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Strategies to Mitigate Enteric Methane Emissions by Ruminants -A Way to Approach the 2.0°C Target

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Abstract

Ruminant livestock enteric fermentation contributes approximately one-third of the global anthropogenic methane (CH 4 ) emissions and is projected to increase significantly to meet the increasing demand for animal-sourced protein. Methane, a short-lived greenhouse gas, needs to be reduced -24 to -47% by 2050 relative to 2010 to meet the 2.0°C target. This study describes the results of a comprehensive meta-analysis to determine effective mitigation strategies. The database included findings from 425 peer-reviewed studies (1963 to 2018). Mitigation strategies were classified into three main categories [animal and feed management, diet formulation, and rumen manipulation (additives and methods used to modify the rumen)] and up to five subcategories (98 total mitigation strategy combinations). A random-effects meta-analysis weighted by inverse variance was carried out (Comprehensive Meta-Analysis, V3.3.070). Five feeding strategies, namely CH 4 inhibitors, oils and fats, oilseeds, electron sinks, and tanniferous forages, decreased absolute CH 4 emissions by on average -21% (range -12 to -35%) and CH 4 emissions per unit of product (CH 4 I; meat or milk) by on average -17% (range -12 to -32%) without negatively affecting animal production (weight gain or milk yield). Furthermore, three strategies, namely decreasing dietary forage-to-concentrate ratio, increasing feeding level, and decreasing grass maturity, decreased CH 4 I by on average -12% (range -9 to -17%) and increased animal production by on average 45% (range 9 to 162%). The latter strategies are central to meeting the increasing demand for animal-sourced food. All strategies, but CH 4 inhibitors, can be implemented now and offer immediate approaches for combating global warming.
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Strategies to Mitigate Enteric Methane Emissions by
Ruminants A Way to Approach the 2.0°C Target
Claudia Arndta*, Alexander N. Hristovb, William J. Pricec, Shelby C. McClellandd,
Amalia M. Pelaeze, Sergio F. Cuevab, Joonpyo Ohb, André Banninke, Ali R. Bayatf, Les
A. Cromptong, Jan Dijkstrae, Maguy A. Eugèneh, Ermias Kebreabi, Michael Kreuzerj,
Mark McGeek, Cécile Martinh, Charles J. Newboldl, Christopher K. Reynoldsg, Angela
Schwarmm, Kevin J. Shingfieldf**, Jolien B. Venemann, David R. Yáñez-Ruizo, and
Zhongtang Yup.
aNational Agrarian University - La Molina, Lima, Peru; bThe Pennsylvania State
University, University Park, USA; cUniversity of Idaho, Moscow, USA; dColorado State
University, Fort Collins, USA; eWageningen University and Research, Wageningen, The
Netherlands; fNatural Resources Institute Finland, Helsinki, Finland; gUniversity of
Reading, Earley Gate, Reading, UK; hINRAE, UCA-VAS, UMRH Centre ARA, Saint-
Genès-Champanelle, France; iUniversity of California, Davis, USA; jETH Zurich, Zürich,
Switzerland; kTeagasc, AGRIC, Grange, Ireland; lSRUC, Edinburgh, United
Kingdom; mNorwegian University of Life Sciences, Aas, Norway; nDe Heus Animal
Nutrition, Ede, The Netherlands; oEstación Experimental del Zaidín, CSIC, Granada,
Spain; pThe Ohio State University, Columbus, USA.
*Correspondence:
Claudia Arndt
arndt.claudia.ca@gmail.com
**The author is deceased.
2
ABSTRACT
Ruminant livestock enteric fermentation contributes approximately one-third of the
global anthropogenic methane (CH4) emissions and is projected to increase significantly
to meet the increasing demand for animal-sourced protein. Methane, a short-lived
greenhouse gas, needs to be reduced -24 to -47% by 2050 relative to 2010 to meet the
2.0°C target. This study describes the results of a comprehensive meta-analysis to
determine effective mitigation strategies. The database included findings from 425 peer-
reviewed studies (1963 to 2018). Mitigation strategies were classified into three main
categories [animal and feed management, diet formulation, and rumen manipulation
(additives and methods used to modify the rumen)] and up to five subcategories (98 total
mitigation strategy combinations). A random-effects meta-analysis weighted by inverse
variance was carried out (Comprehensive Meta-Analysis, V3.3.070). Five feeding
strategies, namely CH4 inhibitors, oils and fats, oilseeds, electron sinks, and tanniferous
forages, decreased absolute CH4 emissions by on average -21% (range -12 to -35%) and
CH4 emissions per unit of product (CH4I; meat or milk) by on average -17% (range -12 to
-32%) without negatively affecting animal production (weight gain or milk yield).
Furthermore, three strategies, namely decreasing dietary forage-to-concentrate ratio,
increasing feeding level, and decreasing grass maturity, decreased CH4I by on average -
12% (range -9 to -17%) and increased animal production by on average 45% (range 9 to
162%). The latter strategies are central to meeting the increasing demand for animal-
sourced food. All strategies, but CH4 inhibitors, can be implemented now and offer
immediate approaches for combating global warming.
SIGNIFICANCE STATEMENT
Ruminant enteric fermentation is a major contributor to global anthropogenic methane
emissions. The demand for animal-sourced products and associated methane emissions
are projected to increase, which could prohibit reaching the 2.0°C target. This meta-
analysis was undertaken to identify effective mitigation strategies to resolve this issue.
We determined five strategies (the supplementation of methane inhibitors, oils and fats,
oilseeds, electron sinks, and tanniferous forages) that decrease absolute and product-
based methane emissions without negatively affecting animal productivity, and three
strategies (decreasing dietary forage-to-concentrate ratio, increasing feeding level, and
decreasing grass maturity) that decrease product-based methane emissions and increase
animal productivity. All strategies, except methane inhibitors, can be adopted now and
offer an immediate approach to combat global warming.
3
INTRODUCTION
The goal of the Paris Agreement, to limit global warming to 2.0°C above pre-industrial
levels, is unlikely to be achieved if food systems continue operating on a business-as-
usual scenario1. Thus, it is of utmost importance to determine and implement strategies
that mitigate food-related greenhouse gas (GHG) emissions. Among the food-related
GHG emissions, methane (CH4) emissions from enteric fermentation by ruminant
livestock contribute 30% of the global anthropogenic CH4 emissions2. As CH4 is a
powerful but short-lived GHG, decreasing global CH4 emissions is especially important
for limiting global warming in the short-term. This urgency has been underlined by the
European Commission, which recently published the EU Methane Strategy3 that is
essential to meet the EU’s nationally determined contributions under the Paris Agreement
and its 2050 climate neutrality goal.
In addition to the Paris Agreement, the international community also agreed to 17
Sustainable Development Goals (SDGs) to achieve sustainable development by 20304.
These include SDG 1 - no poverty, SDG 2 - no hunger, and SDG 13 - climate action.
Consequently, measures to address SDG 13 (climate action) cannot countervail other
SDGs, in particular SDG 2 (zero hunger). This is explicitly highlighted in article 2.1 (b)
of the Paris Agreement "Increasing the ability to adapt to the adverse impacts of climate
change and foster climate resilience and low greenhouse gas emissions development, in a
manner that does not threaten food production"5.
Given all this, effective mitigation strategies that comply with both SDG 13 (climate
action) and SDG 2 (zero hunger) are urgently needed. Accordingly, the challenge facing
food systems is the need to reduce CH4 emissions from animal production by -24 to -47%
by 2050 relative to 20106, while simultaneously increasing the production of animal-
sourced food to meet the projected 68% increase in demand between 2010 and 20507.
Reaching these apparently conflicting twin goals will require effective enteric CH4
mitigation strategies that, at a minimum, do not compromise animal productivity or have
other unacceptable tradeoffs8 and, ideally, increase animal-sourced food production.
Strategies that increase animal production and reduce product-based CH4 emissions (i.e.,
emission intensity variables CH4IG and CH4IM, emission per unit of weight gain or milk
produced, respectively) are especially paramount in low and middle-income countries
where productivity and production per animal are low9,10. Advocates of reducing the
global ruminant population as a means to achieve climate change mitigation goals have
acknowledged that this approach is particularly inappropriate for low-income countries11.
Therefore ruminants are of major importance to achieving SDG 2 (zero hunger), as they
provide food for human consumption from marginal lands and in subsistence agriculture
situations.
4
Several reviews have determined that animal and feed management, diet formulation, and
rumen manipulation strategies could significantly decrease enteric CH4 emissions8,12,13.
However, thus far studies either only investigated the quantitative effects of a single
mitigation strategy or only compared CH4 yield (CH4Y; CH4 per unit of feed intake)
between multiple mitigation strategies. Nonetheless, CH4Y is only one measure and other
important CH4 emission and animal performance metrics must be considered to
determine the effectiveness and feasibility of mitigation strategies. Important CH4
emission metrics include daily CH4 emissions, CH4Y, CH4-energy conversion factor [Ym;
CH4 energy as a proportion of gross energy intake; a component of the Tier 2 calculation
for national GHG inventories recommended by the Intergovernmental Panel on Climate
Change14], CH4IG, and CH4IM. Important animal performance metrics include feed intake,
nutrient digestibility, and animal production.
The objective of this study was to conduct a comprehensive meta-analysis of enteric CH4
mitigation strategies published in peer-reviewed journals by examining their quantitative
effects on the aforementioned CH4 emission and animal performance metrics. There is an
urgent requirement for strategies that can effectively mitigate both absolute and product-
based CH4 emissions without negatively affecting animal productivity or that can
effectively mitigate product-based CH4 emissions while increasing animal-sourced food
production. Our approach of identifying effective ´dual-action´ strategies ensures that
both the ´climate action´ objective of SDG 13 and the ´zero hunger´ objective of SDG 2
are targeted simultaneously.
5
RESULTS AND DISCUSSION
The meta-analysis included 98 mitigation strategies reported in 425 peer-review journal
publications (Supplementary Table 1). Mitigation strategies were classified into three
main categories: animal and feed management, diet formulation, or rumen manipulation
strategies. Of the strategies included, 63 did not significantly (adjusted P ≥ 0.05) decrease
daily CH4 emissions; the remaining 35 strategies decreased daily CH4 emissions and
CH4Y by on average -18% (ranging from -5 to -43%) and -14% (ranging from -4 to -
37%), respectively. These strategies were classified as ‘effective’ in decreasing absolute
and product-based CH4 emissions, if they significantly (adjusted P < 0.05) decreased
daily CH4 emissions, CH4Y, and CH4IG or CH4IM without decreasing animal production
(weight gain of growing animals or milk yield of dairy animals) when production data
were present. Strategies were also classified as ‘effective’ in decreasing product-based
CH4 emissions if they significantly decreased CH4Y and CH4IG or CH4IM while
significantly increasing animal production. A summary of the studied mitigation
strategies is presented in Fig. 1 and the full list of the studied mitigation strategies is
presented in Supplementary Tables 2.
Effective mitigation strategies in the order of efficacy and their effect on CH4 and animal
performance metrics as well as their relevance for confinement or grazing systems are
presented in Fig. 2. As CH4Y was highly correlated with Ym (adjusted R2 = 0.83;
Supplementary Fig. 1) and more data were available for CH4Y than for Ym
(Supplementary Fig. 2), only results for CH4Y are presented and discussed here. All other
strategies that were not classified as effective but had a significant effect on CH4, CH4Y,
Ym, CH4IG or CH4IM are presented in Supplementary Fig. 3 to 5. The CH4 inhibitor
bromochloromethane was not classified as effective, despite fulfilling the selection
criteria for an effective mitigation strategy, because it is an ozone-depleting compound
that is harmful to aquatic organisms and a confirmed carcinogen15. Furthermore, several
mitigation strategies were excluded from the present evaluation or classified as
ineffective because of insufficient publications and warrant further research. These
include breeding low-CH4 emitting animals and improving animal health. Modeling
studies have shown that strategies that improve animal health can significantly increase
animal productivity and reduce emission intensity16. In the subsequent text, the effects of
mitigation strategies on CH4 emissions and animal performance metrics are reported in
parenthesis as mean, 95% confidence interval (CI), and number of treatment comparisons
(n). Reported differences were significant (adjusted P < 0.05) unless indicated otherwise.
6
Strategies that decrease absolute and product-based CH4 emissions
Rumen manipulation by feeding CH4 inhibitors effectively decreased daily CH4
emissions (mean = -35%, 95% CI = -30 to -40%, n = 23, throughout the paper). Within
this category, 3-nitrooxypropanol (3-NOP) is most effective acting on methyl-coenzyme
M reductase, a key enzyme of the methanogenesis pathway of archaea17. Its
supplementation decreased daily CH4 emissions (-39%, -29 to -47%, 11), CH4Y (-37%, -
26 to -46%, 12), and CH4IM (-31%, -21 to -40%, 2) without affecting feed intake or milk
yield. Insufficient data were available to evaluate its effect on weight gain or fiber
digestibility in this analysis. However, in recent studies, 3-NOP did not show adverse
effects on weight gain of growing beef cattle18 or fiber digestibility in early-lactation
dairy cows19 and decreased daily CH4 emissions throughout a 15-week experiment20. A
recent meta-analysis showed that 3-NOP decreases daily CH4 emissions in a dose-
response manner, that its mitigation effect is greater for dairy than beef cattle, and that its
effectiveness decreases with increasing dietary fiber content21. In its current form, 3-NOP
can only be used in confinement systems, because it is more effective when fed
continuously within the animals’ diet20,22, but ongoing research is developing
mechanisms for its application under grazing conditions23. Supplementation of 3-NOP
increased milk fat content in dairy cattle19 and feed efficiency in feedlot cattle24, which
may help offset its cost and stimulate adoption. A limitation of 3-NOP is that its use as a
feed additive requires regulatory approval by various countries. Another CH4 inhibitor
strategy is supplementation with seaweed (e.g. Asparagopsis taxiformis), which can
decrease daily CH4 emissions by up to 80%25. However, more research is warranted on
dietary inclusion levels, effects on animal feed intake and production26, the implications
and safety of feeding bromoform27, its main active compound28, the extremely high
iodine content of Asparagopsis species (which limits how much can be fed in many
countries), as well as the environmental effects of cultivating seaweed29 before it can be
recommended as a mitigation strategy.
Dietary inclusion of oil and fat decreased daily CH4 emissions (-20%, -15 to -24%, 63)
and CH4Y (-15%, -11 to 18%, 52). Weight gain in growing animals or milk production in
dairy animals was unaffected despite decreasing feed intake (-6%, -3 to -8%, 58) and
fiber digestibility (-4%, -2 to -7%, 37). This resulted in decreased CH4IG (-22%, -8 to -
35%, 6) and CH4IM (-12%, -6 to -18%, 24); however, possible effects on manure CH4
emissions due to decreased fiber digestibility need to be evaluated14. Of the subcategories
included here, only dietary inclusion of predominantly vegetable oils effectively
decreased daily CH4 emissions. This effect can be attributed to increased supply of non-
fermentable highly digestible energy, a decreased feed intake and fiber digestibility as
well as inhibition of methanogenesis by unsaturated (or medium-chain saturated) fatty
7
acids, which are usually abundant in vegetable oils. Other meta-analyses also found that
oil inclusion decreased CH4Y (between -9 to -14%), feed intake (-6%) and increased milk
yield (+4%)13,30. Oil inclusion reportedly decreases daily CH4 emissions in a dose-
response manner30 and over the long-term31,32. The amount of oil that can be included in
ruminant diets, however, is limited and inclusion level should not be at the expense of
healthy rumen fermentation that may negatively impact animal health and productivity.
Maximum oil inclusion levels in ruminant diets depend on the animals´ physiological
stage, lipid and other nutrient composition of the basal diet, and fatty acid profile of the
supplemental oil33. Vegetable oils that effectively decreased daily CH4 emissions were:
(1) coconut oil (-28%, -20 to -35%, 16), (2) canola oil (-22%, -12 to -32%, 4), (3) linseed
oil (-22%, -14 to -29%, 14), and (4) sunflower oil (-17%, -9 to -24%, 5). The cost-
effectiveness of feeding oils to decrease daily CH4 emissions likely varies by region and
country, because oil and meat and milk prices vary considerably therein. Studies in
China34, France35, or the Netherlands36 found that dietary inclusion of oils, for the
purpose of mitigating enteric CH4 emissions, was not cost-effective, but trade-offs by
concomitant improvements in the fatty acid profile of milk and meat from a human-
health perspective might help to support the implementation of certain oils and oilseeds.
Dietary inclusion of oilseeds (cracked or crushed) had similar effects on CH4 emissions
and animal performance metrics as the inclusion of oils, even though part of the oil in
crushed oilseeds is rumen-protected. Oilseeds decreased daily CH4 emissions (-20%, -15
to -24%, 26), CH4Y (-14%, -8 to -20%, 18), and CH4IM (-12%, -4 to -19%, 6), tended to
decrease feed intake (-4%, -1 to -7%, 25, P = 0.06), and decreased fiber digestibility (-
8%, -6 to -11%, 13). Similar to oils, oilseeds had no effect on milk yield but decreased
weight gain in growing animals (-13%, -6 to -20%, 8); thus, dietary oilseed inclusion may
only be recommended for lactating dairy animals and not for growing animals. Likewise,
the inclusion of oilseeds needs to be limited to not negatively impact rumen fermentation,
animal health and production. However, as part of the oil in oilseeds is rumen-protected,
dietary inclusion levels can be slightly higher than oils37. In addition, similar to oil
inclusion possible effects on manure CH4 emissions due to decreased fiber digestibility
need to be evaluated. Oilseeds that effectively decreased daily CH4 emissions were: (1)
sunflower seeds (-39%, -15 to -57%, 3), (2) cottonseeds (-19%, -13 to -23%, 7), (3)
linseeds (-17%, -2 to -29%, 4) and (4) canola seeds (-13%, -10 to -16%, 8).
Rumen manipulation with electron sinks, alternative electron acceptors that can redirect
hydrogen from methanogenic archaea towards metabolically beneficial sinks in the
rumen38, decreased daily CH4 emissions (-17%, -14 to -20%, 54) and CH4Y (-15%, -13 to
-18%, 51). Despite small decreases in feed intake (-2%, -1 to -3%, 49) small increases in
milk yield (+3%, +1 to +5%, 13) were observed, resulting in decreased CH4IG (-12%, -2
8
to -20%, 3) and CH4IM (-13%, -9 to -16%, 12). Of the studied electron sinks (fumaric
acid and nitrate), only nitrate was classified as effective. Another meta-analysis found
similar effects of nitrate on daily CH4 emissions (-15%)39. Nitrate has also been shown to
decrease daily CH4 emissions and CH4Y in a dose-response manner with no loss of
effectiveness over and effectively decreased CH4 over the long-term40,41. Similar to 3-
NOP, nitrate was more effective in decreasing daily CH4 emissions and CH4Y in dairy
than in beef cattle39. Although nitrate can be toxic, early research on nitrate
supplementation in ruminant diets reported a decrease in feed intake and no toxicity
symptoms; however, toxicity can occur if animals are not properly acclimatized42.
Acclimatization of animals to dietary nitrate is required to avoid methemoglobinemia, but
rumen adaptation can be lost within three weeks if nitrate is not continuously fed43.
Simultaneous sulfate supplementation has been shown to help protect cattle against
nitrate toxicity40. Nitrate supplementation may increase enteric and possibly manure
nitrous oxide emissions44. Studies in France35 and the Netherlands36 found that nitrate
supplementation was not cost-effective.
Dietary inclusion of tanniferous forages decreased daily CH4 emissions (-12%, -7 to -
16%, 42) and CH4Y (-10%, -6 to -14%, 39) without affecting feed intake or animal
production and consequently decreased CH4IM (-18%, -8 to -26%, 7). However, it also
decreased fiber digestibility (-7%, -2 to -12%, 21), which could potentially increase
manure CH4 emissions14. Sericea lespedeza (Lespedeza cuneata) decreased daily CH4
emissions (-32%, -24 to -39%, 5) without affecting feed intake in goats and it has been
effective in decreasing daily CH4 emissions throughout a 12-week experiment45. Other
tanniferous forages that may potentially decrease daily CH4 emissions are Leucaena (-
8%, 0 to -16%, 12, P = 0.10) and Lotus (corniculatus and pedunculatus) (-8%, -3 to -
13%, 3). Although this meta-analysis did not reveal any effect on feed intake, tanniferous
forages have been associated with decreased palatability and feed intake46. Tannins can
bind to dietary protein and thus decrease protein digestion and animal production,
especially when dietary protein is limiting. Nevertheless, when dietary protein is
excessive or highly degradable, tannins may be beneficial, because they reduce excretion
of nitrogen in urine, which decreases ammonia and nitrous oxide emissions from
manure47. The cost-effectiveness of their supplementation still needs to be evaluated.
Among the identified effective strategies to decrease absolute and product-based CH4
emissions, dietary inclusion of tanniferous forages is the only one applicable to both
confinement and grazing systems. This is important as 37% of global enteric CH4
emissions are attributed to grazing systems48.
9
Strategies that decrease product-based CH4 emissions
Decreasing dietary forage-to-concentrate ratio decreased CH4Y (-13%, -10 to -16%, 69)
without increasing daily CH4 emissions despite increasing feed intake (+9%, +5 to +14%,
85). The associated increase in overall feed intake did not affect fiber digestibility and led
to an increase in weight gain (+21%, +13 to +29%, 32) and milk yield (+17%, +10 to
+24%, 26). Consequently, CH4IG (-9%, -3 to -15%, 16) and CH4IM (-9%, -4 to -14%, 19)
were decreased. The reduction in CH4Y was most likely the result of a shift in rumen
fermentation patterns and a decrease in rumen pH, which inhibits methanogens38.
However, the supplementation of grain-based concentrate needs to be limited, because
overfeeding can lead to subacute ruminal acidosis. Subacute ruminal acidosis is a
nutritional disease that is associated with perturbation of rumen fermentation and
decreased fiber digestibility, milk fat content, and animal health mostly found in feedlot
and high-yielding dairy cattle49. In addition, the promotion of increased use of (food-
quality) grain-based concentrate in ruminant diets will likely intensify feed-food
competition. In contrast, if concentrate-rich diets are mainly based on food industry by-
products, the feed food-competition may be avoided. The cost-effectiveness of this
strategy will depend on forage and concentrate costs as well as associated increases in
animal production and the price of animal products (meat and milk).
Increasing feeding level (+58%, +47 to +71%, 47) increased daily CH4 emissions
(+18%, +14 to +22%, 42), but decreased CH4Y (-8%, -4 to -12%, 31). Fiber digestibility
was decreased (-7%, -2 to -12%, 18), likely due to increased rumen passage rates50.
Increasing feed intake resulted in increased weight gain (+162%, +38 to +398%, 7) and
milk yield (+17%, +10 to +25%, 8) and decreased CH4IM (-17%, -9 to -23%, 5). No data
were available for CH4IG. Similar to our data, a recent study showed that increasing the
level of feeding decreased CH4Y, while increasing daily CH451. Increasing feed intake to
improve animal productivity significantly decreases CH4IG and CH4IM8,52 and the overall
carbon footprint of animal-sourced food53 when diet composition remains unchanged.
This strategy directs energy for CH4 towards animal production51 but also decreases
energy requirements for maintenance relative to milk production and reduces the time to
slaughter for growing animals. Increased feeding level also causes differences in
digestive efficiency including microbial metabolism, particle passage and digestive
kinetics, all of which contribute to the negative relationship between CH4Y and
increasing feed intake8. Potential effects of this practice on manure CH4 emissions, as a
result of decreased fiber digestibility, need to be evaluated. The practice is applicable to
both confinement and grazing systems, but particularly the latter and especially in certain
climatic regions where animals are underfed due to insufficient or low nutritive forage54.
10
Decreasing grass maturity decreased CH4Y (-4%, -1 to -8%, 8) but not daily CH4
emissions. It did not affect feed intake but increased milk yield (+9%, +1 to +18%, 6) and
thus decreased CH4IM (-13%, -7 to -18%, 6). Furthermore, decreasing grass maturity
improved fiber digestibility (+15%, +9 to +21%, 9), which can potentially decrease manure
CH4 emissions14. Insufficient data were available for growing animals and thus, based on
our analysis this mitigation strategy can currently only be recommended for lactating
animals. The positive effect of decreasing grass maturity on milk yield is likely attributed
to greater digestible energy and protein content. Increased protein content, however, can
lead to increased nitrogen intake and excretion55. Thus, possible tradeoffs associated with
direct and indirect manure nitrous oxide emissions require further evaluation. This strategy
is applicable to both confinement and grazing systems. Although decreasing grass maturity
increases the overall efficiency of dietary nutrient use for milk production (kg milk per unit
of feed intake) and milk production, it was not deemed to be cost-effective in the
Netherlands; however, it was more cost-effective than supplementation with nitrate or
linseed36.
11
CONCLUSION
Effective strategies that reduced daily and product-based CH4 emissions without
negatively affecting animal production decreased daily CH4 emissions by on average -
21% (range from -10 to -35%) and product-based emissions by on average -17% (range
from -12 to -32%). Strategies that reduced product-based CH4 emissions and increased
animal production decreased product-based CH4 emissions by on average -12% (range
from -9 to -17%), and increased animal production by on average +45% (range from +9
to +162%). Nevertheless, future studies should continue to explore novel mitigation
strategies and possible synergistic effects of combining effective mitigation strategies,
e.g. 3-NOP with lipids or lipids with nitrates, to develop innovative strategies that have a
large mitigation potential. In addition, possible tradeoffs and pollution swapping with
upstream processes, such as GHG emissions associated with feed productions as well as
manure GHG emissions that could offset gains in enteric CH4 mitigation need to be
investigated. Of the effective strategies that decrease absolute and product-based CH4
emissions, only tanniferous forages are applicable in grazing systems, and it is of utmost
importance that more strategies are developed for these systems. Strategies that mitigate
enteric CH4 emissions whilst improving animal production are of particular relevance in
view of the significant role of ruminants in providing food for human consumption in
low-income countries. All identified effective mitigation strategies, except for the
supplementation of 3-NOP, could be implemented today. Owing to the short-lived
manner of CH4 as a GHG, any such strategy implemented today will significantly reduce
the contributions of food systems to global warming by 2030, and is a way to approach
the 2°C target.
12
Materials and Methods
Literature Search and Classification of Mitigation Strategies. The database for this
meta-analysis was compiled using data obtained by searching the databases of the
Commonwealth Agricultural Bureau International (CABI), the EBSCO Discovery
Service, and the Web of Science from 1964 to 2018. Publications from 1964 through
2016 were searched using CABI and EBSCO Discovery Service with the search terms
‘rumen’ AND ‘methane’ and an additional four searches were completed in the EBSCO
Discovery Service using the term ‘rumen’ in combination with ‘methane’, ‘energy
partitioning’, ‘energy metabolism’, or ‘energy balance’. Publications from 2017 through
2018 were searched using CABI and Web of Science databases. Seven searches were
conducted with the search term ‘methane’ in combination with ‘beef’, ‘cattle’, ‘dairy’,
‘goat’, ‘sheep’, ‘rumen’, or ‘ruminant’ and three searches with the search term ‘rumen’ in
combination with ‘energy balance’, ‘energy metabolism’, or ‘energy partitioning’.
Publications listed in an independently developed database supported by the AnimalChange
project, MitiGate13, were merged with the database created in the current analysis.
The abstracts of the publications found in the search were reviewed and, based on
abstract content, publications were selected for further consideration if they included in
vivo measurement of enteric CH4 emissions, a clearly defined treatment and control, and
multiple replications (i.e., at least four or more animals in continuous design experiments,
crossover design experiments, etc.). Publications were excluded if they were not from
peer-reviewed literature or if they were not in English, French, German, or Portuguese.
Furthermore, publications were excluded if they were based on inappropriate study
design (i.e., experimental period ≤ 10 days) or measurement technique (e.g. the ‘sniffer
technique’ that is based on the CH4-to-carbon dioxide ratio of exhaled breath56,57).
The completed database consisted of 650 publications. From these, only publications that
had a treatment that could be assigned to one of three main mitigation categories, as
described below, and reported statistical variance for at least one of the CH4 emissions
emission metrics (e.g. LSD, RSD, or SE of the mean) were included in the final analysis.
WebPlotDigitizer (https://automeris.io/WebPlotDigitizer/; accessed 30 October 2019)
was used to determine absolute values for a total of nine metrics in seven publications
where data were reported as figures.
Data were classified into three main mitigation categories: (1) animal and feed
management, (2) diet formulation, and (3) rumen manipulation, each of which was then
further classified into up to five subcategories (Supplementary Table 2). Only mitigation
strategies, for which at least two publications were available for at least one CH4
emission metric and two of the remaining CH4 emission or animal metrics, were analyzed
within a main category. Treatment effects were assessed relative to their respective
control values for all responses, therefore, closely related variables and variables with
13
different units were included in the analysis. For example, CH4IM included daily CH4
emissions per liter of milk and milk corrected for fixed energy, fat and protein, or milk
solids (all milk non-water components combined) content as well as milk solids yield.
Similarly, for CH4IG, both weight gain and carcass gain were used. Metrics for feed
intake included intakes of dry matter, gross energy, organic matter, and intake expressed
per unit of body weight or metabolic body weight. Digestibility (of fiber) metrics
included only apparent digestibility of neutral detergent fiber. Where multiple treatments
of a common treatment type were present within an experiment, those treatment means
were averaged, and their respective errors pooled, such that each experiment produced a
single “Treatment” and “Control” pair of response means and SDs.
The final meta-analysis included data from 425 peer-reviewed publications, of which
66% were with cattle, 31% with small ruminants (sheep and goats) and 3% with other
ruminant species (buffalo, deer, and yak). The complete list of references used in the
current analysis is given in Supplementary Table 1. The majority of publications reported
daily CH4 emissions (92%), feed intake (84%), and CH4Y (71%), whereas less than half
of the publications reported weight gain for all animal types (growing, lactating, and
other adult animals) (49%), Ym (48%), fiber digestibility (41%), milk yield (29%), CH4IM
(21%), or CH4IG (7%) (Supplemental Fig. 2). The final analysis only included weight
gain data for growing animals (106 publications), which led to the exclusion of the
weight gain data of half of the publications (104) that reported weight gain data for
lactating and other adult animals.
Statistical Analysis. A mixed model meta-analysis weighted by inverse variance was
carried out considering treatment mean comparisons within publication as a random
effect. Analyses were run across all ruminant species (cattle, buffalo, deer, goat, sheep,
and yak) and included main mitigation strategies and their respective subcategories as
potential moderator fixed effects. Analyses were conducted separately for each of the
nine response variables (daily CH4, CH4Y, Ym, CH4IG, CH4IM, feed intake, weight gain
for growing animals, milk yield, and fiber digestibility) using a log ratio of means,
namely log(Treatment/Control), in order to standardize treatment effects across multiple
measures, species, and outcomes, as well as to allow the expression of treatment
differences as relative percentages58,59. Weight gain for growing animals when consuming
tanniferous plants, however, was assessed based on a standardized relative difference,
[(Treatment-Control)/SEDiff], due to the presence of negative growth rate responses in
two treatment mean comparisons59. Computations were carried out using Comprehensive
Meta-Analysis (V. 3.3.070; Biostat, Englewood, NJ). All analyses were adjusted for
multiple comparisons using a step-down Bonferroni procedure to reduce the risk of Type
I error60 (SAS, V. 9.4; SAS Inst. Inc, Cary, NC). The effect of a mitigation strategy was
considered to be significant for adjusted P < 0.05 and 0.05 ≤ adjusted P ≤ 0.10 was
considered as a trend.
14
ACKNOWLEDGMENTS
The authors want to thank the GLOBAL NETWORK project for generating part of the
database. The GLOBAL NETWORK project
(https://globalresearchalliance.org/research/livestock/collaborative-activities/global-
research-project/; accessed 20 June, 2020) was a multi-national initiative funded by the
Joint Programming Initiative on Agriculture, Food Security and Climate Change and was
coordinated by the Feed and Nutrition Network
(https://globalresearchalliance.org/research/livestock/networks/feed-nutrition-network/;
accessed 20 June, 2020) within the Livestock Research Group of the Global Research
Alliance on Agricultural GHG (https://globalresearchalliance.org; accessed 20 June,
2020).
The authors want to thank MitiGate, which was part of the AnimalChange project funded
by the EU under Grant Agreement FP7-266018 for sharing their database with us
(http://mitigate.ibers.aber.ac.uk/, accessed July 1, 2017). Part of C. Arndt’s, A. N.
Hristov’s, and S. C. McClelland´s time in the early stages of this project was funded by
the Kravis Scientific Research Fund (New York, NY) and a gift from Sue and Steve
Mandel to Environmental Defense Fund. Another part of C. Arndt’s work on this project
was supported by the FONDECYT contract (N° 016-2019-FONDECYT-BM-INC.INV)
and of A. Hristov's work by the USDA (Washington, DC) National Institute of Food and
Agriculture Federal Appropriations under Project PEN 04539 and Accession Number
1000803. E. Kebreab was supported by the Sesnon Endowed Chair Fund of the
University of California, Davis.
15
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20
FIGURES AND TABLES
Figure 1. Studied enteric methane mitigation strategies. For a complete list of strategies,
see supplementary Table S2.
21
A
B
Figure 2. Effective mitigation strategies and their effect on methane (CH4) emission
(a) and animal performance metrics (b). Daily CH4 = daily CH4 emission (g animal-1 day-1);
CH4Y = CH4 yield (CH4 g per kg of dry matter intake), CH4IG = CH4 emission intensity for weight gain (g
CH4 per kg of weight gain for growing animals), CH4IM = CH4 emission intensity for milk (CH4 g per kg of
milk), Intake = dry matter intake (kg d-1); Digestibility = apparent digestibility of neutral detergent fiber
(%); Gain = average daily gain (kg d-1), Milk = milk yield (kg d-1); when numeric values are shown a
significant effect was observed (adjusted P < 0.05) and no effect when adjusted P ≥ 0.05.
22
SUPPLEMENTARY INFORMATION
SUPPLEMENATARY TABLES
Supplementary Table 1. Publications included in this meta-analysis.
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Supplementary Table 2. Mitigation strategies (categories and subcategories) included in this meta-analysis.
Animal and feed management
Diet formulation
Rumen manipulation
Feed processing
By-products
Additives
Forage processing
Fiber sources
Amino acids
Urea-treated straw
Soybean hulls
CH4 inhibitors
Grain processing
Glycerol
3-nitrooxypropanol
Genetic Selection
Lipid sources
Bromochloromethane
Low residual feed intake
Extruded canola
Enzymes
Low CH4 emitter
Extruded linseed
Galactooligosaccharides
Improving health
Protein sources
Ionophores
Improving pasture management
Distiller´s dried grains with solubles
Monensin
Grazing plus supplementation
Soybean meal
Organic acids
Grazing plus concentrate
Pulp sources
Carboxylic acids
Improved pasture
Citrus pulps
Long chain fatty acids
Increased Nitrongen fertilization
Decreasing forage-to-concentrate ratio
Unsaturated fatty acids
Legume-grass vs. grass only pastures
Barley
Docosahexaenoic acid
Reduced pre-grazing herbage mass
Corn
Probiotics
Increasing feeding level
Minerals and Salts
Bacteria
Increasing forage quality
Oils and fats
Lactobacillus
Decreasing grass maturity
Canola oil
Propionibacterium
Increasing corn silage maturity
Coconut oil
Yeasts
Optimizing temperature
Linseed oil
Saccharomyces
Total mixed ration feeding
Oil blends
Secondary plant compounds
Total mixed ration vs. grazing
Rumen protected fat
Essential oils
Sunflower oil
Essential oil blends
Tallow
Garlic
Oilseeds
Oregano
Canola seed
Flavonoids
Cottonseed
Phenols
Linseed
Saponins
Sunflower seed
Saponaria
Increasing protein
Tea saponin
Tannifores forages
Yucca saponin
Lespedeza
Tannins
Leucaena
Condensed tannins
Lotus
Acacia
Sainfoin
Quebracho
Urea
Hydrolysable tannins
Defaunation
Electron sinks
Fumaric acid
Nitrate
Strategies that decreased (adjusted P < 0.05) daily methane (CH4) emission (g d-1), CH4 yield (CH4 per unit of dry matter intake,
g kg-1), or CH4 conversion factor [CH4 energy (MJ) per gross energy intake (MJ), %] are presented in bold.
45
SUPPLEMENTARY FIGURES
Supplementary Fig 1. Relationship between CH4Y (CH4 yield = CH4 per unit of feed dry matter intake, g kg-1) and Ym (CH4 conversion factor =
CH4 energy (MJ) per gross energy intake (MJ) × 100, %), MJ CH4/MJ] of treatment means included in the database of this study (n = 783). Linear
regression analysis was performed using the lm function in R. Standard errors are reported in parenthesis.
46
Supplementary Fig 2. Number of publications that reported methane (CH4) emission and animal performance variables of the 425 studies that were
analyzed in the current meta-analysis. Methane emission variables included in the analysis were: Daily CH4 = daily CH4 emission (g d-1), CH4Y =
CH4 yield (CH4 per unit of feed dry matter intake, g kg-1), Ym = CH4 conversion factor (CH4 energy (MJ) per gross energy intake (MJ) × 100, %),
CH4IG = CH4 intensity for weight gain (CH4 per unit of weight gain of growing animals, g kg-1), CH4IM = CH4 intensity for milk (CH4 per unit of
milk produced, g kg-1), Intake = feed intake (dry matter intake, kg d-1), Digestibility = fiber digestibility (neutral detergent fiber digestibility, %),
Gain = weight gain (average daily gain, kg d-1), and Milk = milk yield (kg d-1).
47
a
b
Supplementary Fig. 3.
Relative treatment effects and 95% confidence intervals of (a) Daily CH4 = daily CH4 emission (g d-1); CH4Y = CH4 yield (CH4 per unit of feed dry
matter intake, g kg-1); CH4IG = CH4 emission intensity for weight gain (CH4 per unit of weight gain of growing animals, g kg-1); and CH4IM = CH4
emission intensity for milk (CH4 per unit of milk produced, g kg-1) and (b) Feed intake (dry matter intake, kg d-1); weight gain (average daily gain, kg
d-1), milk yield (kg d-1); and fiber digestibility (neutral detergent fiber digestibility, %) for animal and feed management strategies that had a
significant effect (adjusted P < 0.05) on daily CH4, CH4Y, or Ym = methane conversion factor [CH4 energy (MJ) per gross energy intake (MJ), %].
Next higher mitigation categories were included for all significant categories (adjusted P < 0.05) even if they were not significant (adjusted P ≥ 0.05)
48
Blue and red bars indicate significant desirable and undesirable effects (adjusted P < 0.05), respectively, white bars indicate lack of significant effects
(adjusted P ≥ 0.05), and no bars indicate that no data were available. The relative treatment effect of increasing feeding level on weight gain is only
partially shown; its relative treatment effect was 162% and its 95% CI was 38 to 398%.
49
a
50
b
Supplementary Fig 4. Relative treatment effects and 95% confidence intervals of (a) Daily CH4 = daily CH4 emission (g d-1); CH4Y = CH4 yield
(CH4 per unit of feed dry matter intake, g kg-1); CH4IG = CH4 emission intensity for weight gain (CH4 per unit of weight gain of growing animals, g kg-
1); and CH4IM = CH4 emission intensity for milk (CH4 per unit of milk produced, g kg-1) and (b) Feed intake = feed intake (dry matter intake, kg d-1);
weight gain (average daily gain, kg d-1), milk yield (kg d-1); and fiber digestibility (neutral detergent fiber digestibility, %) for diet formulation
strategies that had a significant effect (adjusted P < 0.05) on daily CH4, CH4Y, or Ym = methane conversion factor [CH4 energy (MJ) per gross energy
intake (MJ), %]. Next higher mitigation categories were included for all significant categories (adjusted P < 0.05) even if they were not significant
(adjusted P ≥ 0.05). Blue and red bars indicate significant desirable and undesirable effects (adjusted P < 0.05), respectively, white bars indicate lack of
significant effects (adjusted P ≥ 0.05), and no bars indicate that no data were available. Weight gain for tanniferous forage was not significant (not
shown, because it was analyzed with standardized relative difference instead of log ratio of means that was used for the remaining analyses).
51
a
52
b
Supplementary Fig 5. Relative treatment effects and 95% confidence intervals of (a) Daily CH4 = daily CH4 emission (g d-1); CH4Y
= CH4 yield (CH4 per unit of feed dry matter intake, g kg-1); CH4IG = CH4 emission intensity for weight gain (CH4 per unit of weight
gain of growing animals, g kg-1); and CH4IM = CH4 emission intensity for milk (CH4 per unit of milk produced, g kg-1) and (b) Feed
intake = feed intake (dry matter intake, kg d-1); Weight gain (average daily gain, kg d-1), Milk production (kg d-1); and Fiber
53
digestibility (neutral detergent fiber digestibility, %) for rumen manipulation strategies that had a significant effect (adjusted P < 0.05)
on daily CH4, CH4Y, or Ym = methane conversion factor [CH4 energy (MJ) per gross energy intake (MJ), %]. Next higher mitigation
categories were included for all significant categories (adjusted P < 0.05) even if they were not significant (adjusted P ≥ 0.05), and no
bars indicate that no data were available. Blue and red bars indicate significant desirable and undesirable effects (adjusted P < 0.05),
respectively, white bars indicate lack of significant effects (adjusted P ≥ 0.05), and no bars indicate that no data were available.
Weight gain for tanniferous forage was not significant (not shown, because it was analyzed with standardized relative difference
instead of log ratio of means that was used for the remaining analyses). The relative treatment effect of tannin and condensed tannin
on CH4IM is only partially shown; its relative treatment effect was for both -3.5% and its 95% CI was -15.1 to 9.5%.
... Meta-analyses have identified the dietary inclusion of chemical inhibitors of methanogenesis and the bromoformcontaining, red algae Asparagopsis spp., as the most effective strategies to decrease both total enteric CH 4 emissions per animal and enteric CH 4 emissions expressed per unit of dry matter intake (DMI), or CH 4 yield (Veneman et al., 2016;Almeida et al., 2021;Arndt et al., 2021). Although on average the decrease in enteric CH 4 yield (CH 4 produced per unit of DMI) caused by chemical inhibitors of methanogenesis was 25% (Veneman et al., 2016), 34% (Arndt et al., 2021) or 23% (Almeida et al., 2021), the antimethanogenic effects of chemical inhibitors are dosedependent (Mitsumori et al., 2012;Martinez-Fernandez et al., 2016;Dijkstra et al., 2018), and considerably greater decreases in CH 4 production e.g., >80% are possible (Table 3). ...
... Meta-analyses have identified the dietary inclusion of chemical inhibitors of methanogenesis and the bromoformcontaining, red algae Asparagopsis spp., as the most effective strategies to decrease both total enteric CH 4 emissions per animal and enteric CH 4 emissions expressed per unit of dry matter intake (DMI), or CH 4 yield (Veneman et al., 2016;Almeida et al., 2021;Arndt et al., 2021). Although on average the decrease in enteric CH 4 yield (CH 4 produced per unit of DMI) caused by chemical inhibitors of methanogenesis was 25% (Veneman et al., 2016), 34% (Arndt et al., 2021) or 23% (Almeida et al., 2021), the antimethanogenic effects of chemical inhibitors are dosedependent (Mitsumori et al., 2012;Martinez-Fernandez et al., 2016;Dijkstra et al., 2018), and considerably greater decreases in CH 4 production e.g., >80% are possible (Table 3). Similarly, the decrease in CH 4 production and yield by Asparagopsis spp. is related to its dose inclusion (Li et al., 2016;Roque et al., 2019Roque et al., , 2021Kinley et al., 2020), and considerably greater inhibition of CH 4 production than the 49% average (Almeida et al., 2021) has been reported ( Table 3). ...
Article
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Limiting global warming to 1.5°C above pre-industrial levels by 2050 requires achieving net zero emissions of greenhouse gases by 2050 and a strong decrease in methane (CH 4 ) emissions. Our aim was to connect the global need for mitigation of the emissions of greenhouse gases and enteric CH 4 from ruminant production to basic research on the biological consequences of inhibiting rumen methanogenesis in order to better design strategies for pronounced mitigation of enteric CH 4 production without negative impacts on animal productivity or economic returns. Ruminant production worldwide has the challenge of decreasing its emissions of greenhouse gases while increasing the production of meat and milk to meet consumers demand. Production intensification decreases the emissions of greenhouse gases per unit of product, and in some instances has decreased total emissions, but in other instances has resulted in increased total emissions of greenhouse gases. We propose that decreasing total emission of greenhouse gases from ruminants in the next decades while simultaneously increasing meat and milk production will require strong inhibition of rumen methanogenesis. An aggressive approach to pronounced inhibition of enteric CH 4 emissions is technically possible through the use of chemical compounds and/or bromoform-containing algae, but aspects such as safety, availability, government approval, consumer acceptance, and impacts on productivity and economic returns must be satisfactorily addressed. Feeding these additives will increase the cost of ruminant diets, which can discourage their adoption. On the other hand, inhibiting rumen methanogenesis potentially saves energy for the host animal and causes profound changes in rumen fermentation and post-absorptive metabolism. Understanding the biological consequences of methanogenesis inhibition could allow designing strategies to optimize the intervention. We conducted meta-regressions using published studies with at least one treatment with >50% inhibition of CH 4 production to elucidate the responses of key rumen metabolites and animal variables to methanogenesis inhibition, and understand possible consequences on post-absorptive metabolism. We propose possible avenues, attainable through the understanding of biological consequences of the methanogenesis inhibition intervention, to increase animal productivity or decrease feed costs when inhibiting methanogenesis.
... An increase in animal productivity would help offset the additional cost of the feed additive and improve profitability [9]. 3-Nitrooxypropanol has been evaluated in approximately 28 in vivo and 7 in vitro ruminant studies and several recent meta-analyses have examined this substantial body of information to examine overall efficacy when 3-NOP is used for enteric CH 4 mitigation [16][17][18][19][20][21]. 3-NOP could provide a feasible strategy for CH 4 mitigation if it is accepted by consumers and approved by regulatory authorities. ...
... Globally, it is estimated that 37% of enteric CH 4 emissions from ruminant livestock production is pasture-based [79], and thus a significant proportion of ruminant farming is currently excluded from the potential for mitigation using 3-NOP in its present form. However, research is ongoing to extend its application under grazing conditions [20]. This may include adding 3-NOP to pasture supplements, use of lick blocks, encapsulation, slow-release ruminal devices, and so forth. ...
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Methane (CH4) from enteric fermentation accounts for 3 to 5% of global anthropogenic greenhouse gas emissions, which contribute to climate change. Cost-effective strategies are needed to reduce feed energy losses as enteric CH4 while improving ruminant production efficiency. Mitigation strategies need to be environmentally friendly, easily adopted by producers and accepted by consumers. However, few sustainable CH4 mitigation approaches are available. Recent studies show that the chemically synthesized CH4 inhibitor 3-nitrooxypropanol is one of the most effective approaches for enteric CH4 abatement. 3-nitrooxypropanol specifically targets the methyl-coenzyme M reductase and inhibits the final catalytic step in methanogenesis in rumen archaea. Providing 3-nitrooxypropanol to dairy and beef cattle in research studies has consistently decreased enteric CH4 production by 30% on average, with reductions as high as 82% in some cases. Efficacy is positively related to 3-NOP dose and negatively affected by neutral detergent fiber concentration of the diet, with greater responses in dairy compared with beef cattle when compared at the same dose. This review collates the current literature on 3-nitrooxypropanol and examines the overall findings of meta-analyses and individual studies to provide a synthesis of science-based information on the use of 3-nitrooxypropanol for CH4 abatement. The intent is to help guide commercial adoption at the farm level in the future. There is a significant body of peer-reviewed scientific literature to indicate that 3-nitrooxypropanol is effective and safe when incorporated into total mixed rations, but further research is required to fully understand the long-term effects and the interactions with other CH4 mitigating compounds.
... Nutritional interventions to mitigate enteric CH 4 have been thoroughly investigated and discussed Arndt et al., 2021;Congio et al., 2021), and it is likely that strategies based on supplementation with plant extracts, such as essential oils (EO), may have a higher acceptance by livestock producers compared with, for example, the use of antibiotics. The main reason is that most of these plant extracts are Generally Recognized as Safe (GRAS) compounds by the Food and Drug Administration (US FDA, 2021) and could have an appeal to the consumer. ...
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Botanical extracts have a potential to modify rumi-nal fermentation while enhancing metabolism and immunity in dairy cows. The objective of this study was to investigate the effects of a combination of Capsicum oleoresin and clove essential oil (botanicals; BTC) on lactational performance, nutrient utilization, enteric methane (CH 4) emissions, and blood parameters in dairy cows. Twenty Holstein cows (12 multiparous and 8 primiparous) averaging (±SD) 77 ± 28 d in milk in the beginning of the study were used in a replicated 4 × 4 Latin square design experiment with 4 periods of 28 d each. Cows were grouped into squares based on parity, milk yield and days in milk, and assigned to 1 of 4 treatments: control (CON), 150, 300, or 600 mg/ cow per day of BTC. Cows received the same basal diet and BTC were top-dressed on the total mixed ration once daily. Dry matter intake, milk production, and milk composition were not affected by BTC supple-mentation, except for milk fat content that tended to be increased in BTC, compared with CON. Daily CH 4 emission (measured using the GreenFeed system) was linearly decreased by up to 7.5% with increasing doses of BTC. Treatment decreased CH 4 yield (kg of CH 4 ÷ kg of DMI) and tended to decrease CH 4 intensity (kg of CH 4 ÷ kg of milk or energy-corrected milk yields) by 5% in BTC, compared with CON. Supplementa-tion of BTC resulted in a quadratic decrease of serum β-hydroxybutyrate in all cows, and a linear decrease of serum insulin concentration in primiparous but not in multiparous cows. Nutrient utilization and other blood parameters (e.g., blood cells count) were not affected by BTC in the current study. The reduction of enteric CH 4 emission demonstrates a moderate mitigation effect on carbon footprint of milk by BTC supplementa-tion. These results must be further investigated and confirmed in longer-term experiments.
... Methane (CH 4 ) is a powerful short-lived climate forcer (IPCC, 2018) and decreasing its emission is crucially important for limiting global warming to 2.0°C above pre-industrial levels as defined in the Paris Agreement (UN General Assembly, 2015; Arndt et al., 2021). Successful mitigation efforts entail accurate estimation of on-farm emission . ...
Conference Paper
Methane produced from enteric fermentation in ruminants is a significant contributor to anthropogenic greenhouse gas emissions. Empirical prediction models can be useful to estimate enteric methane emissions without undertaking extensive and costly experiments. Recent meta-analyses, based primarily on data from the U.S. and the E.U. with minimal data from the Latin America region, concluded that region-specific models are more accurate in predicting enteric methane than global models. Therefore, the objectives of this study were to: (1) collate a database of individual dairy cattle enteric methane emission data from studies conducted in the Latin America region; (2) determine the key dietary and animal variables for predicting daily enteric methane production (g/day per animal) and yield (g/kg dry matter intake) and their relationships; (3) develop and cross-validate these newly developed models; and (4) compare their predictive ability with extant models, which are currently used to support national greenhouse gas inventories in the region. After outliers were removed, 610 individual dairy cattle records (46% of the original data) from 34 studies (from 2012 to 2021) carried out in 8 countries were retained in the database. Linear mixed models were developed by incrementally adding covariates. The developed methane production equation using only dry matter intake as covariate performed better than extant equations from the Intergovernmental Panel on Climate Change, with smaller root mean square prediction error (20.5 vs. 21.1%) and smaller mean (0.56 vs. 7.75%) and slope (0.64 vs. 5.43%) biases. The prediction of methane production was further improved by a combination of dry matter intake and energy corrected milk yield. In addition, methane yield was satisfactorily predicted by either simple or multiple regression equations containing feeding level or/and animal’s body weight as predictor variables. The newly developed models can be used to improve national greenhouse gas inventories in the Latin America region.
... The plan to mitigate CH 4 emission is proposed in Figure 1E and a 55% reduction in CH 4 emissions from enteric fermentation is technically feasible as follows: 1) via feed management, such as increasing forage digestibility, which could support a 9% to 17% reduction in CH 4 emissions; 2) via diet formulation, such as decreasing dietary forage-to-concentrate ratio and inclusion of oilseeds, as oil and fat could achieve a 9% to 20% reduction in CH 4 emissions; however, altering animal feed formulation may cause GHG emissions to change, which merits further investigation; and 3) via rumen manipulation by CH 4 inhibitors, alternative electron receptors, and dietary inclusion of tanniferous forages, which enable 12% to 35% reduction in CH 4 emissions. 10 Overall, China is ranked at almost the lowest level of ADF consumptionrelated GHG emissions per capita per year in the world, due to its low average ADF consumption rate, and preferential consumption of low GHG emissionrelated ADF. However, the projected increase in the consumption of ADF may pose great challenges for achieving the stringent 1.5 C global warming target and China's "carbon neutrality" pledge. ...
... The plan to mitigate CH 4 emission is proposed in Figure 1E and a 55% reduction in CH 4 emissions from enteric fermentation is technically feasible as follows: 1) via feed management, such as increasing forage digestibility, which could support a 9% to 17% reduction in CH 4 emissions; 2) via diet formulation, such as decreasing dietary forage-to-concentrate ratio and inclusion of oilseeds, as oil and fat could achieve a 9% to 20% reduction in CH 4 emissions; however, altering animal feed formulation may cause GHG emissions to change, which merits further investigation; and 3) via rumen manipulation by CH 4 inhibitors, alternative electron receptors, and dietary inclusion of tanniferous forages, which enable 12% to 35% reduction in CH 4 emissions. 10 Overall, China is ranked at almost the lowest level of ADF consumptionrelated GHG emissions per capita per year in the world, due to its low average ADF consumption rate, and preferential consumption of low GHG emissionrelated ADF. However, the projected increase in the consumption of ADF may pose great challenges for achieving the stringent 1.5 C global warming target and China's "carbon neutrality" pledge. ...
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Animal-derived food production accounts for one-third of the global anthropogenic greenhouse gas (GHG) emissions. Diet followed in China is ranked as low-carbon emitting (i.e. 0.21 t CO2-eq per capita in 2018, ranking at 145th out of 168 countries) due to the low average animal-derived food consumption rate, and preferential consumption of animal-derived foods with lower-GHG emissions (i.e. pork and eggs vs beef and milk). However, the projected increase in GHG emissions from livestock production poses great challenges for achieving China’s “Carbon Neutrality” Pledge. We propose that the livestock sector may achieve “Climate Neutrality” with net-zero warming around 2050 by implementing healthy diet and mitigation strategies to control enteric methane emissions.
... Methane (CH 4 ) is a powerful short-lived climate forcer (IPCC, 2018) and decreasing its emission is crucially important for limiting global warming to 2.0°C above pre-industrial levels as defined in the Paris Agreement (UN General Assembly, 2015; Arndt et al., 2021). Successful mitigation efforts entail accurate estimation of on-farm emission . ...
Article
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... The plan to mitigate CH 4 emission is proposed in Figure 1E and a 55% reduction in CH 4 emissions from enteric fermentation is technically feasible as follows: 1) via feed management, such as increasing forage digestibility, which could support a 9% to 17% reduction in CH 4 emissions; 2) via diet formulation, such as decreasing dietary forage-to-concentrate ratio and inclusion of oilseeds, as oil and fat could achieve a 9% to 20% reduction in CH 4 emissions; however, altering animal feed formulation may cause GHG emissions to change, which merits further investigation; and 3) via rumen manipulation by CH 4 inhibitors, alternative electron receptors, and dietary inclusion of tanniferous forages, which enable 12% to 35% reduction in CH 4 emissions. 10 Overall, China is ranked at almost the lowest level of ADF consumptionrelated GHG emissions per capita per year in the world, due to its low average ADF consumption rate, and preferential consumption of low GHG emissionrelated ADF. However, the projected increase in the consumption of ADF may pose great challenges for achieving the stringent 1.5 C global warming target and China's "carbon neutrality" pledge. ...
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The photometric properties of the uppermost lunar regolith are used in the spectroscopic study. China's Chang’E‐5 (CE‐5) mission successfully landed in the Northern Oceanus Procellarum of the Moon, carrying the scientific payload lunar mineralogical spectrometer (LMS). LMS performed full‐view scanning and obtained the reflectance spectra in various geometric configurations. The photometric properties, including the single‐scattering albedo ω and two parameters of the Henyey‐Greenstein phase function (b, c), were derived. Our modeling results showed weak backward scattering and strong forward scattering properties of the regolith at the CE‐5 landing site. Meanwhile, the asymmetry parameter (−b×c) $(-b\times c)$ indicates that CE‐5 regolith has weaker forward scattering than the Apollo lunar soil samples and the regolith at the Chang’E‐4 landing site. The derived Hapke parameters can be used for comparison with that of the returned lunar sample, supporting further studies of lunar spectroscopy, and can be the ground truth of the CE‐5 landing area.
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This report presents scenarios “with existing measures” (WEM) and “with additional measures” (WAM) concerning the agriculture and LULUCF (Land use, land-use change and forestry) sectors in Finland. The report is part of the project Carbon neutral Finland 2035 – impact assessments of climate and energy policies and measures (HIISI), funded by the Prime Minister’s Office. In the scenarios, supply and demand within the operational environment govern forestry production and agricultural land use, and thus forest carbon sink and greenhouse gas emissions from agricultural lands. In 2035, the LULUCF net sink in the WEM and WAM scenarios will be 18 and 23 Mt CO2-eq (million tonnes of carbon dioxide equivalent), respectively. Agriculture sector emissions in the WEM and WAM scenarios will be 6.2 and 5.8 Mt CO2-eq, respectively. In the WAM scenario, policy measures in agriculture cause changes in land use, farming practices, and the feeding of cattle. By 2035, this reduces cropland and grassland emissions in the LULUCF sector by 1.0 Mt CO2-eq and agriculture sector emissions by 0.4 Mt CO2-eq compared to the WEM scenario. Forest fertilization will increase the forest net sink of LULUCF sector in the WAM scenario. In addition to this and the agricultural changes, the LULUCF balance is affected by energy production and the allocation of new construction.
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In this review we describe the research which led to: (i) the identification and testing of a fermentation byproduct (Rice wine distillers" byproduct-RDB) with the capacity to reduce methane emissions from ruminants; and (ii) the development of a supplement made by fermenting polished rice (or cassava root) with yeast (Saccharomyces cerevisiae) which had similar capacity as ": RDB" to reduce methane "in vitro".We consider that both products can be described as "prebiotics" because they are derived from the yeast cell wall and when fed at low levels (4%) to a ruminant diet they: (i) improve animal health by reducing HCN toxicity from cassava-rich feeds; and (ii) increase the production of propionic acid in the rumen and indirectly improve animal performance as well as reducing missions of methane. We hypothesize that, tannins present in the leaves of cassava, combine with protein (and other soluble nutrients) making them resistant to fermentation in the rumen. This allows their escape to the intestine where the low pH disrupts the tannin-nutrient bonds and the nutrients become available for enzymic digestion and absorption. At the same time, beta-glucan and related compounds derived from the fermented yeast cell wall selectively provide energy for the growth of bacteria that produce volatile fatty acids in a process whereby they selectively compete for electrons with bacteria that produce methane.
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A grazing experiment was undertaken to assess the effects of two levels of herbage mass (HM) on herbage DM intake (DMI), fat and protein corrected milk yield (FPCM), grazing behaviour, energy expenditure (HP), and methane emissions (CH 4 ) of grazing dairy cows in spring. Treatments were a low HM (1447 kg DM/ha; LHM) or a high HM (1859 kg DM/ha; HHM). Pasture was composed mainly of cocksfoot ( Dactylis glomerata ) and lucerne ( Medicago sativa ), offered at a daily herbage allowance of 30 kg DM/cow, above 5 cm. Eight multiparous Holstein cows were used in a 2 × 2 Latin Square design in two 10-day periods. Despite the differences in pre-grazing HM between treatments, OM digestibility was not different (P = 0.28). Herbage mass did not affect DMI or FPCM. Grazing time was not different between treatments, but cows had a greater bite rate when grazing on LHM swards. However, HP did not differ between treatments. Daily methane emission (per cow), methane emission intensity (per kg FPCM) and methane yield (as percentage of gross energy intake) were not different. The lack of effect of the amount of pre-grazing HM on energy intake, confirms that the difference between HM treatments was beyond the limits that impose extra energy expenditure during grazing.
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The aim of the present research was to evaluate the effect of Pithecellobium dulce, Tagetes erecta and Cosmos bipinnatus on methane emission, milk yield and dry matter intake in dairy cattle. A 4×4 Latin square experimental design was employed, using four multiparous Holstein cows of 553±72.4kg body weight, at mid lactation and average milk yield of 17.3±3kg/day. The experiment lasted 92 days, divided into four experimental periods of 23 days each. All cows had free access to maize and alfalfa silage in a 50:50 proportion, 4kg of concentrate/day and ad libitum access to water. Treatments consisted in supplementation of 0.5kg/day of the experimental plants, with one control treatment without supplementation. Each cow received one of each treatment in turn during one of the four periods. The C. bipinnatus reduced methane production by 16% (P<0,05) in comparison with the control diet. Milk production, milk composition and dry matter intake were not affected (p>0 0.05) by the use of C. bipinnatus or any other plant species. Supplementation at low doses of C. bipinnatus showed a reduction in ruminal methane production in dairy cows.
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The relationship between DM intake ( DMI ) and enteric methane emission is well established in ruminant animals but may depend on measurement technique (e.g. spot v . continuous gas sampling) and rumen environment (e.g. use of fermentation modifiers). A previous meta-analysis has shown a poor overall (i.e. 24 h) relationship of DMI with enteric methane emission in lactating dairy cows when measured using the GreenFeed system ( GF ; Symposium review: uncertainties in enteric methane inventories, measurement techniques, and prediction models. Journal of Dairy Science 101, 6655 to 6674). Therefore, we examined this relationship in a 15-week experiment with lactating dairy cows receiving a control diet or a diet containing the investigational product 3-nitrooxypropanol ( 3-NOP ), an enteric methane inhibitor, applied at 60 mg/kg feed DM. Daily methane emission, measured using GF, and DMI were clustered into 12 feed-intake timeslots of 2 h each. Methane emission and DMI were the lowest 2 h before feeding and the highest within 6 h after feed provision. The overall (24 h) relationship between methane emission and DMI was poor ( R ² = 0.01). The relationship for the control (but not 3-NOP) cows was improved ( R ² = 0.31; P < 0.001) when DMI was allocated to timeslots and was strongest ( R ² = 0.51; P < 0.001) 8 to 10 h after feed provision. Analysis of the 3-NOP emission data showed marked differences in the mitigation effect over time. There was a lack of effect in the 2-h timeslot before feeding, the mitigation effect was highest (45%) immediately after feed provision, persisted at around 32% to 39% within 10 h after feed provision, and decreased to 13%, 4 h before feeding. These trends were clearly related to DMI (i.e. 3-NOP intake) by the cows. The current analysis showed that the relationship of enteric methane emission, as measured using GF, and DMI in dairy cows depends on the time of measurement relative to time of feeding. The implication of this finding is that a sufficient number of observations, covering the entire 24-h feeding cycle, have to be collected to have representative emission estimates using the GF system. This analysis also revealed that the methane mitigation effect of 3-NOP is highest immediately after feed provision and lowest before feeding.
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The red macroalgae (seaweed) Asparagopsis spp. has shown to reduce ruminant enteric methane (CH4) production up to 99% in vitro. The objective of this study was to determine the effect of Asparagopsis taxiformis on CH4 production (g/day per animal), CH4 yield (g CH4/kg dry matter intake (DMI)), average daily gain (ADG), feed conversion efficiency (FCE), and carcass and meat quality in growing beef steers. Twenty-one Angus-Hereford beef steers were randomly allocated to one of three treatment groups: 0% (Control), 0.25% (Low Dose; LD), and 0.5% (High Dose; HD) A. taxiformis inclusion based on organic matter intake. Steers were fed 3 diets: high, medium, and low forage total mixed ration (TMR) representing typical life-stage diets of growing beef steers. The LD and HD treatments over 147 days reduced enteric CH4 yield 45 and 68%, respectively; however, there was an interaction between TMR type and the magnitude of CH4 yield reduction. Supplementing the low forage TMR reduced CH4 yield 69.8% (P <0.001) for LD and 80% (P <0.001) for HD treatment. Hydrogen (H2) yield (g H2/DMI) increased significantly (P<0.001) 336 and 590% compared to Control for the LD and HD treatments, respectively. No differences were found in carbon dioxide (CO2) yield (g CO2/DMI), ADG, carcass quality, strip loin proximate analysis and shear force, or consumer taste preferences. DMI tended (P = 0.08) to decrease 8% in steers in LD treatment but significantly (P = 0.002) reduced 14% in steers in HD treatment. Conversely, FCE tended to increase 7% in steers in LD treatment (P = 0.06) and increased 14% in steers in HD (P < 0.01) treatment compared to Control. The persistent reduction of CH4 by A. taxiformis supplementation suggests that this is a viable feed additive to significantly decrease the carbon footprint of ruminant livestock and potentially increase production efficiency.
Article
Asparagopsis taxiformis (AT) is a source of multiple halogenated compounds and, in a limited number of studies, has been shown to decrease enteric CH4 emission in vitro and in vivo. Similarly, oregano has been suggested as a potential CH4 mitigating agent. This study consisted of 2 in vitro and 2 in vivo experiments. Experiment (Exp.) 1 was aimed at establishing the effect of AT on CH4 emission in vitro. Two experiments (Exp. 2 and 3) with lactating dairy cows were conducted to determine the antimethanogenic effect of AT and oregano (Exp. 3) in vivo. Another experiment (Exp. 4) was designed to investigate stability of bromoform (CHBr3) in AT over time. In Exp. 3, 20 Holstein cows were used in a replicated 4 × 4 Latin square design with four 28-d periods. Treatments were basal diet (control) or basal diet supplemented with (dry matter basis) 0.25% AT (LowAT), 0.50% AT (HighAT), or 1.77% oregano (Origanum vulgare L.) leaves. Enteric gas emissions were measured using the GreenFeed system (C-Lock Inc., Rapid City, SD), and rumen samples were collected for fermentation analysis using the ororuminal technique. In Exp.1 (in vitro), relative to the control, AT (at 1% dry matter basis, inclusion rate) decreased CH4 yield by 98%. In Exp. 3, HighAT decreased average daily CH4 emission and CH4 yield by 65% and 55%, respectively, in experimental periods 1 and 2, but had no effect in periods 3 and 4. The differential response to AT among experimental periods was likely a result of a decrease in CHBr3 concentration in AT over time, as observed in Exp. 4 (up to 84% decrease in 4 mo of storage). In Exp. 3, H2 emission was increased by AT and, as expected, the proportion of acetate in the total volatile fatty acids in the rumen was decreased and those of propionate and butyrate were increased by HighAT compared with the control. Compared with the control, HighAT decreased dry matter intake, milk yield, and energy-corrected milk yield in Exp. 3. Milk composition was not affected by treatment, except lactose percentage and yield were decreased by HighAT. Concentrations of iodine and bromide in milk were increased by HighAT compared with the control. Milk CHBr3 concentration and its organoleptic characteristics were not different between control and HighAT. Oregano had no effect on CH4 emission or lactational performance of the cows in Exp. 3. Overall, AT included at 0.50% in the ration of dairy cows can have a large mitigation effect on enteric CH4 emission, but dry matter intake and milk production may also decrease. There was a marked decrease in the CH4 mitigation potential of AT in the second half of Exp. 3, likely resulting from CHBr3 decay over time.
Article
Thought for food To have any hope of meeting the central goal of the Paris Agreement, which is to limit global warming to 2°C or less, our carbon emissions must be reduced considerably, including those coming from agriculture. Clark et al. show that even if fossil fuel emissions were eliminated immediately, emissions from the global food system alone would make it impossible to limit warming to 1.5°C and difficult even to realize the 2°C target. Thus, major changes in how food is produced are needed if we want to meet the goals of the Paris Agreement. Science , this issue p. 705
Article
Supplementing a diet with nitrate is regarded as an effective and promising methane (CH4) mitigation strategy by competing with methanogens for available hydrogen through its reduction of ammonia in the rumen. Studies have shown major reductions in CH4 emissions with nitrate supplementation, but with large variation in response. The objective of this study was to quantitatively investigate the effect of dietary nitrate on enteric CH4 production and yield and evaluate the variables with high potential to explain the heterogeneity of between-study variability using meta-analytical models. A data set containing 56 treatments from 24 studies was developed to conduct a meta-analysis. Dry matter (DM) intake, nitrate dose (g/kg of DM), animal body weight, roughage proportion of diet, dietary crude protein and neutral detergent fiber content, CH4 measurement technique, and type of cattle (beef or dairy) were considered as explanatory variables. Average DM intake and CH4 production for dairy cows (16.2 ± 2.93 kg/d; 311 ± 58.8 g/d) were much higher than for beef cattle (8.1 ± 1.57 kg/d; 146 ± 50.9 g/d). Therefore, a relative mean difference was calculated and used to conduct random-effect and mixed-effect model analysis to eliminate the large variations between types of animal due to intake. The final mixed-effect model for CH4 production (g of CH4/d) had 3 explanatory variables and included nitrate dose, type of cattle, and DM intake. The final mixed-effect model for CH4 yield (g of CH4/kg of DM intake) had 2 explanatory variables and included nitrate dose and type of cattle. Nitrate effect sizes on CH4 production (dairy: −20.4 ± 1.89%; beef: −10.1 ± 1.52%) and yield (dairy: −15.5 ± 1.15%; beef: −8.95 ± 1.764%) were significantly different between the 2 types of cattle. When data from slow-release nitrate sources were removed from the analysis, there was no significant difference in type of cattle anymore for CH4 production and yield. Nitrate dose enhanced the mitigating effect of nitrate on CH4 production and yield by 0.911 ± 0.1407% and 0.728 ± 0.2034%, respectively, for every 1 g/kg of DM increase from its mean dietary inclusion (16.7 g/kg of DM). An increase of 1 kg of DM/d in DM intake from its mean dietary intake (11.1 kg of DM/d) decreased the effect of nitrate on CH4 production by 0.691 ± 0.2944%. Overall, this meta-analysis demonstrated that nitrate supplementation reduces CH4 production and yield in a dose-dependent manner, and that elevated DM intake decreases the effect of nitrate supplementation on CH4 production. Furthermore, the stronger antimethanogenic effect on CH4 production and yield in dairy cows than in beef steers could be related to use of slow-release nitrate in beef cattle.
Article
Breeding cows for low CH4 emissions requires that the trait is variable and that it can be recorded with low cost from an adequate number of individuals and with high precision, but not necessarily with high accuracy if the trait is measured with high repeatability. The CH4:CO2 ratio in expired breath is a trait often used as a tracer with the production of CO2 predicted from body weight (BW), energy-corrected milk yield, and days of pregnancy. This approach assumes that efficiency of energy utilization for maintenance and production is constant. Data (307 cow-period observations) from 2 locations using the same setup for measuring CH4 and CO2 in respiration chambers were compiled, and observed production of CH4 and CO2 was compared with the equivalent predicted production using 2 different approaches. Carbon dioxide production was predicted using a previously reported model based on metabolic BW and energy corrected milk production and a currently developed model based on energy requirements and the relationship between observed CO2 and heat production (models 1 and 2, respectively). Animals used were categorized (low, medium, and high efficiency) according to (1) residual feed intake and (2) residual milk production. Model 1 underestimated CH4 production by 15%, whereas model 2 overestimated CH4 by 1.4% for the whole database. Model 1 underestimated CO2 production by 2.8 and 0.9 kg/d for low- and high-efficiency cows, respectively, whereas model 2 underestimated CO2 production by 0.9 kg/d for low-efficient animals but overestimated it by 1.2 kg/d for high-efficiency cows. Efficient cows produce less heat, and consequently CO2, per unit of metabolic body weight and energy-corrected milk than inefficient cows, challenging the use of CO2 as a tracer gas. Because of biased estimates of CO2 production, the models overestimated CH4 production of high-efficiency cows by, on average, 17% relative to low-efficiency cows, respectively. Selecting low CH4-emitting cows using a CO2 tracer method can therefore favor inefficient cows over efficient cows.