Challenges and opportunities to capture dietary effects in on-farm greenhouse gas emissions models of ruminant systems

Improving Nutrition Security in Low- and Middle-Income Countries and the Role of Animal-Source Foods

Nutrition security is challenging in regions where resources are limited and food production is naturally constrained. In low- and middle-income countries (LMICs), undernutrition is high for many reasons, including lack of nutritional diversity and low high-quality protein content. Interest in the role of animal-source food (ASF) in reducing nutrition insecurity is increasing, as evidence from LMICs suggests that consumption of ASF is strongly associated with reduction in stunting, improved diet quality, and overall nutrition, particularly in early stages of life. We review the strengths and limitations of ASF consumption in terms of accessibility, safety, and nutritional benefits compared to non-ASF sources. We present a critical discussion on existing barriers to ASF consumption and its future directions in LMICs. Understanding the role of ASF in improving nutrition security in LMICs is crucial to optimizing public health, designing appropriate interventions, and implementing effective policy in resource-poor settings.

Feed additives for methane mitigation: Recommendations for testing enteric methane-mitigating feed additives in ruminant studies

There is a need for rigorous and scientifically-based testing standards for existing and new enteric methane mitigation technologies, including antimethanogenic feed additives (AMFA). The current review provides guidelines for conducting and analyzing data from experiments with ruminants intended to test the antimethanogenic and production effects of feed additives. Recommendations include study design and statistical analysis of the data, dietary effects, associative effect of AMFA with other mitigation strategies, appropriate methods for measuring methane emissions, production and physiological responses to AMFA, and their effects on animal health and product quality. Animal experiments should be planned based on clear hypotheses, and experimental designs must be chosen to best answer the scientific questions asked, with pre-experimental power analysis and robust post-experimental statistical analyses being important requisites. Long-term studies for evaluating AMFA are currently lacking and are highly needed. Experimental conditions should be representative of the production system of interest, so results and conclusions are applicable and practical. Methane-mitigating effects of AMFA may be combined with other mitigation strategies to explore additivity and synergism, as well as trade-offs, including relevant manure emissions, and these need to be studied in appropriately designed experiments. Methane emissions can be successfully measured, and efficacy of AMFA determined, using respiration chambers, the sulfur hexafluoride method, and the GreenFeed system. Other techniques, such as hood and face masks, can also be used in short-term studies, ensuring they do not significantly affect feed intake, feeding behavior, and animal production. For the success of an AMFA, it is critically important that representative animal production data are collected, analyzed, and reported. In addition, evaluating the effects of AMFA on nutrient digestibility, animal physiology, animal health and reproduction, product quality, and how AMFA interact with nutrient composition of the diet is necessary and should be conducted at various stages of the evaluation process. The authors emphasize that enteric methane mitigation claims should not be made until the efficacy of AMFA is confirmed in animal studies designed and conducted considering the guidelines provided herein.

Feed additives for methane mitigation: Assessment of feed additives as a strategy to mitigate enteric methane from ruminants-Accounting; How to quantify the mitigating potential of using antimethanogenic feed additives

Recent advances in our understanding of methanogenesis have led to the development of antimethanogenic feed additives (AMFA) that can reduce enteric methane (CH4) emissions to varying extents, via direct targeting of methanogens, alternative electron acceptors, or altering the rumen environment. Here we examine current and new approaches used for the accounting (i.e., quantification) of enteric CH4 abatement by the use of AMFA in the livestock sector from the individual animal to the global scale. Along with this process, recommendations are provided on how to account for the mitigation potential at the animal level, as well as in farm-scale models, emissions trading schemes, life cycle assessment, and carbon (C) footprinting tools, and in regional and national inventories. In addition, an assessment of uncertainties and potential trade-offs and off-setting with the use of AMFA (i.e., efficacy vs. effectiveness, upstream and downstream emissions) is provided. The accounting of on-farm enteric CH4 emissions and benefits from the use of AMFA starts with the ruminant animal (with estimates obtained from a range of approaches, from simple empirical emission factors or equations to complex process-based models) and goes all the way to national and supranational accounting. The choice of methodologies and levels of complexity to account for mitigation of enteric CH4 (or total GHG) emissions in livestock systems must be tailored to the scale of analysis aimed, the availability of input data to represent contextualized conditions, and the accounting objectives (e.g., academic exercise vs. producer's GHG certification vs. national GHG inventory). The accounting of enteric CH4 mitigating effects needs to consider the AMFA delivery methods and synergies and trade-offs of GHG emissions at levels before and beyond (upstream and downstream) the animal to fully assess the impact of AMFA use. At large, the accounting of methane abatement by feed additives remains to be fully assessed beyond experimental results (efficacy) to address pragmatism (effectiveness), potential for adoption, and societal acceptance.

Relevance of farm-scale indicators and tools for farmers to assess sustainability of their mixed crop-ruminant livestock systems

Ensuring the sustainability and circularity of mixed crop-ruminant livestock systems is essential if they are to deliver on the enhancement of long-term productivity and profitability with a smaller footprint. The objectives of this study were to select indicators in the environmental, economic and social dimensions of sustainability of crop-livestock systems, to assess if these indicators are relevant in the operational schedule of farmers, and to score the indicators in these farm systems. The scoring system was based on relevance to farmers, data availability, frequency of use, and policy. The study was successful in the assemblage of a suite of indicators comprising three dimensions of sustainability and the development of criteria to assess the usefulness of these indicators in crop-ruminant livestock systems in distinct agro-climatic regions across the globe. Except for ammonia emissions, indicators within the Emissions to air theme obtained high scores, as expected from mixed crop-ruminant systems in countries transitioning towards low emission production systems. Despite the inherent association between nutrient losses and water quality, the sum of scores was numerically greater for the former, attributed to a mix of economic and policy incentives. The sum of indicator scores within the Profitability theme (farm net income, expenditure and revenue) received the highest scores in the economic dimension. The Workforce theme (diversity, education, succession) stood out within the social dimension, reflecting the need for an engaged labor force that requires knowledge and skills in both crop and livestock husbandry. The development of surveys with farmers/stakeholders to assess the relevance of farm-scale indicators and tools is important to support direct actions and policies in support of sustainable mixed crop-ruminant livestock farm systems.

An integral assessment of the impact of diet and manure management on whole-farm greenhouse gas and nitrogen emissions in dairy cattle production systems using process-based models

Feed management decisions are crucial in mitigating greenhouse gas (GHG) and nitrogen (N) emissions from ruminant farming systems. However, assessing the downstream impact of diet on emissions in dairy production systems is complex, due to the multifunctional relationships between a variety of distinct but interconnected sources such as animals, housing, manure storage, and soil. Therefore, there is a need for an integral assessment of the direct and indirect GHG and N emissions that considers the underlying processes of carbon (C), N and their drivers within the system. Here we show the relevance of using a cascade of process-based (PB) models, such as Dutch Tier 3 and (Manure)-DNDC (Denitrification-Decomposition) models, for capturing the downstream influence of diet on whole-farm emissions in two contrasting case study dairy farms: a confinement system in Germany and a pasture-based system in New Zealand. Considerable variation was found in emissions on a per hectare and per head basis, and across different farm components and categories of animals. Moreover, the confinement system had a farm C emission of 1.01 kg CO2-eq kg-1 fat and protein corrected milk (FPCM), and a farm N emission of 0.0300 kg N kg-1 FPCM. In contrast, the pasture-based system had a lower farm C and N emission averaging 0.82 kg CO2-eq kg-1 FPCM and 0.006 kg N kg-1 FPCM, respectively over the 4-year period. The results demonstrate how inputs and outputs could be made compatible and exchangeable across the PB models for quantifying dietary effects on whole-farm GHG and N emissions.

Dietary supplementation of Allium mongolicum modulates rumen-hindgut microbial community structure in Simmental calves

Compared to traditional herbage, functional native herbage is playing more important role in ruminant agriculture through improving digestion, metabolism and health of livestock; however, their effects on rumen microbial communities and hindgut fermentation are still not well understood. The objective of present study was to evaluate the effects of dietary addition of Allium mongolicum on bacterial communities in rumen and feces of claves. Sixteen 7-month-old male calves were randomly divided into four groups (n = 4). All calves were fed a basal ration containing roughage (alfalfa and oats) and mixed concentrate in a ratio of 60:40 on dry matter basis. In each group, the basal ration was supplemented with Allium mongolicum 0 (SL0), 200 (SL200), 400 (SL400), and 800 (SL800) mg/kg BW. The experiment lasted for 58 days. Rumen fluid and feces in rectum were collected, Rumen fluid and hindgut fecal were collected for analyzing bacterial community. In the rumen, Compared with SL0, there was a greater relative abundance of phylum Proteobacteria (p < 0.05) and genera Rikenellaceae_RC9_gut_group (p < 0.01) in SL800 treatment. In hindgut, compared with SL0, supplementation of A. mongolicum (SL200, SL400, or SL800) decreased in the relative abundances of Ruminococcaceae_UCG-014 (p < 0.01), Ruminiclostridium_5 (p < 0.01), Eubacterium_coprostanoligenes_group (p < 0.05), and Alistipes (p < 0.05) in feces; Whereas, the relative abundances of Christensenellaceae_R-7_group (p < 0.05), and Prevotella_1 (p < 0.01) in SL800 were higher in feces, to maintain hindgut stability. This study provided evidence that A. mongolicum affects the gastrointestinal of calves, by influencing microbiota in their rumen and feces.

Relevance of sward structure and forage nutrient contents in explaining methane emissions from grazing beef cattle and sheep

Forage nutrient contents are an important factor explaining the dry matter intake (DMI), average daily gain (ADG), and methane emissions (CH₄) of ruminants fed indoors. However, for grazing animals, the forage nutrient contents might be limited in explaining such response variables. We aimed to verify the explanatory power of forage nutrient contents and sward structure on daily intake, performance, and CH₄ emissions by sheep and beef cattle grazing different grassland types in southern Brazil. We analyzed data from five grazing trials using sheep and beef cattle grazing on Italian ryegrass (Lolium multiflorum), mixed Italian ryegrass and black oat (Lolium multiflorum + Avena strigosa), pearl millet (Pennisetum americanum), and multispecies native grassland. We used mixed models, including the forage nutrient contents [crude protein (CP), neutral detergent fiber (NDF), and acid detergent fiber (ADF)], sward structure (sward height and herbage mass) and their interactions, as fixed effects and trial, season, methodologies, animal species, grassland type, and paddock, as random effects. The model for DMI (kg DM/LW^0.75) had an adjusted coefficient of determination (R²_adj) of 71.6 %, where 11.3, 23.1, and 37.2 % of the R²_adj were explained by the forage nutrient contents, sward structure, and their interaction, respectively. The ADG (kg/LW^0.75) model presented an R²_adj of 74.2 %, with 12.5 % explained by forage nutrient contents, 29.3 % by sward structure, and 32.4 % by their interaction. The daily CH₄ emission (g/LW^0.75) model had a lower adjusted coefficient of determination (R²_adj = 47.6 %), with 16.8 % explained by forage nutrient contents and 30.8 % explained by sward structure, but no effect of the interaction. Our results show that in grazing ecosystems, the forage nutrient contents explain a small fraction, and the greater explanatory power for DMI, ADG, and CH₄ emissions models is related to sward structure descriptors, such as sward height and herbage mass. Moreover, the interaction between these variables explains most of the variation. In conclusion, forage nutrient contents and sward structure have different influences on DMI, ADG, and CH₄ emissions by grazing ruminants. Because of its relevance to daily CH₄ emissions, offering an optimal sward structure to grazing animals is a major climate-smart strategy to improve animal production and mitigate CH₄ emissions in pastoral ecosystems.

Rumen Microbiome Reveals the Differential Response of CO2 and CH4 Emissions of Yaks to Feeding Regimes on the Qinghai-Tibet Plateau

Shifts in feeding regimes are important factors affecting greenhouse gas (GHG) emissions from livestock farming. However, the quantitative values and associated drivers of GHG emissions from yaks (Bos grunniens) following shifts in feeding regimes have yet to be fully described. In this study, we aimed to investigate CH4 and CO2 emissions differences of yaks under different feeding regimes and their potential microbial mechanisms. Using static breathing chamber and Picarro G2508 gas concentration analyzer, we measured the CO2 and CH4 emissions from yaks under traditional grazing (TG) and warm-grazing and cold-indoor feeding (WGCF) regimes. Microbial inventories from the ruminal fluid of the yaks were determined via Illumina 16S rRNA and ITS sequencing. Results showed that implementing the TG regime in yaks decreased their CO2 and CH4 emissions compared to the WGCF regime. The alpha diversity of ruminal archaeal community was higher in the TG regime than in the WGCF regime. The beta diversity showed that significant differences in the rumen microbial composition of the TG regime and the WGCF regime. Changes in the rumen microbiota of the yaks were driven by differences in dietary nutritional parameters. The relative abundances of the phyla Neocallimastigomycota and Euryarchaeota and the functional genera Prevotella, Ruminococcus, Orpinomyces, and Methanobrevibacter were significantly higher in the WGCF regime than in the TG regime. CO2 and CH4 emissions from yaks differed mainly because of the enrichment relationship of functional H2- and CO2-producing microorganisms, hydrogen-consuming microbiota, and hydrogenotrophic methanogenic microbiota. Our results provided a view that it is ecologically important to develop GHG emissions reduction strategies for yaks on the Qinghai-Tibet Plateau based on traditional grazing regime.

Ammonia and greenhouse emissions from cow's excreta are affected by feeding system, stage of lactation and sampling time

Decomposition of dairy cows' excreta on housing floor leads to ammonia and greenhouse gases production, yet factors affecting total emissions have not been fully disclosed. This work aimed to assess the impact of lactation stage, feeding system and sampling time on gaseous emission potential of cow's faeces and urine in laboratory chambers systems. Individual faeces and urine were collected from two groups of four cows, at peak and post peak lactation, from three commercial farms with distinct feeding systems: total mixed ration (TMR), total mixed ration plus concentrate at robot (TMR + robot), and total mixed ration plus concentrate in automatic feeders (TMR + AF). Samples were collected before a.m. (T8h), at middle day (T12h), and before p.m. (T17h) milking. In a laboratory chambers system, faeces and urine were mixed in a ratio of 1.7:1, and ammonia and greenhouse gases emissions were monitored during 48-h. Cumulative N-N₂O emissions were the highest in TMR + robot system, post peak cows and sampling time T17h. An interaction between stage of lactation and sampling time was detected for N-NH₃ and N-N₂O (g/kg organic soluble N) emissions. Post peak cows also produced the highest cumulative N-NH₃ emissions. Overall results contribute for the identification of specific on-farm strategies to reduce gaseous emissions from cows' excreta.

Quantification of methane emitted by ruminants: a review of methods

The contribution of greenhouse gas (GHG) emissions from ruminant production systems varies between countries and between regions within individual countries. The appropriate quantification of GHG emissions, specifically methane (CH4), has raised questions about the correct reporting of GHG inventories and, perhaps more importantly, how best to mitigate CH4 emissions. This review documents existing methods and methodologies to measure and estimate CH4 emissions from ruminant animals and the manure produced therein over various scales and conditions. Measurements of CH4 have frequently been conducted in research settings using classical methodologies developed for bioenergetic purposes, such as gas exchange techniques (respiration chambers, headboxes). While very precise, these techniques are limited to research settings as they are expensive, labor-intensive, and applicable only to a few animals. Head-stalls, such as the GreenFeed system, have been used to measure expired CH4 for individual animals housed alone or in groups in confinement or grazing. This technique requires frequent animal visitation over the diurnal measurement period and an adequate number of collection days. The tracer gas technique can be used to measure CH4 from individual animals housed outdoors, as there is a need to ensure low background concentrations. Micrometeorological techniques (e.g., open-path lasers) can measure CH4 emissions over larger areas and many animals, but limitations exist, including the need to measure over more extended periods. Measurement of CH4 emissions from manure depends on the type of storage, animal housing, CH4 concentration inside and outside the boundaries of the area of interest, and ventilation rate, which is likely the variable that contributes the greatest to measurement uncertainty. For large-scale areas, aircraft, drones, and satellites have been used in association with the tracer flux method, inverse modeling, imagery, and LiDAR (Light Detection and Ranging), but research is lagging in validating these methods. Bottom-up approaches to estimating CH4 emissions rely on empirical or mechanistic modeling to quantify the contribution of individual sources (enteric and manure). In contrast, top-down approaches estimate the amount of CH4 in the atmosphere using spatial and temporal models to account for transportation from an emitter to an observation point. While these two estimation approaches rarely agree, they help identify knowledge gaps and research requirements in practice.