A meta-analysis of methane mitigation potential of feed additives evaluated in vitro

A systematic literature review of in vitro studies was performed to identify methane (CH4) mitigation interventions with a potential to reduce CH4 emission in vivo. Data from 277 peer-reviewed studies published between 1979 and 2018 were reviewed. Individual CH4 mitigation interventions were classified into 14 categories of feed additives based on their type, chemical composition, and mode of action. Response variables evaluated were absolute CH4 emission (number of treatment means comparisons = 1,325); total volatile fatty acids (VFA; n = 1,007), acetate (n = 783), propionate (n = 792), and butyrate (n = 776) concentrations; acetate to propionate ratio (A:P; n = 675); digestibility of dry matter (DM; n = 489), organic matter (OM; n = 277), and neutral detergent fiber (NDF; n = 177). Total gas production was used as an explanatory variable in the model for CH4 production. Relative mean difference between treatment and control means reported in the studies were calculated and used for statistical analysis. Robust variance estimation method was used to analyze the effects of CH4 mitigation interventions. In vitro CH4 production was decreased by antibodies (−38.9%), chemical inhibitors (−29.2%), electron sinks (−18.9%), essential oils (−18.2%), plant extracts (−14.5%), plants inclusion (−11.7%), saponins (−14.8%), and tannins (−14.5%). Overall effects of direct fed microbials, enzymes, macroalgae, and organic acids supplementation did not affect CH4 production in the current meta-analysis. When considering the effects of individual mitigation interventions containing a minimum number of 4 degrees of freedom within feed additives categories, Enterococcus spp. (i.e., direct fed microbial), nitrophenol (i.e., electron sink), and Leucaena spp. (i.e., tannins) decreased CH4 production by 20.3, 27.1, and 23.5%, respectively, without extensively, or only slightly, affecting ruminal fermentation and digestibility of nutrients. It should be noted, however, that although the total number of publications (n = 277) and treatment means comparisons (n = 1,325 for CH4 production) in the current analysis were high, data for most mitigation interventions were obtained from less than 5 observations (e.g., maximum number of observations was 4, 7, and 22 for nitrophenol, Enterococcus spp., and Leucaena spp., respectively), because of limited data available in the literature. These should be further evaluated in vitro and in vivo to determine their true potential to decrease enteric CH4 production, yield, and intensity. Some mitigation interventions (e.g., magnesium, Heracleum spp., nitroglycerin, β-cyclodextrin, Leptospermum pattersoni, Fructulus Ligustri, Salix caprea, and Sesbania grandiflora) decreased in vitro CH4 production by over 50% but did not have enough observations in the database. These should be more extensively investigated in vitro, and the dose effect must be considered before adoption of mitigation interventions in vivo

Rumen physiology constrains diet niche: linking digestive physiology and food selection across wild ruminant species

We propose a hypothesis for digestive constraints on the browsing and grazing options available to ruminants: that the diet-niche range (maximum and minimum grass intake) of a species is dependent upon its predisposition to stratified rumen contents, based on observations that this characteristic is a critical step towards enhanced fibre digestion and greater fluid throughput. We compare a physiological (heterogeneity of ingesta fluid content) and an anatomical (the intraruminal papillation pattern) measure with dietary evidence for a range of African and temperate species. Both measures are strongly related to the mean percentage of grass in species’ natural diets, as well as to the maximum and minimum levels of grass intake, respectively. The nature of these effects implies a stratification-level threshold, below which a species will not use a grass-based diet, but above which grass consumption can increase exponentially. However, above this threshold, a minimum percentage of grass in the diet is a prerequisite for optimal performance. We argue that this second constraint is crucial, as it depicts how a greater fluid throughput reduces potential for detoxification of plant secondary compounds, and therefore limits the maximum amount of browse a stratifying species will consume

Spin alignment of K∗(892)±K^*(892)^\pm mesons produced in neutron-carbon interactions

A new precise measurements of spin density matrix element $\rho_{00}$ of $K^*(892)^{\pm}$ mesons produced inclusively in neutron-carbon interactions at \~60 GeV have been carried out in the EXCHARM experiment at the Serpukhov accelerator. The values of $\rho_{00}$ obtained in the transversity frame are $0.424\pm0.011(stat)\pm0.018(sys)$ for $K^*(892)^+$ and $0.393\pm0.025(stat)\pm0.018(sys)$ for $K^*(892)^-$. Significant $P_T$ dependence of $\rho_{00}$ has been observed in $K^*(892)^+$ production.Comment: 8 pages, LaTeX, 3 eps figure

Mitigation of methane and nitrous oxide emissions from animal operations: II. A review of manure management mitigation options

This review analyzes published data on manure management practices used to mitigate methane (CH4) and nitrous oxide (N2O) emissions from animal operations. Reducing excreted nitrogen (N) and degradable organic carbon (C) by diet manipulation to improve the balance of nutrient inputs with production is an effective practice to reduce CH4 and N2O emissions. Most CH4 is produced during manure storage; therefore, reducing storage time, lowering manure temperature by storing it outside during colder seasons, and capturing and combusting the CH4 produced during storage are effective practices to reduce CH4 emission. Anaerobic digestion with combustion of the gas produced is effective in reducing CH4 emission and organic C content of manure; this increases readily available C and N for microbial processes creating little CH4 and increased N2O emissions following land application. Nitrous oxide emission occurs following land application as a byproduct of nitrification and dentrification processes in the soil, but these processes may also occur in compost, biofilter materials, and permeable storage covers. These microbial processes depend on temperature, moisture content, availability of easily degradable organic C, and oxidation status of the environment, which make N2O emissions and mitigation results highly variable. Managing the fate of ammoniacal N is essential to the success of N2O and CH4 mitigation because ammonia is an important component in the cycling of N through manure, soil, crops, and animal feeds. Manure application techniques such as subsurface injection reduce ammonia and CH4 emissions but can result in increased N2O emissions. Injection works well when combined with anaerobic digestion and solids separation by improving infiltration. Additives such as urease and nitrification inhibitors that inhibit microbial processes have mixed results but are generally effective in controlling N2O emission from intensive grazing systems. Matching plant nutrient requirements with manure fertilization, managing grazing intensity, and using cover crops are effective practices to increase plant N uptake and reduce N2O emissions. Due to system interactions, mitigation practices that reduce emissions in one stage of the manure management process may increase emissions elsewhere, so mitigation practices must be evaluated at the whole farm level

Methane prediction equations including genera of rumen bacteria as predictor variables improve prediction accuracy

Methane (CH) emissions from ruminants are of a significant environmental concern, necessitating accurate prediction for emission inventories. Existing models rely solely on dietary and host animal-related data, ignoring the predicting power of rumen microbiota, the source of CH. To address this limitation, we developed novel CH prediction models incorporating rumen microbes as predictors, alongside animal- and feed-related predictors using four statistical/machine learning (ML) methods. These include random forest combined with boosting (RF-B), least absolute shrinkage and selection operator (LASSO), generalized linear mixed model with LASSO (glmmLasso), and smoothly clipped absolute deviation (SCAD) implemented on linear mixed models. With a sheep dataset (218 observations) of both animal data and rumen microbiota data (relative sequence abundance of 330 genera of rumen bacteria, archaea, protozoa, and fungi), we developed linear mixed models to predict CH production (g CH/animal·d, ANIM-B models) and CH yield (g CH/kg of dry matter intake, DMI-B models). We also developed models solely based on animal-related data. Prediction performance was evaluated 200 times with random data splits, while fitting performance was assessed without data splitting. The inclusion of microbial predictors improved the models, as indicated by decreased root mean square prediction error (RMSPE) and mean absolute error (MAE), and increased Lin’s concordance correlation coefficient (CCC). Both glmmLasso and SCAD reduced the Akaike information criterion (AIC) and Bayesian information criterion (BIC) for both the ANIM-B and the DMI-B models, while the other two ML methods had mixed outcomes. By balancing prediction performance and fitting performance, we obtained one ANIM-B model (containing 10 genera of bacteria and 3 animal data) fitted using glmmLasso and one DMI-B model (5 genera of bacteria and 1 animal datum) fitted using SCAD. This study highlights the importance of incorporating rumen microbiota data in CH prediction models to enhance accuracy and robustness. Additionally, ML methods facilitate the selection of microbial predictors from high-dimensional metataxonomic data of the rumen microbiota without overfitting. Moreover, the identified microbial predictors can serve as biomarkers of CH emissions from sheep, providing valuable insights for future research and mitigation strategies.Te authors gratefully acknowledge funding for this project from the USDA National Institute of Food and Agriculture (Award number: 2014-67003-21979). Te animal and microbial data originated from a study funded by the Pastoral Greenhouse Gas Research Consortium (www.pggrc.co.nz)

Full adoption of the most effective strategies to mitigate methane emissions by ruminants can help meet the 1.5 °C target by 2030 but not 2050

To meet the 1.5 °C target, methane (CH) from ruminants must be reduced by 11 to 30% by 2030 and 24 to 47% by 2050 compared to 2010 levels. A meta-analysis identified strategies to decrease product-based (PB; CH per unit meat or milk) and absolute (ABS) enteric CH emissions while maintaining or increasing animal productivity (AP; weight gain or milk yield). Next, the potential of different adoption rates of one PB or one ABS strategy to contribute to the 1.5 °C target was estimated. The database included findings from 430 peer-reviewed studies, which reported 98 mitigation strategies that can be classified into three categories: animal and feed management, diet formulation, and rumen manipulation. A random-effects meta-analysis weighted by inverse variance was carried out. Three PB strategies—namely, increasing feeding level, decreasing grass maturity, and decreasing dietary forage-to-concentrate ratio—decreased CH per unit meat or milk by on average 12% and increased AP by a median of 17%. Five ABS strategies—namely CH inhibitors, tanniferous forages, electron sinks, oils and fats, and oilseeds—decreased daily methane by on average 21%. Globally, only 100% adoption of the most effective PB and ABS strategies can meet the 1.5 °C target by 2030 but not 2050, because mitigation effects are offset by projected increases in CH due to increasing milk and meat demand. Notably, by 2030 and 2050, low- and middle-income countries may not meet their contribution to the 1.5 °C target for this same reason, whereas high-income countries could meet their contributions due to only a minor projected increase in enteric CH emissions.We 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 multinational initiative funded by the Joint Programming Initiative on Food Security, Agriculture, 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). We thank MitiGate, which was part of the Animal Change project funded by the EU under Grant Agreement FP7-266018 for sharing their database with us (http://mitigate.ibers.aber.ac.uk/, accessed 1 July 2017). Part of C.A., A.N.H., and S.C.M.’s time in the early stages of this project was funded by the Kravis Scientific Research Fund (New York) and a gift from Sue and Steve Mandel to the Environmental Defense Fund. Another part of C.A.’s work on this project was supported by the National Program for Scientific Research and Advanced Studies - PROCIENCIA within the framework of the "Project for the Improvement and Expansion of the Services of the National System of Science, Technology and Technological Innovation" (Contract No. 016-2019) and by the German Federal Ministry for Economic Cooperation and Development (issued through Deutsche Gesellschaft für Internationale Zusammenarbei) through the research “Programme of Climate Smart Livestock” (Programme 2017.0119.2). Part of A.N.H.’s work was funded by the US Department of Agriculture (Washington, DC) National Institute of Food and Agriculture Federal Appropriations under Project PEN 04539 and Accession no. 1000803. E.K. was supported by the Sesnon Endowed Chair Fund of the University of California, Davis

Mitigation of methane and nitrous oxide emissions from animal operations: I. A review of enteric methane mitigation options

The goal of this review was to analyze published data related to mitigation of enteric methane (CH4) emissions from ruminant animals to document the most effective and sustainable strategies. Increasing forage digestibility and digestible forage intake was one of the major recommended CH4 mitigation practices. Although responses vary, CH4 emissions can be reduced when corn silage replaces grass silage in the diet. Feeding legume silages could also lower CH4 emissions compared to grass silage due to their lower fiber concentration. Dietary lipids can be effective in reducing CH4 emissions, but their applicability will depend on effects on feed intake, fiber digestibility, production, and milk composition. Inclusion of concentrate feeds in the diet of ruminants will likely decrease CH4 emission intensity (Ei; CH4 per unit animal product), particularly when inclusion is above 40% of dietary dry matter and rumen function is not impaired. Supplementation of diets containing medium to poor quality forages with small amounts of concentrate feed will typically decrease CH4 Ei. Nitrates show promise as CH4 mitigation agents, but more studies are needed to fully understand their impact on whole-farm greenhouse gas emissions, animal productivity, and animal health. Through their effect on feed efficiency and rumen stoichiometry, ionophores are likely to have a moderate CH4 mitigating effect in ruminants fed high-grain or mixed grain–forage diets. Tannins may also reduce CH4 emissions although in some situations intake and milk production may be compromised. Some direct-fed microbials, such as yeast-based products, might have a moderate CH4–mitigating effect through increasing animal productivity and feed efficiency, but the effect is likely to be inconsistent. Vaccines against rumen archaea may offer mitigation opportunities in the future although the extent of CH4 reduction is likely to be small and adaptation by ruminal microbes and persistence of the effect is unknown. Overall, improving forage quality and the overall efficiency of dietary nutrient use is an effective way of decreasing CH4 Ei. Several feed supplements have a potential to reduce CH4 emission from ruminants although their long-term effect has not been well established and some are toxic or may not be economically feasible

Mitigation of methane and nitrous oxide emissions from animal operations: III. A review of animal management mitigation options

The goal of this review was to analyze published data on animal management practices that mitigate enteric methane (CH4) and nitrous oxide (N2O) emissions from animal operations. Increasing animal productivity can be a very effective strategy for reducing greenhouse gas (GHG) emissions per unit of livestock product. Improving the genetic potential of animals through planned cross-breeding or selection within breeds and achieving this genetic potential through proper nutrition and improvements in reproductive efficiency, animal health, and reproductive lifespan are effective approaches for improving animal productivity and reducing GHG emission intensity. In subsistence production systems, reduction of herd size would increase feed availability and productivity of individual animals and the total herd, thus lowering CH4 emission intensity. In these systems, improving the nutritive value of low-quality feeds for ruminant diets can have a considerable benefit on herd productivity while keeping the herd CH4 output constant or even decreasing it. Residual feed intake may be a tool for screening animals that are low CH4 emitters, but there is currently insufficient evidence that low residual feed intake animals have a lower CH4 yield per unit of feed intake or animal product. Reducing age at slaughter of finished cattle and the number of days that animals are on feed in the feedlot can significantly reduce GHG emissions in beef and other meat animal production systems. Improved animal health and reduced mortality and morbidity are expected to increase herd productivity and reduce GHG emission intensity in all livestock production systems. Pursuing a suite of intensive and extensive reproductive management technologies provides a significant opportunity to reduce GHG emissions. Recommended approaches will differ by region and species but should target increasing conception rates in dairy, beef, and buffalo, increasing fecundity in swine and small ruminants, and reducing embryo wastage in all species. Interactions among individual components of livestock production systems are complex but must be considered when recommending GHG mitigation practices