiration chambers is 10% or more [30].

However, this bias is neither consistent nor predictable [49].

In Situ Gas Measurement: Gas Sensor Capsules Gas sensors capsules have been developed for ruminants in climate-related research to monitor CH4, H2, and CO2 concentrations [44] and have also been designed to measure enteric gases in humans [50]. Such gas sensors capsules comprise gas-permeable membranes [51–54], gas sensors, a microcontroller for driving the sensors, digitizing, storing, and coding the signals, a transmitter, an antenna, and a power supply [55]. They concurrently measure the concentrations of CH4, CO2, and H2, but do not measure flux (emission). To enhance instrument utility, measures of internal rumen pressure, rumen size, and eructation pattern can be incorporated to estimate the gas production rates. The simultaneous measurement of CO2 and CH4 con-centrations in rumen and breath (respiratory and eructated) is advantageous to test the feasibility of using CO2 as a tracer gas [56]. This could lead to the use of low-cost hand-held systems to estimate CH4 production.

In Vitro Measurements A range of in vitro gas production techniques (IVGPTs) have been utilized to estimate CH4 production [57,58]. These methods have several significant constraints, including possible artificial incubation periods, a ‘single’ end-point that is used to calculate organic matter degradation, VFA products and gas production (through accumulation and change in pH of incubation), and the possibility that steady-state conditionsmay not be reached. A steady-state condition in rumen processes is defined as when digesta pools within compartments (e.g., rumen) of a dynamic system do not significantly change [59]. IVGPT is defined as a ‘perturbed system’ and quasi-steady-state conditions are maintained [60]. This is important when con-sidering that methanogenic Archaea have a relatively slow population doubling time (likely >10 h [61]). The current approaches using IVGPT measure ultimate CH4 yield from a known quantity of feed incubated in rumen fluid and can be used for ranking the CH4 production potential of those feeds. Recently, there has been interest in developing near-infrared reflec-tance spectroscopy (NIRS) feed evaluation methods in conjunction with IVGPT to measure nutritive characteristics, principally digestibility of feeds, as well as fermentability and CH4 production [62].

In theory, IVGPTs would be rapid and inexpensive approaches for estimating ruminant CH4.

However, in vivo organic matter degradation of feeds is influenced by the level of feeding and physicochemical nature of the feed itself [63]. This suggests that the extent of degradation of a feed is not constant with feed intake and, hence, CH4 productionmay significantly differ between in vitro and in vivo assessments. Furthermore, this raises the possibility that enteric CH4 production should be expressed on a fermentable organic matter basis. This is difficult to do in practice because feed organic matter is fermented both in the rumen and the hind gut, and estimates of digestible organic matter (as measured by the total tract digestibility method) do not accurately reflect organic matter digested in the rumen, which is the major site of CH4 production.

6 Trends in Biotechnology, Month Year, Vol. xx, No. yy

Field Measurements Field-, or herd-, scale measurements using open-path Fourier transformed infrared (FTIR) spectroscopy and open-path laser technologies; mass balance, flux-gradients linked to micrometeorological models, such as eddy covariance; and inverse dispersion methods (back-ward Lagrangian Stochastic models [64]) are often used for estimating emissions from free-ranging ruminants. These techniques are suitable for measurement periods of up to 2 weeks within grazing environments of 0.2–2.0 ha, and animal densities of >30/ha [65].

Open-path micrometeorological measurements of emissions from groups of animals are subject to changes in enteric CH4 emissions of individual animals, behavioral processes of individual and groups of animals, and changes in the local climatic conditions. In many studies, increases in CH4 concentration during the night (from approximately [12_TD$DIFF]23.00 h to [13_TD$DIFF]05.00 h) have been noted.

These changes may not reflect biological processes but microclimatic effects, such as temper-ature inversions, changes in saturated vapor pressure, and low wind speed. If these measure-ments are used in the calculation of total daily emissions, without data quality procedures in place, the overall emission per animal can be inflated. The accuracy of field emission measure-ment techniques has been assessed by controlled gas release verification studies [66,64], by repeated field versus respiration chamber comparisons, and also by comparison with tracer-based methods. Recently, wave-modulation, cavity ring-down spectrometry, and aircraft-mounted quantum cascade lasers have been used to measure CH4 emissions from grazing ruminants over longer periods (weeks to months) and on a landscape scale (>1000 ha) [63]. The use of these approaches to measure CH4 emissions from groups of animals is new, with few published data, especially on the accuracy of measurements, available.

Methane Emission Models Recently, several emissions models have been developed to: (i) predict total emissions from livestock; and (ii) evaluate the impacts of a range of mitigation strategies used for reducing CH4 production [67–69]. Many of these models have been constructed from information based on respiration chamber measurements, voluntary food intake, digestibility of feeds, animal phenotype (live weight and body size), and animal performance (growth, milk production, and constituents yield). A variety of equations have been developed to predict CH4 emissions from livestock. For instance, in the USA, such equations have been extracted for lactating dairy cows using a large database of indirect calorimetry [70]. In this example, the equation was used in conjunction with dietary information to understand both mitigation strategy and economic costs of abating CH4 emissions. The approach taken to construct the initial CH4 emissions model was empirical (statistical) and relatednutrient intake toCH4outputdirectly [71]. Twocriticismsof suchapproaches are that they oversimplify the processes that drive enteric CH4 production (i.e., they generally fail to consider many physiological specification of livestock and/or environmental effects for enteric CH4 production), and that investigations for direct comparison of such models are yet to be performed (e.g., those adopted by the United Nations Framework Convention on Climate Change to predict national enteric CH4 emissions in most countries, including Australia and Canada).

Several dynamic and mechanistic models have been developed that attempt to simulate enteric CH4 emissions based on mathematical descriptions of biological processes [72,73]. These models provide adequate predictions of enteric CH4 production, but are not robust enough to incorporate detailed descriptions of microbiome processes or the interactions between the host animal and the gut microbiome.

In general, the majority of the aforementioned models predict enteric CH4 production on an individual animal basis using tracer (e.g., SF6) or other methods. Those predicted emissions are then scaled up to develop the whole-farm models. However, they are contingent on having reproducible data sets that have been conducted under controlled conditions. Errors associated Trends in Biotechnology, Month Year, Vol. xx, No. yy 7 with estimates of enteric CH4 production of individual animals or micrometeorological-linked approaches are too high to provide an accurate estimation. As such, the modeling techniques only enable researchers to be guided on the expected emissions from herds and flocks. Many of the national inventory greenhouse gas emissions are generally based on such empirical model-ing strategies.

Other Technologies There is a range of other possible technologies that can be used to measure CH4 emissions.

These include, but are not limited to [14_TD$DIFF]: (i) the analysis of the gut microbiome in rumen or excreted in feces in conjunction with ether lipids of archaeal cell membranes [74,75]; (ii) analysis of CH4 emissions based on milk constituents using mid-IR spectroscopy [76]; and (iii) estimating CH4 emissions from livestock based on the use of CO2 as a tracer gas [56]. The use of ether lipids of archaeal cell membranes as a marker for enteric CH4 production has recently been shown to be feasible. A close relation between CH4 production and total methanogen count was observed [75]. However, caution must be taken in interpreting the relation insofar that the association between fecal methanogen concentrations and CH4 output may also reflect differences in the ability of the methanogen to yield CH4 and the diversity of methanogens that are found in the digestive tract. The use of mid-IR spectroscopy of milk constituents and association to enteric CH4 production is still in its infancy [76]. Currently, the cross-correlation relations betweenmid-IR and enteric CH4 production have been investigated using SF6 tracer studies. For reasons outlined here, care should be taken in interpreting these studies and, until studies have been Table 1. Comparison of Different Techniques for Measuring Enteric CH4

Method Cost Advantages Disadvantages

Respiration and accumulation chambers

Generally high

Highly accurate, controlled environment; information about individual animals

Results different from free-range animals;

configurations still vary from one research group to another; an animal adaptation period is required; every 2–3 h[1_TD$DIFF] accumulation [5_TD$DIFF]chambers must release CO2 that builds up

Hood and/or head box systems

Moderate to high

Portable and less expensive than a chamber; requires less space

Do not measure hindgut emissions; an animal adaptation period is required; not designed for grazing situations but are used in those conditions frequently

Tracers Moderate Accurate; few interferences by other gases; the animal can free range

Rely on SF6, which is a greenhouse gas itself;

does not completely capture all tracer and, therefore, relies on spot concentration measurements; high contact with animal, whihc can disrupt normal behavior

Gas sensor capsules

Low Compatible with new electronic technologies; relies on small, low-cost sensors[6_TD$DIFF]; continuous measurements

Information about relation between concentration and flux (emission); still under development

In vitro measurements

Low High reproducibility but used to rank feeds for methaogenic potential and not for measurements of flux; allows different rumen microbial environments to be evaluated

Outcomes can be different from actual measurements; method relies on donor animals for rumen environment;

standardization can be difficult

Field measurements

High Information about many animals; data produced in natural grazing environment

Require expensive and accurate measurement approaches: data processing heavily influenced by microclimatic conditions; loss of data can be high

CH4 emission models

Low Estimate the distribution of production; not limited to any configuration

Can be different from real scenatios; still rely on input data made from respiration and accumulation chambers measurements as well as tracer methods

8 Trends in Biotechnology, Month Year, Vol. xx, No. yy

Outstanding Questions Which other technologies can be used for CH4 measurements? It is known that porous metalorganic frameworks (MOF) are exceptional materials for storing H2-containing gases, such as CH4. Is it possible to use MOFs as inert digesta flow markers as well as a tech-nique to measure CH4 and H2 seques-tered on the material?

Fecal sampling is relatively easy, but is it possible to devise a range of com-pounds other than MOF that adsorb CH4 tightly and can pass through the digestive tract?

What are the opportunities for using cell membrane microbial lipids or con-served glycoproteins unique to the methanogenic Archaea as molecular diagnostics for CH4 production?

There are new approaches in usingCO2

(e.g., stable isotope analysis) as a tracer for CH4 rather than the traditional published using direct measurement of CH4, they should be viewed as preliminary. Estimating CH4 emissions from the erupted and respiratory CO2 as a tracer has also so far mostly resulted in crude outcomes, significantly deviating from the expected emission values [56].

Concluding Remarks and Future Perspectives Here, we have outlined the most common techniques used to measure enteric CH4 production and have discussed some of their advantages and disadvantages. A synopsis is presented in Table 1. These methods range from measurement techniques for the CH4 production by individual animals to those that can be used in the field with groups of animals. None of these methods are perfect, which is an observation that should be considered before embarking on CH4 measurements on live animals. It is also critical that the context of the measurement is known. New technologies are rapidly evolving that are more accurate and have a relatively lower cost compared with current approaches. Some of these technologies will also provide future avenues for considering new possibilities in assessing CH4 production and answering the questions that remain (see Outstanding Questions).

Acknowledgment The authors acknowledge support from the Australian Government Department of Agriculture's Filling the Research Gap

Program (grant no. B.CCH.6220 and B.CCH.6210).

References approach of using SF6. Respiratory and rumen CO2 currently confound such measurements, but is there a way to separate these pathways?

How can we use phenotypic and geno-typic information to identify ‘low’ and ‘high’ CH4-emitting animals as well as favorable low CH4-producing micro-biome? There is a limited number of studies examining the interaction between the host animal and the rumen microbiome (e.g., the Rumen Pan-genome program hosted by the Univer-sity of Western Australia). Recently, whole-genome analysis has been final-ized for sheep [77] and key rumen methanogens [78]. How will the meas-urements of the host animal phenotype (CH4 emissions, rumen size and mor-phology, and digesta flow rate), the host genotype (imputed genome sequence), transcriptome (RNA sequence and spe-cies identification) of the gastrointestinal tract and the rumen microbial metage-nome of the rumenmicrobial population explain differences in rumen CH4 pro-duction between individual animals?

Approaches to measure and predict CH4 production from individual animals under grazing conditions are still incom-plete. How can a better understanding of thebehavioral processesofananimal, including its foraging and CH4 emis-sions, be gained to help in developing new stochastic models and measure-ment algorithms for CH4 production?

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