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Agricultural and Biological Sciences » "Livestock Science", book edited by Selim Sekkin, ISBN 978-953-51-2864-9, Print ISBN 978-953-51-2863-2, Published: January 11, 2017 under CC BY 3.0 license. © The Author(s).

Chapter 4

Livestock Methane Emission: Microbial Ecology and Mitigation Strategies

By Marleny Garcia Lozano, Peña Garcia Yadira, Karen Abigail Avendaño Arellano, López Ortiz Carlos E. and Nagamani Balagurusamy
DOI: 10.5772/65859

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Overview

Ruminant digestion process.
Note: Gastrointestinal tract of ruminants and main biochemical processes occurring in it.
Figure 1. Ruminant digestion process. Note: Gastrointestinal tract of ruminants and main biochemical processes occurring in it.
Mitigation strategies on methane emission by rumen microbiome manipulation through change in diets.
Note: The main pathways and products formed when high fiber diet is used are represented in green color. The effect of high starch diets, which enhances propionate production due to shifting of hydrogen sinks, is presented in orange color. Dietary supplements and their main targets in order to reduce methane production are indicated in blue color.
Figure 2. Mitigation strategies on methane emission by rumen microbiome manipulation through change in diets. Note: The main pathways and products formed when high fiber diet is used are represented in green color. The effect of high starch diets, which enhances propionate production due to shifting of hydrogen sinks, is presented in orange color. Dietary supplements and their main targets in order to reduce methane production are indicated in blue color.

Livestock Methane Emission: Microbial Ecology and Mitigation Strategies

Marleny Garcia Lozano1, Yadira Peña Garcia1, Karen Abigail Avendaño Arellano1, Carlos E. López Ortiz1 and Nagamani Balagurusamy1
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Abstract

Rumen microbiome plays a critical role in the development and nutrition of the host, and any alteration in the rumen microbiome has an important effect on the animal. Rumen microbial ecology is always dynamic in response to the diets and physiological conditions of the host. Ruminal microorganisms are mainly anaerobic and provide around 75% of the energy needed by the animal. The importance of microbial diversity in rumen has gained attention not only due to its significance on the productivity of the host, but also due to the emission of greenhouse gases (GHGs) and their environmental impact. Livestock is one of the most important sources of GHGs from agriculture, contributing more than 25% of global GHGs emissions. However, the variations in livestock emission in different regions of the world could be attributed to the changes in diversity and abundance of rumen microbial communities, which vary according to the type and age of animal, type of feeds, feeding strategies, climate, etc. This chapter deals on rumen microbial ecology, the role of microorganisms in enteric fermentation and the different mitigation strategies based on manipulation of rumen microbial diversity to reduce the methane emissions from livestock.

Keywords: methane, rumen, enteric fermentation, rumen ecology, mitigation strategies

1. Introduction

Global warming has been attributed to the increment of atmospheric concentration of greenhouse gases (GHGs). Since 1750, concentrations of CO2, CH4 and N2O had increased by 40, 150 and 20%, respectively, until 2014, and the rate of increment of GHG per year from 2000 to 2010 was approximately 2.2% [1]. Of various anthropogenic activities contributing to global warming, agriculture is an important source. This sector is responsible for 18% of the total anthropogenic GHG emissions annually [2]. Livestock represents the most important cause of GHG from agriculture contributing approximately to 80% of these emissions [3] and more than 25% of global GHG emissions [4].

Herrero et al. [5] estimated the total emissions from livestock were in the range of 5.6 – 7.5 GtCO2–eq/year (5.6 to 7.5 × 1012 kg CO2–eq) between 1995 and 2005. They observed that the main sources were enteric CH4 (~32.2%), N2O emissions associated with feed production (~27.45%) and land use for animal feed and pasture (~24.42%). Havlík et al. [6] opined that ruminants represent more than 80% livestock emissions; particularly, beef and dairy sector contribute to about 60% [7]. Emissions from enteric fermentation contribute to 8% of total CH4 emissions and are estimated to increase to 30% between 2000 and 2020 [8]. Enteric fermentation is the normal process of feed digestion in ruminants and is mediated by the microbial activity in the rumen and in the large intestines. Significant amount of methane is produced by methanogens residing within the rumen (87%) [9], which is released principally through eructation, approximately 10–15% is emitted by normal respiration and via flatus [10].

The continued growth of human population and consequent demand for food are potential drivers of GHG emissions. International climate negotiators have been focused to reduce GHG emissions by the improvement of engineering processes, energy efficiency and investments on alternative energy generation technologies. However, the abatement of ruminant GHG emissions has not received adequate attention by the United Nations Framework Convention on Climate Change [11]. Even so, several research groups have been working to develop strategies to optimize ruminal functions in order to achieve the desired levels of production by enhancing feed conversion efficiency and simultaneously reducing methane emissions by manipulating the rumen microorganisms. It is essential to have a detailed knowledge of ruminal microbiome, their interactions among themselves and with the host to achieve these objectives, and to identify the new approaches for mitigation of GHGs emissions [12].

2. Livestock GHG emissions

Livestock emissions depend considerably on some of the environmental characteristics such as the mean annual temperature, geographic location and the economic level of the country. It has been observed that in developing and emerging countries, the dietary habits increase meat consumption contributing to these emissions [4, 13], nevertheless developed countries have a greater proportion of intensive animal production, which results in higher emissions of CH4, which is estimated to be 150.7 g/cow/day by cattle [4]. Additionally, the size and productivity of animals affect their feed intake and enteric CH4 emissions [14], which can vary by animal type, growth stage and composition of diet [15, 16]. Castelán-Ortega et al. [17] reported that the average CH4 emissions by individual dairy cattle are higher in the tropics than in temperate regions, 319.1 and 283 g/day, respectively. This could be attributed to the elevated proportion of cellulose in tropical forages, which is reported to produce three times more CH4 than hemicellulose.

The estimation of livestock emissions differs considerably between studies as different models are employed for their estimation. Some authors use their own models, but most of the authors follow the guidelines of IPCC [18]. However, the differences on estimations still continue. Tier I utilizes default global or regional emission factors. Tier II utilizes estimated regional or local emission factors and is used in some enteric fermentation studies, nevertheless Tier III is the most reliable model for enteric CH4 emission and has several advantages compared to Tier II, because it represents mechanisms of enteric fermentation in more detail and can be expected to describe more of the variations caused due to nutritional and animal factors [8, 19].

Enteric fermentation in ruminants and manure management emissions contributes directly to around 9% of total anthropogenic emissions. In 1990, enteric methane global emissions were 84 Tg/year CO2-eq (84 × 109 kg CO2-eq), which increased to 92 Tg/year CO2-eq in 2005. It is reported that the main sources of global enteric CH4 emissions are Asia (33%), followed by Latin America (23.9%), Africa (14.5%), Western Europe (8.3%) and North America (7.1%) [14]. Beef trades also have a significant impact on GHG emissions. Emissions from beef trade represented 2% of total emissions traded internationally in 2010 and increased by 19% during the period between 1990 and 2010. The dominant global fluxes in 2010 were the exportation of emissions embodied in meat from Brazil and Argentina to Russia (2.8 and 1.4 Mt CO2-eq (2.8 and 1.4 × 109 kg CO2-eq), respectively), emissions embodied in US imports of meat from Canada were the same that emissions embodied in US exports to Mexico of 1.2 Mt CO2-eq. Australian meat exported to South Korea also embodied substantial emissions of 1.0 Mt CO2-eq. In European countries, meat exported from France to Italy and France to Greece embodied 1.4 and 1.2 Mt CO2-eq emissions, respectively. Also Italian meat imported from Poland, Germany and Netherlands embodied 0.7, 0.6 and 0.7 Mt CO2-eq emissions, while Chinese emissions embodied in beef exported were small in comparison with the other countries. Although emissions due to import of meat are considered insignificant, it is important to consider all livestock sectors that contribute to emissions [13].

With respect to the Mexico, total CH4 emissions in 2006 were 8954.10 Gg, and agriculture sector was the highest contributor with significant input due to enteric fermentation and manure management [16]. Earlier, Rendón-Huerta et al. [18] has also reported that enteric CH4 emissions are the major source of GHG emissions in Mexican livestock production systems. They calculated the GHG emissions from dairy cattle in Mexico for a period of time of 30 years using a Tier II of IPCC and reported that emissions of CH4, N2O and CO2-eq during 1970 to 2010 increased from 144 to 270, 0.349 to 0.713 and 3704 to 6962 Mt/year, respectively. They observed that methane emissions per cow increased by 11%, while per liter of milk decreased by 30%. In the past 40 years, total N2O emission increased by 104%, but N2O/cow emissions increased only by 22% in the same period and decreased by 25% per liter of milk. The reduction in GHG emissions per liter of milk means an increase in the efficiency of production systems resulting in an augmentation of milk production per cow and consequentially diminishing the emissions [18]. Hernández-De Lira et al. [16] based on animal census data from 2012, reported that the methane emissions by enteric fermentation in Mexico were 1926.08 Gg CH4, of which beef cattle produced 1651.8 Gg CH4; while dairy cows generated only 172.70 Gg CH4.

Emissions by manure management, mostly CH4 and N2O, are produced during the manure decomposition carried out by anaerobic microbial activities. These emissions depend on specific manure composition and quantity produced which, in turn is dependent on other factors as animal type, breed, weight, diet and climate conditions. Although CH4 emissions from enteric fermentation are higher than those from manure [13, 16], manures also contribute to N2O emissions due to volatile nitrogen losses, principally in form of ammonia (NH3) and NOx [13]. They have reported that CH4 and N2O emissions from manure would increase by 20 and 29%, respectively, from 2000 to 2020.

Asia, particularly China, Western Europe and North America are the regions with the highest GHG emissions from manure management [14]. According to EPA [20], global GHG emissions from manure management were 446 million tonnes of CO2-eq, of which the share of CH4 and N2O was 53 and 47%, respectively, while FAO [3] estimated global GHG emissions from manure management were 368 million tonnes of CO2-eq. In case of Mexico, CH4 emission from manure was 62.24 Gg CH4, where beef cattle and dairy cow emitted with 29.49 and 2.42 Gg CH4, respectively [16]. Similarly, FAO [3] reported that Asia, Central and South America, Sub-Saharan Africa, Western Europe, North America, Eastern Europe and the Commonwealth of Independent States were the regions with the highest emissions of N2O due to manure [14].

3. Rumen environment

Ruminants are herbivorous mammals considered as latecomers in evolution. Their forestomach is a very complex environment, which allows them to convert plant tissues into nutritious and useful products. The digestive tract of ruminants is formed by various compartments such as reticulum, rumen, omasum, abomasum, small intestine, cecum, colon and rectum [21]. The ruminant stomach is composed by three pregastric fermentation chambers (rumen, reticulum and omasum) [22] ( Figure 1 ). Environmental conditions such as temperature (38–42°C), redox potential (250 to 450 mV), pH (5.5–7) controlled by buffer in saliva and osmolarity (260–340 mOsm) [23] provide the ideal conditions for the digestion of plant material by microorganisms. Fibrous components are hydrolyzed and fermented by the interactions among different microbial communities inhabiting the rumen, producing mainly acetate, propionate and butyrate, CO2, H2 and CH4. VFAs are the most important source of energy for the animal (75% of the total amount of the digested energy) [24]. Moreover, microbial cell biomass is the major source of protein and amino acids [25]. Microbial population also synthetizes vitamins B and K and employs detoxification mechanisms for phytotoxins and mycotoxins [26].

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Figure 1.

Ruminant digestion process. Note: Gastrointestinal tract of ruminants and main biochemical processes occurring in it.

Microbial ruminant ecosystem is composed by a high microbial population density, predominantly obligate anaerobic microorganisms. Bacteria are the most abundant microorganisms and more than 50% of the cell mass in the rumen are comprised of at least 50 bacterial genera (1010 –1011 ml-1), followed by 25 genera of ciliate protozoa (104 –106 ml-1), six genera of fungi (103–106 ml1), methanogenic archaea (107–1010 ml1) and bacteriophages (108–109 ml1) [2729], nevertheless only 10% of these microbiome have been identified and described [30]. The interactions of these microorganisms are widely different, namely mutualism, commensalism, syntrophy, competition and depredation [31, 32].

Hydrolysis of plant polysaccharide material is the first step in the enteric fermentation process, and 80% of plant cell material degradation is carried out by bacteria and fungi, and the rest 20% is by protozoa [33]. In the second stage, monomers are fermented to VFAs, branched chain VFAs, organic acids (lactate), alcohols, CO2 and H2. VFAs are absorbed by the rumen and omasal walls of the host animal for its nutrition [10]. Though several parameters such as rumen fluid, volume, pH and VFAs, concentration can disturb this absorption [34]. Free acids can be oxidized by obligate hydrogen producing bacteria to acetate, albeit this reaction is thermodynamically non-favorable, and hence are carried out only in synthropic association with hydrogen consuming bacteria or archaea, which diminish the partial pressure of H2. When the conditions are not favorable, VFAs are accumulated, decreasing the pH and inhibiting rumen microbiome [35, 36]. NH3 is produced due to proteolysis and can be used by microorganisms to build their own proteins. The excess of NH3 is absorbed by the rumen wall and transported by the animal blood [37]. The digested proteins, lipids and the carbohydrate constituents of microbial cells are exploited in the small intestine for the maintenance of the animal and the production of meat and milk. During enteric fermentation, a large quantity of CO2 is produced due to diverse biochemical processes. A part of this CO2 produced is released through eructation or normal respiration, and other part is reduced with H2 to CH4 by hydrogenotrophic methanogens. Methane produced is primarily released through eructation and approximately 10–15% is emitted by normal respiration and via flatus [10]. CH4production can be accomplished by the reduction of acetate and methyl-containing C1 compounds, nonetheless these pathways are not common in the rumen [38]. About 2–12% of gross energy intake (GEI) produced in the rumen by fermentation is converted to methane, which apart from leading to the loss of the feed energy, results in the emission and consequently, global warming [39].

4. Microbial diversity and abundance in rumen

As explained above, microorganisms present in gastrointestinal tracts (GIT) of ruminants and their relationship yield several benefits to the host. The composition of microbiome in GIT varies according to several conditions. Microbial populations can be affected by factors such as type and race of animal, age of the host, diets, feeds, farming practicing and geographical regions [40].

The microbial diversity presents in ruminant’s changes across different points of the GIT. Mao et al. [41] studied the microbial population of 10 distinct sites of the GIT in dairy cattle and observed that the microbial diversity differed for the analyzed points. They reported 21 different phyla belonged to Firmicutes (64.81%), Bacteroidetes (15.06%) and Proteobacteria (13.29%). At genus level, the most abundant genera in cattle GIT included Prevotella, Treponema, Succiniclasticum, Ruminococcus, Acetitomaculum, Mogibacterium, Butyrivibrio and Acinetobacter as well as many different unclassified genera, among which Prevotella, unclassified Ruminococcaceae, unclassified Rikenellaceae, unclassified Christensenellaceae and unclassified Bacteriodales were predominant.

A study carried out by Henderson et al. [42] determined the rumen microbiology of 32 species or subspecies of animals from 35 different countries of seven world regions and evaluated the differences among them. Seven bacterial groups comprised around 67.1% of the total bacterial sequenced, they corresponded to Prevotella, Butyrivibrio and Ruminococcus, as well as unclassified Lachnospiraceae, Ruminococcaceae, Bacteroidales and Clostridiales, but were not present in the same proportions in all animal species tested. The abundance of archaea worldwide was similar in all the sampled analyzed, and all belonged to methanogens and corresponded to Methanobrevibacter gottschalkii and M. ruminantium. Methanosphaera sp. and two Methanomassiliicoccaceae-affiliated groups, contributing to 89.2% of total archaeal community in rumen. Even in the same region, the age of the animal is other important factor that contributed to considerable differences in microbial diversity. It has been demonstrated that the ruminal microbiota of young dairy cattle is more heterogeneous than microbial community of those cows reaching maturity (2 years). In general, microbial communities in the rumen of dairy cows have been dominated by bacteria (>90%), followed by eukarya (2–8%) and a small abundance of archaea (1.0%). Similarly, a metagenomic study of the rumen microbiome in Holstein dairy cows reported 26 bacterial phyla belonging to Bacteroidetes (61–80%), followed by Firmicutes (12–23%), Proteobacteria (3–10%), Spirochaeta, Fibrobacteres and Actinobacteria (up to 2%). Again, they reported that Prevotella from Bacteroidetes was the most abundant genus (>50%), followed by Bacteroides (10.91%) and Parabacteroides (1.73%). In the case of Firmicutes, the predominant genera were Abiotrophia, Acetivibrio and Acetohalobium. In the archaeal community, the genera Methanobrevibacter, being the predominant genera, and accounted 0.5% of the total microbial abundance [43].

Earlier, Kim et al. [44] analyzed the diversity of bacteria and archaea based on 16S ribosomal RNA (rRNA) and reported 13,478 bacterial and 3516 archaeal sequences, which correspond to 7000 and 1500 species of bacteria and archaea, respectively. Among nineteen phyla of bacterial domain, the most abundant were Firmicutes (57.9%), Bacteroidetes (26.7%) and Proteobacteria (6.9%). Within Firmicutes, the most abundant class was Clostridia (>90%), and the rest belonged to Bacilli, Erysipelotrichi and unclassified Firmicutes. In the Clostridia class, the predominant genera were Buryrivibrio, Acetivibrio, Ruminococcus, Succiniclasticum, Pseudobutyrivibrio and Mogibacterium. In the Bacteroidetes phylum, the predominant class was Bacteroidia, and Prevotella represented the most abundant genera. All the five classes of Proteobacteria were represented in the rumen bacterial sequences. More than 99% of the archaeal sequences correspond to the phylum Euryarchaeota, followed by 11 sequences of the phylum Crenarchaeota. About 94% of all archaeal sequences were assigned to the classes Methanobacteria, Methanomicrobia, Thermoplasmata and Methanopyri, all of them within phylum Euryarchaeota. However, this microbial abundance in rumen can be considerably different between the extremely high and low methane emitters. While archaea are 2.49 times more, bacteria are less (0.98×) in high emitters. In addition, Euryarcheota and Crenarcheota recorded an increase in high emitters (2.48× and 3.00×, respectively), and at genus level, Methanobrevibacter and Methanosphaera have been found more abundant (2.44× and 2.54×, respectively). In case of bacterial domain, there were no significant differences between Firmicutes and Bacteroides between high and low emitters, but Proteobacteria was 0.24 times less in high emitters. At genus level, Desulfovibrio was two times more in high emitters than low emitters. However, a higher abundance of Succinovibrionaceae was recorded in low emitters along with a change in acetate and hydrogen concentration profile, resulting in a low methanogenesis [45]. These microbial dynamics in animals of different types and from different regions clearly demonstrate that it is possible to develop strategies to mitigate livestock methane emission through microbial manipulation strategies. Various studies [46, 47] have suggested that it is possible to adapt the rumen microorganisms by manipulating the feeding management in the young animal, which have been found to persist in their later life. These results suggested that the methane emissions can be decreased considerably by manipulation of rumen microbiome through feed alterations.

As mentioned earlier, the composition of population in rumen is affected by the age and diet of the animal. Li et al. [47] evaluated the rumen microbiota of pre-ruminant calves of 14- and 42-day-old calves fed milk replacers based on 454-pyrosequencing of 16S rDNA and reported a total of 170 bacterial genera in the developing rumen of 14-day-old calves. They, further demonstrated that microbiota changed according to their dietary modifications and physiological changes in the host. Moreover, the transition from 14 to 42 days had a significant impact on the ruminal microbial composition. The most abundant phylum, Bacteroidetes, increased significantly his abundance from 45.7 (14 days) to 74.8% (42 days), the phylum Synergistetes also increased, while the abundance of Firmicutes, Proteobacteria and Fusobacteria decreased during this time. The results of these two age groups are different from those based on the rumen of 12-month-old animal, where the most abundant phyla were Bacteroidetes(52%), Firmicutes (42.7%), Spirochaetes (2.3%) and Fibrobacteres (1.9%). This study clearly demonstrated that the changes in feed affect and change the dynamics of ruminal microbiome. Petri et al. [48] studied the impact of diet and its impact of an acidotic challenge on the composition of six different bacterial targets from heifers fed forage, mixed forage, high grain, post-acidic challenge (4 and 12 h) and recovery. They observed that all of the bacterial target groups were affected by dietary treatment, with exception of S. bovis, Raminococcus spp. and Fibrobacter succinogenes represented a large percentage of the bacterial population present in the mixed forage diet. Prevotella corresponds to the most abundant genera in the acidotic challenge, but the lowest in the animal fed forage. Megasphaera elsdenii was present in abundance in the sample of 12 h after acidotic challenge, but its abundance decreased during recovery, while at the same time S. ruminantium increased in proportion. Both S. ruminantium and M. elsdenii accounted the smallest proportion of the bacterial population in heifers fed forages.

5. Methane mitigation strategies

The necessity to implement abatement strategies for enteric GHG emissions has been expanded in conjunction with the increase in the population and food demand. There are two concerns over methane emissions by livestock ruminants. First, the release of methane is considered a loss of energy for the animal, resulting in a decrease in animal productivity between 2 and 12%. Second, the calorific potential of methane released has a negative impact on climate change. There are several publications on strategies to reduce methane production [4952]. The main target of these strategies is on methanogenic archaea by decreasing their substrate availability either directly or indirectly. Overall, abatement strategies include mechanisms such as modifications in dietary composition, and/or by supplementation of diet with chemical inhibitors, lipids or plant compounds, some of these strategies are shown in Figure 2 .

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Figure 2.

Mitigation strategies on methane emission by rumen microbiome manipulation through change in diets. Note: The main pathways and products formed when high fiber diet is used are represented in green color. The effect of high starch diets, which enhances propionate production due to shifting of hydrogen sinks, is presented in orange color. Dietary supplements and their main targets in order to reduce methane production are indicated in blue color.

5.1. Dietary composition

The quantity of enteric methane production is directly related to the quantity and quality of the feed consumed by the animal. The loss of GEI was augmented with an increase in high feed quantity. Animals with a low feed efficiency increase environmental impact due to the loss of GEI in form of methane.

The most common feeding mechanisms for the ruminants are based on pasture (grazing) and harvested forages. Hay and silage are the most common cattle forages. Hay has been recognized as superior feed than silage, but in cold and wet weather, silage is most used due to its major productivity. Silages for ruminants in temperate areas are usually based on cereals and legumes such as grass, maize, lucerne and red clover, which provide carbohydrate, protein and lipid sources for the animal [53]. It has been extensively reviewed that the replacement of ruminant forage diets with high grain diets can reduce methane production [9, 27, 54, 55]. Fermentation of cereal grains with high starch content increased the voluntary intake and reduced the residence time in the rumen, promoting post-ruminal digestion. Starch also enhanced propionate production, which depleted H+, and thereby decreased its availability for hydrogenotrophic methanogens. Moreover, propionate production decreased the pH, causing an inhibitory effect on methanogens and protozoa [56]. The loss of GEI with grain-based diets is commonly 4%, while it is 6.5% or more in forage-based diets.

Lettat et al. [57] reported that starchy diets, apart from increasing the propionate concentration, decreased the concentrations of acetate and butyrate and consequently methane production (-14%). Diversity and richness of bacterial community were reduced with increase in the starch content of the diet, however, the total bacterial population, Prevotella spp. and M. elsdenii were favored. The bacterial group Prevotella has been identified as amylolytic and propionate producer and the dominant within the rumen [58, 59], while M. elsdenni is a well-known lactate-utilizing and propionate-producing bacteria. CH4 reduction has been linked to the decrease in protozoan populations since protozoa are known as hydrogen producers and are in symbiotic relationship with methanogens. Hence, with a decrease in protozoan population, there is a decrease in the hydrogen transfer between them and methanogens, and this decreased the methane production. However, metabolic activity of archaea and methanogenic population increased when methane production decayed, demonstrating the cDNA-qPCR method to estimate archaeal growth and activity is unreliable to reflect changes in ruminal methanogenesis. However, there should be sufficient care before adopting this as a wholescale strategy. It has reported that changes in dietary composition not only can affect microbial diversity but also can generate animal disorders, producing a negative effect on the host. Saleem et al. [60] reported that high grain diets increased the concentrations of several toxic compounds such as putrescine, methylamines, ethanolamine and VFAs in the rumen fluid. VFAs accumulation can decrease the pH lower than 5.5 and produce subacute ruminal acidosis, which is a common and disturbing problem for farmers [61]. High grain diets have been commonly observed in favor of amylolytic microorganisms and against fibrolytic microorganisms. Petri et al. [48] reported that rumen of Angus heifers fed with high grains diet recorded a higher abundance of Prevotella spp., S. ruminanitum known also as amylolytic bacteria, and M. elsdenii. Whereas, a higher abundance of the fibrolytic bacteria Ruminococcus spp. and F. succionogenes, and the lactate-producing S. bovis was observed with forage diet. Kittelmann et al. [62] observed a positive correlation between the occurrence of methanogens and fibrolytic bacteria. Methanobrevibacter ruminanitum is found to be correlated with the family Fibrobactereacea and M. gottschalkii with the family Ruminococcaceae. Ruminococcus spp. is known to produce large amounts of H2, while Fibrobacter spp. produces formate, which is substrates for methanogens. Therefore, the abundance of fibrolytic bacteria could be related with methanogenic communities and consequently with methane production.

5.2. Dietary supplementation

5.2.1. Chemical inhibitors

Compounds nontoxic to animal, but inhibitors to methanogens have been used to reduce methane production. Although these compounds inhibit-specific enzymes involved in methanogenesis pathway, it has been reported that they could also have an impact on other microbial groups present and could affect the uptake of feed by the animal [5, 27]. The most used and effective compounds are the analogous of coenzyme M, inhibitors of methanopterin biosynthesis, nitrocompounds and halogenated compounds [6365].

Bromochloromethane (BCM), a methane analogue, has been extensively used to decrease methane production [6567] but has a limited use due to its great ozone depleting capacity [66]. This compound reduces vitamin B12 and inhibits the cobamide-dependent methyl transferase step of the biosynthesis pathway of methyl coenzyme M, involved in methanogenesis pathway. After 12 h of supplementation, BCM-cyclodextrin (0.5 g/100 kg live weight) decreased the methane production of steer by 29%, and without adversely affecting the animal productivity [65]. Mitsumori et al. [67] studied the effect of different concentrations of BCM-cyclodextrin (BCM-CD) on the rumen microbial population of goats. Doses of BCM-CD were of low (0.5 g/100 kg live weight LW), medium (2 g/100 kg LW) and high (5 g/100 kg LW), which decreased the methane emissions by 4.64, 71.46 and 91.23%, respectively. Denman et al. [68] analyzed the microbial diversity of the samples from the above study and reported that the relative abundance of Bacteroidetes increased with the BCM-CD doses, while Firmicutes, Synergistetes and Lentrisphaerae phyla decreased. In the case of control animal, Bacteroidetes (60%) was dominant, followed by Firmicutes (24%), Synergistetes and Lentisphaera (both contributed ~4%). Administration of BCM also reduced considerably methanogenic diversity, however, Methanobrevibater species were the most abundant in all treatments. Based on phylogenetic binding and functional assignment, the major genera were Prevotella and Selenomonas which were associated with the propionate production by the randomizing succinate pathway. This pathway was the primary route of H2 consumption and decreased H2 availability for methanogens.

2-bromoethanesulfonate (BES) is another common and successful compound to decrease methane emissions, which is an analog of coenzyme M. In an in vitro mesocosm study with cow manure and anaerobic digester sludge, a 89 and 100% decrease in methane production was observed at 0.5 and 10 mmol/L, respectively. Relative abundance of Methanosaeta and Methanosarcina decreased considerably at 10 mmol/L. Moreover, a decrease in mcrA expression, which encodes the α subunit of the methyl coenzyme M reductase and due to it is used for the relative measure of methane metabolites and methanogenic abundance in different environments [69], was observed with the increment of BES. A decrease in syntrophic-bacteria Syntrophomonas was observed too at both concentrations of BES. It is known for oxidation of butyrate and other fatty acids in syntrophic association with H2-consuming bacteria and/or hydrogenotrophic methanogens and could explain the decrease in methanogenic activity [70].

The inhibitory effect of chloroform is attributed to its capacity to target the corrinoid-containing MtrA subunit of the large multimeric membrane enzyme methyl tetrahydromethanopterin:coenzyme M methyltransferase [71]. Martínez-Fernández et al. [72] studied the inhibitory effect of chloroform-cyclodextrin (CCD) by way of supplementation; as low (1 g/100kg live weight LW), medium (1.6 g/100 kg LW) and high (2.6 g/100 kg LW) dose along with two diets (roughage:concentrate (60:40) or roughage hay) in eight steers. All three doses decreased the methane production by 14, 37 and 55%, respectively. Changes in microbial community were observed too, archaeal abundance was negatively correlated with CDD levels, Methanobacteriaceae family and Methanoplasmatales order were found to be decreased. Protozoan population increased with CCD doses with roughage:concentrate diet, while chloroform did not have any effect on fungi community. Bacterial population was also affected, relative abundance of Bacteroidetes increased, while Firmicutes, Synergistetes and Verrucomicrobia phyla were decreased. While methanogenesis was inhibited, an increment in the production of amino acids, organic and nucleic acids was observed. All of these metabolic changes modified the ruminal microbiome, increased the Bacteroidetes:Firmicutes ratio and decreased archaea and Synergistetes. Although abundance of fibrolytic bacteria, protozoa and fungi was not affected, methanogenesis was inhibited by 30%. They concluded that the use of chloroform as methanogenic inhibitor did not adversely affect rumen metabolism and could redirect H2 to another pathways producing non-methane end products.

Apart from the compounds mentioned, nitrocompounds are also being used in vivo to mitigate methane emissions. These compounds target of specific sites of MCR due to its molecular shape and oxidative potential and inhibit the last step of methanogenesis pathway. It has been reported that 3-nitrooxypropanol (NOP) at 40–80 mg/kg, decreased methane emissions around 30% and also increased body weight gain considerably without affecting feed intake or milk characteristics [73]. Duin et al. [74] reported that only 0.1 µM NOP is needed to inactivate completely MCR, and 1 µM to inhibit the methanogenic population. It was also reported that bacterial population was not affected by the addition of NOP, while methanogenic population decreased and protozoal abundance increased [75]. The decrease in methane production (−59.2%) by NOP (2 g/day) could be related directly to the reduction in the population of methanogens. The reduction in methanogen populations due to the addition of nitrocompounds need not always result in an increase in protozoan populations, since the compounds could also affect the symbiotic methanogens-protozoan association and thereby could result in decreased protozoan populations.

5.2.2. Plant bioactive compounds

Plant secondary metabolites have also been extensively used in the reduction of methane emissions. The most common used are tannins, saponins and essential oils, and they can affect methanogens either directly or indirectly. Further, they reduce protozoal population and thereby reducing symbiotically associated methanogens, apart from decreasing fiber digestibility and H2 production [76].

Tannins are polyphenolic compounds which form complexes with metal ions, amino acids and polysaccharides, and thereby reduce ruminal fermentation. They can be divided into hydrolysable and condensed tannins. Hydrolysable tannins at high concentrations may be toxic to ruminants, while condensed tannins can make several nutrients unavailable to the animal due to irreversible binding [77]. Moreover, they can bind to the gastrointestinal tract, causing negative effects [78]. However, they have been found to be effective in reducing methane emissions. Condensed tannins have been reported to reduce methane by around 16% based on dry matter intake (DMI) [79]. Total methanogen population decreased by 22.3–36.7% when purified hydrolysable (HT) and condensed tannins (CT) (1 mg/ml) were tested in vitro conditions. Hydrolysable tannins were found to be more effective than with condensed tannins in reducing methane formation [80]. On the contrary, Bhatta et al. [76] reported that CT had a greater effect on methane reduction (−5.5%) than HT (−0.6%) and its inhibitory effect on methanogens (−28.6%) was more than HT (-11.6%). Protozoan populations also decreased by 12.3% with HT diets. However, a combination of HT+CT diets had a more significant effect and a 36.2% decrease was reported. Although tannins reduced total VFA concentrations was found to increase propionate concentrations and decrease iso-acids, which could have a negative effect on methanogenesis. In previous studies, a reduction in total and cellulolytic bacteria in response to tannins was observed along with the reduction in VFA production and also H2 production, contributing to methane inhibition [81, 82].

Saponins are complex and diverse molecules which are divided in triterpene and steroid glycosides [83]. They are considered effective compounds to suppress methane production due to their anti-protozoan properties [54]. Their anti-protozoan properties are attributed mainly to the formation of complexes with sterols in the membrane surface of protozoans [84]. However, this is pH dependent and composition of diet with addition of saponins [85, 86]. Moreover, saponins are potential defaunation agents and could result in the reduction in enteric CH4 production by eliminating protozoa [9]. Nevertheless, they have an effect on the whole ruminant microbiome and animal digestion process, and not specifically targeting protozoan populations.

5.2.3. Lipid supplementation

Supplementation of lipids in ruminant diets is found to improve microbial metabolism of rumen, decreasing enteric methane emissions. Reduction in methane production could be due to the direct effect of fatty acids on methanogens, or indirectly due to the inhibition of the protozoan communities and associated methanogens due to enhanced propionate production. Beauchemi et al. [54] calculated that CH4 (g/kg DMI) is reduced by 5.6% for each percentage unit of lipid, while Eugène et al. [87] estimated the methane reduction to about 2.3%.

Lipids commonly supplemented to reduce enteric fermentation are calcium salts of fatty acids, hydrogenated fats, and fats of animal origin, extracted plant oils, oilseeds and wastes from processing plants with high fat content [88]. Based on a meta-analysis of 27 publications on the effect of fatty acids in ruminant diets, fatty acids C12:0 and C18:3 demonstrated a significant inhibitory effect on methanogenesis without affect the productivity in dairy cattle [89]. Patra and Yu [90] analyzed in vitro the effect of five essential oils (EO) such as clove oil (CLO; from Eugenia spp.), eucalyptus oil (EUO; from Eucalyptus globulus), garlic oil (GAO; from Allium sativum L.), origanum oil (ORO; from Thymus capitatus L. Hoffmanns & Link) and peppermint oil (PEO; from Mentha piperita L.) on methane production, fermentation and ruminal microbiome. CLO, EUO, GAO, ORO and PEO significantly reduced the methane formation by 34.4, 17.6, 42.3, 87 and 25.7%. Further, decrease in relative abundance of ruminant microbial population such as archaea, protozoa and major cellulolytic bacteria F. succinogenes, R. flavefaciens and R. albus was recorded. Microarray analysis by RumenBactArray showed that the effect of each oil tested was unique. Firmicutes phylum was decreased by addition ORO and GAO, but increased by PEO. While, Bacteroidetes phylum, mainly Prevotella OTUS were found to be increased by addition of ORO and PEO. EO decreased the abundance of several microorganisms, Syntrophococcus sucromutans, Succiniclasticum ruminis and Lachnobacterium and members of Lachnospiraceae, Ruminococcaceae, Prevotellaceae, Bacteroidales and Clostridiales. This was correlated with feed degradability, ammonia concentration and molar percentage of VFAs, which directly affect microbial communities, their metabolic interactions and hence the methane production.

Beauchemi et al. [91] studied the effect of addition of saturated and unsaturated long-chain fatty acids to cattle basal diet, consisting mainly of whole-crop silage. Lipids of animal origin (tallow) and sunflower oil at 34 g/kg, and oilseed (whole sunflower seeds) at 89.3 g/kg were added to bring the total dietary fat content to about 59 g/kg of dry matter. On basis of dry matter intake, diets containing tallow or sunflower oil decreased methane emissions by 11%, while sunflower seeds by 23%. Based on digestible energy intake, all lipid sources decreased methane emissions by 17%. Previously, coconut oil has also been reported as an effective inhibitor of methane production. Jordan et al. [92] reported a 39% decrease in methane emission at a concentration of 375 g/day.

Although supplements are being used primarily in reducing methane emission from livestock, their use in increasing efficiency in feed conversion and animal productivity, based on GEI, animal weight gain, meat and milk production has also been reported [73]. However, few other studies also have reported the negative effect of supplements on the quantity and quality of animal products such as milk and meat [60, 61]. This contradiction could be due to the reason that rumen microbial diversity is dependent on type and amount of feed, which in turn influences the nutrient absorption by animal. This implies that further studies on the relation between rumen microbiome and metabolomics of rumen are essential in order to understand the variations in relation to animal products due to supplements.

References

1 - IPCC (Intergovernmental Panel on Climate Change). Climate Change 2014: Mitigation of Climate Change. Cambridge University Press, New York, USA. 2015, p. 3.
2 - Steinfeld H, Gerber P, Wassenaar TD, Castel V, de Haan C. Livestock’s Long Shadow: Environmental Issues and Options. Food Agriculture Organization, Rome, Italy. 2006.
3 - FAO. Food and Agriculture Organization of the United Nations Rome, Italy. FAOSTAT. 2006.
4 - Sejian V, Lal R, Lakritz J, Ezeji T. Measurement and prediction of enteric methane emission. International Journal of Biometeorology. 2011;55(1):1–16. doi:10.1007/s00484-010-0356-7
5 - Herrero M, Havlík P, Valin H, Notenbaert A, Rufino MC, Thornton PK, Blümmel M, Weiss F, Grace D, Obersteiner M. Biomass use, production, feed efficiencies, and greenhouse gas emissions from global livestock systems. Proceedings of the National Academy of Sciences. 2013;110(52):20888–20893. doi:10.1073/pnas.1308149110
6 - Havlík P, Valin H, Herrero M, Obersteiner M, Schmid E, Rufino MC, Mosnier A, Thornton PK, Böttcher H, Conant RT, Frank S, Fritz S, Fuss S, Kraxner F, Notenbaert A. Climate change mitigation through livestock system transitions. Proceedings of the National Academy of Sciences. 2014;111(10):3709–3714. doi:10.1073/pnas.1308044111
7 - Bellarby J, Tirado R, Leip A, Weiss F, Lesschen JP, Smith P. Livestock greenhouse gas emissions and mitigation potential in Europe. Global Change Biology. 2013;19(1):3–18. doi:10.1111/j.1365-2486.2012.02786.x
8 - Bannink A, Van Schijndel MW, Dijkstra J. A model of enteric fermentation in dairy cows to estimate methane emission for the Dutch National Inventory Report using the IPCC Tier 3 approach. Animal Feed Science and Technology. 2011;166–167:603–618. doi:10.1016/j.anifeedsci.2011.04.043
9 - Boadi D, Benchaar C, Chiquette J, Massé D. Mitigation strategies to reduce enteric methane emissions from dairy cows: Update review. Canadian Journal of Animal Science. 2004;84(3):319–335. doi:10.4141/A03-109
10 - Hill J, McSweeney C, Wright ADG, Bishop-Hurley G, Kalantar-Zadeh K. Measuring methane production from ruminants. Trends in Biotechnology. 2016;34(1):26–35. doi:10.1016/j.tibtech.2015.10.004
11 - Ripple WJ, Smith P, Haberl H, Montzka SA, McAlpine C, Boucher DH. Ruminants, climate change and climate policy. Nature Climate Change. 2014;4(1):2–5. doi:10.1038/nclimate2081
12 - Chaucheyras-Durand F, Ossa F. Review: The rumen microbiome: Composition, abundance, diversity, and new investigative tools. The Professional Animal Scientist. 2014;30(1):1–12. doi:10.15232/S1080-7446(15)30076-0
13 - Caro D, LoPresti A, Davis SJ, Bastianoni S, Caldeira K. CH4 and N2O emissions embodied in international trade of meat. Environmental Research Letters. 2014;9(11):114005–114018. doi:10.1088/1748-9326/9/11/114005
14 - O’Mara FP. The significance of livestock as a contributor to global greenhouse gas emissions today and in the near future. Animal Feed Science and Technology. 2011;166–167:7–15. doi:10.1016/j.anifeedsci.2011.04.074
15 - Du Toit CJL, Meissner HH, Van Niekerk WA. Direct methane and nitrous oxide emissions of South African dairy and beef cattle. South African Journal of Animal Science. 2013;43(3):320–339. doi:10.4314/sajas.v43i3.7
16 - Hernandez-De Lira IO, Huber DH, Espinosa-Solares T, Balagurusamy N. Methane emission and bioenergy potential from livestock manures in Mexico. Journal of Renewable and Sustainable Energy. 2015;7(5):05117. doi:10.1063/1.4934564
17 - Castelán-Ortega OA, Ku-Vera JC, Estrada-Flores JG. Modeling methane emissions and methane inventories for cattle production systems in Mexico. Atmósfera. 2014;27(2):185–191. doi:10.1016/S0187-6236(14)71109-9
18 - Rendón-Huerta JA, Pinos-Rodríguez JM, García-López JC, Yáñez-Estrada LG, Kebreab E. Trends in greenhouse gas emissions from dairy cattle in Mexico between 1970 and 2010. Animal Production Science. 2014;54(3):292–298. doi:10.1071/AN12327
19 - Herrero M, Henderson B, Hvlik P, Thornton PK, Conant RT, Smith P, Wirsenius S, Hristov AN, Gerber P, Gill M, Butterbach-Bahl K. Greenhouse gas mitigation potentials in the livestock sector. Nature Climate Change. 2016;6:452–461. doi:10.1038/nclimate2925
20 - EPA. Environmental Protection Agency. Global Anthropogenic Non-CO2 Greenhouse Gas Emissions: 1990–2020. 2006. EPA Report No. 430-R-06-003, Office of Atmospheric Programs, Climate Change Division, Washington, DC.
21 - Russell JB, Rychlik JL. Factors that alter rumen microbial ecology. Science. 2001;292(5519):1119–1122. doi:10.1128/AEM.01289-09
22 - Mackie RI. Mutualistic fermentative digestion in the gastrointestinal tract: Diversity and evolution. Integrative and Comparative Biology. 2002;42(2):319–326. doi:10.1093/icb/42.2.319
23 - Valente TN, da Silva Lima E, dos Santos WB, Cesario AE, Tavares CA, de Freitas MA. Ruminal microorganism consideration and protein used in the metabolism of the ruminants: A review. African Journal of Microbiology Research. 2016;10(14):456–464. doi:10.5897/AJMR2016.7627
24 - Bergman EN. Energy contributions of volatile fatty acids from the gastrointestinal tract in various species. Physiological Reviews. 1990;70(2):567–590.
25 - Storm E, Ørskov ER. The nutritive value of rumen micro-organisms in ruminants. British Journal of Nutrition. 1983;50(2):479–485. doi:10.1079/BJN19830114
26 - Mackie RI, McSweeney CS, Aminov RI. Rumen. eLS. 2013. doi:10.1002/9780470015902.a0000404.pub2
27 - Patra AK. Enteric methane mitigation technologies for ruminant livestock: A synthesis of current research and future directions. Environmental Monitoring and Assessment. 2012;184(4):1929–1952. doi:10.1007/s10661-011-2090-y
28 - Gruninger RJ, Puniya AK, Callaghan TM, Edwards JE, Youssef N, Dagar SS, Filegerova K, Griffith GW, Forster R, Tsang A, McAllister T, Elshahed MS. Anaerobic fungi (phylum Neocallimastigomycota): Advances in understanding their taxonomy, life cycle, ecology, role and biotechnological potential. FEMS Microbiology Ecology. 2014;90(1):1–17. doi:10.1111/1574-6941.12383
29 - Kamra DN. Rumen microbial ecosystem. Current Science. 2005;89(1):124–135.
30 - Pers-Kamczyc E, Zmora P, Cieslak A, Szumacher-Strabel M. Development of nucleic acid based techniques and possibilities of their application to rumen microbial ecology research. Journal of Animal and Feed Sciences. 2011;20(3):315–337.
31 - Hungate RE. Ruminal Fermentation. In: Handbook of Physiology. Washington, DC: American Physiological Society. 1968, p. 2725–2745.
32 - Russell JB. Ecology of Rumen Microorganisms: Energy Use. In: Dobson A, Dobson MJ (eds.), Aspects of Digestive Physiology in Ruminants. Ithaca, NY: Cornell University Press. 1988, p. 74–98.
33 - Dijkstra J, Tamminga S. Simulation of the effects of diet on the contribution of rumen protozoa to degradation of fibre in the rumen. British Journal of Nutrition. 1995;74(5):617–634. doi:10.3168/jds.2006-518
34 - Dijkstra J, Boer H, Van Bruchem J, Bruining M, Tamminga S. Absorption of volatile fatty acids from the rumen of lactating dairy cows as influenced by volatile fatty acid concentration, pH and rumen liquid volume. British Journal of Nutrition. 1993;69(02):385–396. doi:10.1079/BJN19930041
35 - Morgavi DP, Forano E, Martin C, Newbold CJ. Microbial ecosystem and methanogenesis in ruminants. Animal. 2010;4(07):1024–1036. doi:10.1017/S1751731110000546
36 - Sieber JR, McInerney MJ, Gunsalus RP. Genomic insights into syntrophy: The paradigm for anaerobic metabolic cooperation. Annual Review of Microbiology. 2012;66:429–452. doi:10.1146/annurev-micro-090110-102844
37 - Abdoun K, Friederike S, Holger M. Ammonia and urea transport across the rumen epithelium: A review. Animal Health Research Reviews. 2006;7(1–2):43–59. doi:10.1017/S1466252307001156
38 - Hooke SE, Wright ADG, McBride BW. Methanogens: Methane producers of the rumen and mitigation strategies. Archaea. 2010;2010(1):1–11. doi:10.1155/2010/945785
39 - Johnson KA, Johnson DE. Methane emissions from cattle. Journal of Animal Science. 1995;73(8):2483–2492. doi:10.2527/1995.7382483x
40 - Zhou MI, Hernandez-Sanabria E. Assessment of the microbial ecology of ruminal methanogens in cattle with different feed efficiencies. Applied and Environmental Microbiology. 2009;75(20):6524–6533. doi:10.1128/AEM.02815-08
41 - Mao S, Zhang M, Liu J, Zhu W. Characterizing the bacterial microbiota across the gastrointestinal tracts of dairy cattle: Membership and potential function. Scientific Reports. 2015;5(16116):1–14. doi:10.1038/srep16116
42 - Henderson G, Cox F, Ganesh S, Jonker A, Young W. Rumen microbial community composition varies with diet and host, but a core microbiome is found across a wide geographical range. Scientific Reports. 2015;5:1–13. doi:10.1038/srep14567
43 - Pitta DW, Indugu N, Kumar S, Vecchiarelli B, Sinha R, Baker LD, Bhukya B, Ferguson JD. Metagenomic assessment of the functional potential of the rumen microbiome in Holstein dairy cows. Anaerobe. 2016;38:50–60. doi:10.1016/j.anaerobe.2015.12.003
44 - Kim M, Morrison M, Yu Z. Status of the phylogenetic diversity census of ruminal microbiome. FEMS Microbiology Ecology. 2011;76(1):49–63. doi:10.1111/j.1574-6941.2010.01029.x
45 - Wallace RJ, Rooke JA, McKain N, Duthie CA, Hyslop JJ, Ross DW, Waterhouse MW, Roehe R. The rumen microbial metagenome associated with high methane production in cattle. BMC Genomics. 2015;16(1):1–14. doi:10.1186/s12864-015-2032-0
46 - O’Neill BF, Deighton MH, O’loughlin BM, Mulligan FJ, Boland TM, O’donovan M, Lewis E. Effects of a perennial ryegrass diet or total mixed ration diet offered to spring-calving Holstein-Friesian dairy cows on methane emissions, dry matter intake, and milk production. Journal of Dairy Science. 2011;94(4):1941–1951. doi:10.3168/jds.2010-3361
47 - Li RW, Connor EE, Li C, Baldwin VI, Ransom L, Sparks ME. Characterization of the rumen microbiota of pre-ruminant calves using metagenomic tools. Environmental Microbiology. 2012;14(1):129–139. doi:10.1111/j.1462-2920.2011.02543.x
48 - Petri RM, Schwaiger T, Penner GB, Beauchemin KA, Forster RJ, McKinnon JJ, McAllister TA. Characterization of the core rumen microbiome in cattle during transition from forage to concentrate as well as during and after an acidotic challenge. PLoS One. 2013;8(12):e83424. doi:10.1371/journal.pone.0083424
49 - Beauchemin KA, McAllister TA, McGinn SM. Dietary mitigation of enteric methane from cattle. CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources. 2009;4(9):1–18. doi:10.1079/PAVSNNR20094035
50 - Eckard RJ, Grainger C, De Klein CA. Options for the abatement of methane and nitrous oxide from ruminant production: A review. Livestock Science. 2010;130(1–3):47–56. doi:10.1016/j.livsci.2010.02.010
51 - Gerber PJ, Hristov AN, Henderson B, Makkar H, Oh J, Lee C, Meinen R, Montes F, Ott T, Firkins J, Rotz A. Technical options for the mitigation of direct methane and nitrous oxide emissions from livestock: A review. Animal. 2013;7(2s):220–234. doi:10.1017/S1751731113000876
52 - Hristov AN, Oh J, Firkins JL, Dijkstra J, Kebreab E, Waghorn G, Gerber PJ. Special topics—mitigation of methane and nitrous oxide emissions from animal operations: I. A review of enteric methane mitigation options. Journal of Animal Science. 2013;91(11):5045–5069. doi:10.2527/jas.2013-6583
53 - Kalac P. The effects of silage feeding on some sensory and health attributes of cow’s milk: A review. Food Chemistry. 2011;125(2):307–317. doi:10.1016/j.foodchem.2010.08.077
54 - Beauchemin KA, Kreuzer M, O’mara F, McAllister TA. Nutritional management for enteric methane abatement: A review. Animal Production Science. 2008;48(8):21–27. doi:10.1071/EA07199
55 - Iqbal MF, Cheng YF, Zhu WY, Zeshan B. Mitigation of ruminant methane production: Current strategies, constraints and future options. World Journal of Microbiology and Biotechnology. 2008;24(12):2747–2755. doi:10.1007/s11274-008-9819-y
56 - Hegarty RS. Reducing rumen methane emissions through elimination of rumen protozoa. Crop and Pasture Science. 1999;50(8):1321–1328. doi:10.1071/AR99008
57 - Lettat A, Hassanat F, Benchaar C. Corn silage in dairy cow diets to reduce ruminal methanogenesis: Effects on the rumen metabolically active microbial communities. Journal of Dairy Science. 2013;96(8):5237–5248. doi:10.3168/jds.2012-6481
58 - Nagaraja TG, Titgemeyer EC. Ruminal acidosis in beef cattle: The current microbiological and nutritional outlook. Journal of Dairy Science. 2007;90:E17–EE38. doi:10.3168/jds.2006-478
59 - Bekele AZ, Koike S, Kobayashi Y. Genetic diversity and diet specificity of ruminal Prevotella revealed by 16S rRNA gene-based analysis. FEMS Microbiology Letters. 2010;305(1):49–57. doi:10.1111/j.1574-6968.2010.01911.x
60 - Saleem F, Ametaj BN, Bouatra S, Mandal R, Zebeli Q, Dunn SM, Wishart DS. A metabolomics approach to uncover the effects of grain diets on rumen health in dairy cows. Journal of Dairy Science. 2012;95(11):6606–6623. doi:10.3168/jds.2012-5403
61 - Loor JJ, Elolimy AA, McCann JC. Dietary impacts on rumen microbiota in beef and dairy production. Animal Frontiers. 2016;6(3):22–29. doi:10.2527/af.2016-0030
62 - Kittelmann S, Seedorf H, Walters WA, Clemente JC, Knight R, Gordon JI, Janssen PH. Simultaneous amplicon sequencing to explore co-occurrence patterns of bacterial, archaeal and eukaryotic microorganisms in rumen microbial communities. PLoS One. 2013;8(2):e47879. doi:10.1371/journal.pone.0047879
63 - Dumitru R, Palencia H, Schroeder SD, Demontigny BA, Takacs JM, Rasche ME, Ragsdale SW. Targeting methanopterin biosynthesis to inhibit methanogenesis. Applied and Environmental Microbiology. 2003;69(12):7236–7241. doi:10.1128/AEM.69.12.7236–7241.2003
64 - Zhou Z, Meng Q, Yu Z. Effects of methanogenic inhibitors on methane production and abundances of methanogens and cellulolytic bacteria in in vitro ruminal cultures. Applied and Environmental Microbiology. 2011;77(8):2634–2637. doi:10.1128/AEM.02779-10
65 - Denman SE, Tomkins NW, McSweeney CS. Quantitation and diversity analysis of ruminal methanogenic populations in response to the antimethanogenic compound bromochloromethane. FEMS Microbiology Ecology. 2007;62(3):313–322. doi:10.1111/j.1574-6941.2007.00394.x
66 - Tomkins NW, Colegate SM, Hunter RA. A bromochloromethane formulation reduces enteric methanogenesis in cattle fed grain-based diets. Animal Production Science. 2009;49(12):1053–1058. doi:10.1071/EA08223
67 - Mitsumori M, Shinkai T, Takenaka A, Enishi O, Higuchi K, Kobayashi Y, Nonaka I, Asanuma N, Denman SE, McSweeney CS. Responses in digestion, rumen fermentation and microbial populations to inhibition of methane formation by a halogenated methane analogue. British Journal of Nutrition. 2012;108(03):482–491. doi:10.1017/S0007114511005794
68 - Denman SE, Fernandez GM, Shinkai T, Mitsumori M, McSweeney CS. Metagenomic analysis of the rumen microbial community following inhibition of methane formation by a halogenated methane analog. Frontiers in Microbiology. 2015;6:1–12. doi:10.3389/fmicb.2015.01087
69 - Alvarado A, Montañez-Hernández LE, Palacio-Molina SL, Oropeza-Navarro R, Luévanos-Escareño MP, Balagurusamy N. Microbial trophic interactions and mcrA gene expression in monitoring of anaerobic digesters. Frontiers in Microbiology. 2014;5:597. doi:10.3389/fmicb.2014.00597
70 - Webster TM, Smith AL, Reddy RR, Pinto AJ, Hayes KF, Raskin L. Anaerobic microbial community response to methanogenic inhibitors 2-bromoethanesulfonate and propynoic acid. MicrobiologyOpen. 2016;4:537–550. doi:10.1002/mbo3.349
71 - Henderson G, Cook GM, Ronimus RS. Enzyme-and gene-based approaches for developing methanogen-specific compounds to control ruminant methane emissions: A review. Animal Production Science. 2016.A–J. doi:10.1071/AN15757
72 - Martinez-Fernandez G, Denman SE, Yang C, Cheung J, Mitsumori M, McSweeney CS. Methane inhibition alters the microbial community, hydrogen flow and fermentation response in the rumen of cattle. Frontiers in Microbiology. 2016;7:1–14. (1122). doi:10.3389/fmicb.2016.01122
73 - Hristov AN, Oh J, Giallongo F, Frederick TW, Harper MT, Weeks HL, Kindermann M. An inhibitor persistently decreased enteric methane emission from dairy cows with no negative effect on milk production. Proceedings of the National Academy of Sciences. 2015;112(34):10663–10668. doi:10.1073/pnas.1504124112
74 - Duin EC, Wagner T, Shima S, Prakash D, Cronin B, Yáñez-Rui DR, Kindermann M. Mode of action uncovered for the specific reduction of methane emissions from ruminants by the small molecule 3-nitrooxypropanol. Proceedings of the National Academy of Sciences. 2016;113(22):6172–6177. doi:10.1073/pnas.1600298113
75 - Romero-Perez A, Okine EK, McGinn SM, Guan LL, Oba M, Duval SM, Beauchemin KA. Sustained reduction in methane production from long-term addition of 3-nitrooxypropanol to a beef cattle diet. Journal of Animal Science. 2015;93(4):1790–1791. doi:10.2527/jas.2014-8726
76 - Bhatta R, Uyeno Y, Tajima K, Takenaka A, Yabumoto Y, Nonaka I, Enishi O, Kurihara M. Difference in the nature of tannins on in vitro ruminal methane and volatile fatty acid production and on methanogenic archaea and protozoal populations. Journal of Dairy Science. 2009;92(11):5512–5522. doi:10.3168/jds.2008-1441
77 - Reed JD. Nutritional toxicology of tannins and related polyphenols in forage legumes. Journal of Animal Science. 1995;73(5):1516–1528. doi:10.2527/1995.7351516x
78 - Makkar HPS, Francis G, Becker K. Bioactivity of phytochemicals in some lesser-known plants and their effects and potential applications in livestock and aquaculture production systems. Animal. 2007;1(09):1371–1391. doi:10.1017/S1751731107000298
79 - Grainger C, Clarke T, Auldist MJ, Beauchemin KA, McGinn SM, Waghorn GC, Eckard RJ. Potential use of Acacia mearnsii condensed tannins to reduce methane emissions and nitrogen excretion from grazing dairy cows. Canadian Journal of Animal Science. 2009;89(2):241–251. doi:10.4141/CJAS08110
80 - Jayanegara A, Goel G, Makkar HP, Becker K. Divergence between purified hydrolysable and condensed tannin effects on methane emission, rumen fermentation and microbial population in vitro. Animal Feed Science and Technology. 2015;209:60–68. doi:10.1016/j.anifeedsci.2015.08.002
81 - Castro-Montoya JM, Makkar HPS, Becker K. Chemical composition of rumen microbial fraction and fermentation parameters as affected by tannins and saponins using an in vitro rumen fermentation system. Canadian Journal of Animal Science. 2011;91(3):433–448. doi:10.4141/cjas2010-028
82 - Ghasemi S, Naserian AA, Valizadeh R, Tahmasebi AM, Vakili AR, Behgar M, Ghovvati S. Inclusion of pistachio hulls as a replacement for alfalfa hay in the diet of sheep causes a shift in the rumen cellulolytic bacterial population. Small Ruminant Research. 2012;104(1–3):94–98. doi:10.1016/j.smallrumres.2011.09.052
83 - Vincken JP, Heng L, de Groot A, Gruppen H. Saponins, classification and occurrence in the plant kingdom. Phytochemistry. 2007;68(3):275–297. doi:10.1016/j.phytochem.2006.10.008
84 - Wallace RJ, McEwan NR, McIntosh FM, Teferedegne B, Newbold CJ. Natural products as manipulators of rumen fermentation. Asian Australasian Journal of Animal Sciences. 2002;15(10):1458–1468. doi:10.5713/ajas.2002.1458
85 - Lila ZA, Mohammed N, Kanda S, Kamada T, Itabashi H. Effect of sarsponin on ruminal fermentation with particular reference to methane production in vitro. Journal of Dairy Science. 2003;86(10):3330–3336. doi:10.3168/jds.S0022-0302(03)73935-6
86 - Hess HD, Kreuzer M, Diaz TE, Lascano CE, Carulla JE, Soliva CR, Machmüller A. Saponin rich tropical fruits affect fermentation and methanogenesis in faunated and defaunated rumen fluid. Animal Feed Science and Technology. 2003;109(1):79–94. doi:10.1016/S0377-8401(03)00212-8
87 - Eugène M, Massé D, Chiquette J, Benchaar C. Meta-analysis on the effects of lipid supplementation on methane production in lactating dairy cows. Canadian Journal of Animal Science. 2008;88(2):331–337. doi:10.4141/CJAS07112
88 - Jenkins T. Success of fat in dairy rations depends on the amount. Feedstuffs (USA). 1997;2:11–12.
89 - Patra AK. The effect of dietary fats on methane emissions, and its other effects on digestibility, rumen fermentation and lactation performance in cattle: A meta-analysis. Livestock Science. 2013;155(2–3):244–254. doi:10.1016/j.livsci.2013.05.023
90 - Patra AK, Yu Z. Effects of essential oils on methane production and fermentation by, and abundance and diversity of, rumen microbial populations. Applied and Environmental Microbiology. 2012;78(12):4271–4280. doi:10.1128/AEM.00309-12
91 - Beauchemin KA, McGinn SM, Petit HV. Methane abatement strategies for cattle: Lipid supplementation of diets. Canadian Journal of Animal Science. 2007;87(3):431–440. doi:10.4141/CJAS07011
92 - Jordan E, Lovett DK, Hawkins M, Callan JJ, O’Mara FP. The effect of varying levels of coconut oil on intake, digestibility and methane output from continental cross beef heifers. Animal Science. 2006;82(06):859–865. doi:10.1017/ASC2006107.