A Review of Enteric Methane Emission Measurement Techniques in Ruminants

The effect of Vachellia eriolaba leaf meal inclusion on growth performance, blood parameters and methane gas emission in lambs fed diets containing ammoniated maize stover

The study evaluated the effect of Vachellia erioloba leaf meal in diets containing ammoniated maize stove on growth performance, methane emission and heath of growing lambs. Thirty-two female lambs were allocated to the following four dietary treatments: total mixed ration (TMR, control), 20% inclusion of untreated maize stover (UMS), 20% inclusion of ammoniated maize stover (AMS), and combined inclusion of 10% ammoniated maize stover and 10% Vachellia erioloba leaves (AMSVL). Each treatment was replicated 8 times and a lamb in an individual pen was regarded as an experimental unit in a completely randomized design. Feed intake was higher (P < 0.05) in lambs fed the AMS and AMSVL diets compared to those fed UMS. Final body weights were higher in lambs fed the AMS and AMSVL diets. Both average daily gain (ADG) and feed convention ratio (FCR) were not affected by diet. In comparison with the AMS and AMSVL diets, the lambs fed the UMS diet had the highest (P < 0.05) methane emission. Overall, lambs fed the control diets had the lowest (P < 0.05) methane gas emission. Blood hematological values were affected by diet with the AMSVL fed lambs having the highest (P < 0.05) mean platelet volume (MPV) and procalcitonin (PCT) values. Furthermore, total albumin, amylase and total bilirubin were the highest (P < 0.05) in lambs fed on the AMSVL diet. Lambs fed on AMS diet had the highest (P < 0.05) serum urea levels. It can be concluded that combined inclusion of ammoniated maize stover and Vachellia leaves improved feed value and lamb performance when compared to the individual inclusion of both UMS and AMS.

Effects of Brown Seaweed (Ascophyllum nodosum) Supplementation on Enteric Methane Emissions, Metabolic Status and Milk Composition in Peak-Lactating Holstein Cows

The dairy industry contributes significantly to anthropogenic methane emissions, which have an impact on global warming. This study aimed to investigate the effects of a dietary inclusion of brown seaweed Ascophyllum nodosum on enteric methane emissions (EMEs), hematological and blood biochemical profiles, and milk composition in dairy cows. Eighteen Holstein cows were divided into three groups: CON (non-supplemented cows), BS50 (50 mL of 10% A. nodosum), and BS100 (100 mL of 10% A. nodosum). In each cow, measurements of EME, dry matter intake (DMI), and milk yield (MY), as well as blood and milk sampling with respective analyzes, were performed before supplementation (P1), after 15 (P2) days, and after 30 (P3) days of supplementation. A. nodosum reduced (p < 0.05) methane production, methane yield, and methane intensity in both BS50 and BS100, and raised DMI (p < 0.05) only in BS50. Total bilirubin (p < 0.05) was higher in BS50 compared to CON cows in P2, and triacylglycerols were lower (p < 0.05) in BS50 than in CON cows in P3. Higher milk fat content was found in BS50 than in CON cows in P3. C16:0 proportions were higher (p < 0.05) in BS50 and BS100 than in CON cows, while C18:3n-3 was higher (p < 0.05) in BS100 than in BS50 and CON cows in P3. Dietary treatment with A. nodosum reduced EMEs and showed the potential to increase DMI and to improve energy status as well as milk composition in peak-lactating dairy cows.

Advances in Methane Emission Estimation in Livestock: A Review of Data Collection Methods, Model Development and the Role of AI Technologies

This review examines the significant role of methane emissions in the livestock industry, with a focus on cattle and their substantial impact on climate change. It highlights the importance of accurate measurement and management techniques for methane, a potent greenhouse gas accounting for 14-16% of global emissions. The study evaluates both conventional and AI-driven methods for detecting methane emissions from livestock, particularly emphasizing cattle contributions, and the need for region-specific formulas. Sections cover livestock methane emissions, the potential of AI technology, data collection issues, methane's significance in carbon credit schemes, and current research and innovation. The review emphasizes the critical role of accurate measurement and estimation methods for effective climate change mitigation and reducing methane emissions from livestock operations. Overall, it provides a comprehensive overview of methane emissions in the livestock industry by synthesizing existing research and literature, aiming to improve knowledge and methods for mitigating climate change. Livestock-generated methane, especially from cattle, is highlighted as a crucial factor in climate change, and the review underscores the importance of integrating precise measurement and estimation techniques for effective mitigation.

Methane Emission and Metabolic Status in Peak Lactating Dairy Cows and Their Assessment Via Methane Concentration Profile

Ruminant husbandry contributes to global methane (CH4) emissions and beside its negative impact on the environment, enteric CH4 emissions cause a loss of gross energy intake in cows. The study is aimed to estimate CH4 emission and metabolic status in dairy cows via the methane concentration profile as a tool for analyzing the CH4 production pattern. The study included eighteen cows whose enteric CH4 emission was measured during three consecutive days in three periods: 2 hours before (P1), 2–4 hours (P2) and 6–8 hours (P3) after the morning feeding. Based on CH4 enteric emissions, cows were divided into two groups (n=6, respectively): HM (average CH4 concentration: 5430.08 ± 365.92 ppm) and LM (average CH4 concentration: 1351.85 ± 205.20 ppm). Following CH4 measurement, on day 3, venous blood was sampled to determine the indicators of the metabolic status. HM cows had significantly higher average CH4 concentrations, maximum and average CH4 peak amplitude than LM cows in all measuring periods (P1-P3), while the number of CH4 peaks tended to be higher in HM than in LM cows in P2. There were no differences in the maximum and average CH4 peak width and average distance among two CH4 peaks between examined groups of cows. HM cows had significantly higher total protein concentrations and significantly lower total bilirubin and NEFA concentrations than LM cows. In conclusion, HM cows have a greater number of eructations and release more CH4 per eructation than LM cows, hence the differences in metabolic status are most likely related to the differences in their liver function.

Feed intake, emission of enteric methane and estimates, feed efficiency, and ingestive behavior in buffaloes supplemented with palm kernel cake in the Amazon biome

The use of palm kernel cake as an alternative to conventional ingredients, due to the presence of residual fat, can also reduce methane emissions. The objective of the study was to evaluate, in two different experiments, the effects of palm kernel cake supplementation on feed intake, enteric methane production and estimates, and the ingestive behavior of buffaloes in the Amazon biome. In experiment 1, to evaluate feed intake, methane production, and feed efficiency, 20 crossbred females, dry and empty, with a mean age of 34 months and an initial body weight of 514 ± 69 kg, were supplemented with palm kernel cake for 60 days. The supply was calculated in relation to body weight (BW) in four treatments: 0% (control); 0.25, 0.50, and 1% of palm kernel cake, distributed in a completely randomized design. In experiment 2, to evaluate the ingestive behavior, 24 mixed-breed, dry, and non-pregnant buffaloes supplemented with palm kernel cake were evaluated in the less rainy season (LR) and the wettest season (WS) of the eastern Amazon, distributed in a completely randomized in the same treatments as experiment 1. The inclusion of palm kernel cake in the supplementation increased the feed intake of dry matter and components (MM, OM, CP, NDF, ADF, and EE) (P < 0.01), reducing the production of enteric methane intake (P < 0.01), the ratio per kg of meat produced (P < 0.01) and feed efficiency (P < 0.01), and influenced the ingestive behavior (time grazing, rumination, and idleness) during the day. We suggest that further research be carried out to verify the results and improve the use of this co-product as a methanogenesis mitigator.

Phenotypic relationship and repeatability of methane emissions and performance traits in beef cattle using a GreenFeed system

Rumen methanogenesis results in the loss of 6% to 10% of gross energy intake in cattle and globally is the single most significant source of anthropogenic methane (CH4) emissions. The purpose of this study was to analyze greenhouse gas traits recorded in a commercial feedlot unit to gain an understanding into the relationships between greenhouse gas traits and production traits. Methane and carbon dioxide (CO2) data recorded via multiple GreenFeed Emission Monitoring (GEM), systems as well as feed intake, live weight, ultrasound scanning data, and slaughter data were available on 1,099 animals destined for beef production, of which 648 were steers, 361 were heifers, and 90 were bulls. Phenotypic relationships between GEM emission measurements with feed intake, weight traits, muscle ultrasound data, and carcass traits were estimated. Utilization of GEM systems, daily patterns of methane output, and repeatability of GEM system measurements across averaging periods were also assessed. Methane concentrations varied with visit number, duration, and time of day of visit to the GEM system. Mean CH4 and CO2 varied between sex, with mean CH4 of 256.1 g/day ± 64.23 for steers, 234.7 g/day ± 59.46 for heifers, and 156.9 g/day ± 55.98 for young bulls. A 10-d average period of GEM system measurements were required for steers and heifers to achieve a minimum repeatability of 0.60; however, higher levels of repeatability were observed in animals that attended the GEM system more frequently. In contrast, CO2 emissions reached repeatability estimates >0.6 for steers and heifers in all averaging periods greater than 2-d, suggesting that cattle have a moderately consistent CO2 emission pattern across time periods. Animals with heavier bodyweights were observed to have higher levels of CH4 (correlation = 0.30) and CO2 production (correlation = 0.61), and when assessing direct methane, higher levels of dry matter intake were associated with higher methane output (correlation = 0.31). Results suggest that reducing CH4 can have a negative impact on growth and body composition of cattle. Methane ratio traits, such as methane yield and intensity were also evaluated, and while easy to understand and compare across populations, ratio traits are undesirable in animal breeding, due to the unpredictable level of response. Methane adjusted for dry matter intake and liveweight (Residual CH4) should be considered as an alternative emission trait when selecting for reduced emissions within breeding goals.

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.

Predicting enteric methane emission in lactating Holsteins based on reference methane data collected by the GreenFeed system

Methane emission is not included in the current breeding goals for dairy cattle mainly due to the expense and difficulty in obtaining sufficient data to generate accurate estimates of the relevant traits. While several models have been developed to predict methane emission from milk spectra using reference methane data obtained by the respiration chamber, SF6 and sniffer methods, the prediction of methane emission from milk mid-infrared (MIR) spectra using reference methane data collected by the GreenFeed system has not yet been explored. Methane emission was monitored for 151 cows using the GreenFeed system. Prediction models were developed for daily and average (for the trial period of 12 or 14 days) methane production (g/d), yield (g/kg DM intake (DMI)) and intensity (g/kg of fat- and protein-corrected milk) using partial least squares regression. The predictions were evaluated in 100 repeated validation cycles, where animals were randomly partitioned into training (80%) and testing (20%) populations for each cycle. The best performing model was observed for average methane intensity using MIR, parity and DMI with validation coefficient of determination (R²_val) and RMSE of prediction of 0.66 and 4.7 g/kg of fat- and protein-corrected milk, respectively. The accuracy of the best models for average methane production and average methane yield were poor (R²_val = 0.28 and 0.12, respectively). A lower accuracy of prediction was observed for methane intensity and production (R²_val = 0.42 and 0.17) when daily records were used while prediction for methane yield was comparable to that for average methane yield (R²_val = 0.16). Our results suggest the potential to predict methane intensity with moderate accuracy. In this case, prediction models for average methane values were generally better than for daily measures when using the GreenFeed system to obtain reference methane emission measurements.

The influence of breath concentration in the gas sample on the accuracy of methane to carbon dioxide ratio using the sniffer method in dairy cows

The purpose of this study was to investigate the carbon dioxide (CO₂ ) concentration in the sampled gas to avoid low concentration of breath while measuring the methane (CH₄ )/CO₂ ratio using the sniffer method. This study also assessed the effect of selective elimination by applying the threshold of CO₂ concentration to the CH₄ /CO₂ ratio. The gas measurement in the automatic milking system was conducted with 26 multiparous Holstein cows using an electric fan to manipulate the CO₂ concentration in the sampled gas. Four different thresholds of the background-corrected CO₂ concentrations (0, 0.025, 0.05, and 0.1%) were applied to every 1-s value of the individual gas measurement. Subsequently, three different upper limits of the proportion of eliminated values (none, 0.5, and 0.33) were applied to the individual records per milking. The results showed that the sampled gas must contain more than 0.1% of the corrected CO₂ concentration to enable accurate calculation of the CH₄ /CO₂ ratio. It is recommended that at least half of the values in the data be larger than the threshold of the corrected CO₂ concentration for unbiased measurement of the CH₄ /CO₂ ratio.

Response to Climate Change: Evaluation of Methane Emissions in Northern Australian Beef Cattle on a High Quality Diet Supplemented with Desmanthus Using Open-Circuit Respiration Chambers and GreenFeed Emission Monitoring Systems

Simple Summary

The beef industry in Northern Australia is characterized by an extensive grazing system in dry tropical rangelands defined by climate change indices of very low rainfall, a prolonged dry season and feeds of low nutritive value. In response, beef cattle need to be more efficient in converting the available drought-tolerant feeds to muscle, in an attempt to minimize greenhouse gas emissions. This study addressed the problem of reducing methane emissions from tropical beef cattle with the goal of decreasing the impact of climate change and greenhouse gas emissions in Northern Australia. The primary objective was to compare the effect of supplementing tropical beef cattle with both good quality lucerne and poor quality hay with increasing levels of different Desmanthus cultivars on in vivo methane emission. The results showed that in tropical beef cattle on high-quality diets, irrespective of cultivar and emission evaluation method, Desmanthus does not reduce methane emissions.

Abstract

The main objective of this study was to compare the effect of supplementing beef cattle with Desmanthus virgatus cv. JCU2, D. bicornutus cv. JCU4, D. leptophyllus cv. JCU7 and lucerne on in vivo methane (CH₄) emissions measured by open-circuit respiration chambers (OC) or the GreenFeed emission monitoring (GEM) system. Experiment 1 employed OC and utilized sixteen yearling Brangus steers fed a basal diet of Rhodes grass (Chloris gayana) hay in four treatments—the three Desmanthus cultivars and lucerne (Medicago sativa) at 30% dry matter intake (DMI). Polyethylene glycol (PEG) was added to the diets to neutralize tannin binding and explore the effect on CH₄ emissions. Experiment 2 employed GEM and utilized forty-eight animals allocated to four treatments including a basal diet of Rhodes grass hay plus the three Desmanthus cultivars in equal proportions at 0%, 15%, 30% and 45% DMI. Lucerne was added to equilibrate crude protein content in all treatments. Experiment 1 showed no difference in CH₄ emissions between the Desmanthus cultivars, between Desmanthus and lucerne or between Desmanthus and the basal diet. Experiment 2 showed an increase in CH₄ emissions in the three levels containing Desmanthus. It is concluded that on high-quality diets, Desmanthus does not reduce CH₄ emissions.

Challenges and opportunities for quantifying greenhouse gas emissions through dairy cattle research in developing countries

The global dairy sector is facing the challenge of reducing greenhouse gas (GHG) emissions whilst increasing productivity to feed a growing population. Despite the importance of this challenge, many developing countries do not have the required resources, specifically funding, expertise and facilities, for quantifying GHG emissions from dairy production and research. This paper aims to address this challenge by discussing the magnitude of the issue, potential mitigation approaches and benefits in quantifying GHG emissions in a developing country context. Further, the paper explores the opportunities for developing country dairy scientists to leverage resources from developed countries, such as using existing relevant GHG emission estimation models. It is clear that further research is required to support developing countries to quantify and understand GHG emissions from dairy production, as it brings significant benefits including helping to identify and implement appropriate mitigation strategies for local production systems, trading carbon credits and achieving the nationally determined contribution obligations of the Paris Agreement.

Measurement of Enteric Methane Emissions by the SF6 Technique Is Not Affected by Ambient Weather Conditions

Simple Summary

Although the SF₆ technique was developed over 25 years ago with the intention that it could be used to measure enteric methane production from ruminants outdoors, no experiments have reported the influence of ambient wind speed, temperature, humidity or rainfall on the accuracy of the technique. Six different cohorts of dairy cows (40 per cohort) were kept outdoors and fed a common diet during spring in 3 consecutive years. Individual cow feed intakes and daily methane productions were measured over 5 consecutive days and an automatic weather station measured air temperature, wind speed, relative humidity and rainfall every 10 min. Regression analyses were used to relate the average daily temperature, wind speed, humidity and rainfall to the average daily dry matter intake, methane production and methane yield of each cohort of cows. It was concluded that the modified SF₆ technique can be used outdoors during a range of weather conditions without a significant effect on the measurement of methane production or methane yield of dairy cows.

Abstract

Despite the fact that the sulphur hexafluoride (SF₆) tracer technique was developed over 25 years ago to measure methane production from grazing and non-housed animals, no studies have specifically investigated whether ambient wind speed, temperature, relative humidity and rainfall influence the accuracy of the method. The aim of this research was to investigate how these weather factors influence the measurement of enteric methane production by the SF₆ technique. Six different cohorts of dairy cows (40 per cohort) were kept outdoors and fed a common diet during spring in 3 consecutive years. Methane production from individual cows was measured daily over the last 5 days of each 32-day period. An automated weather station measured air temperature, wind speed, relative humidity and rainfall every 10 min. Regression analyses were used to relate the average daily wind speed, average daily temperature, average daily relative humidity and total daily rainfall measurements to dry matter intake, average daily methane production and methane yield of each cohort of cows. It was concluded that the modified SF₆ technique can be used outdoors during a range of wind speeds, ambient temperatures, relative humidities and rainfall conditions without causing a significant effect on the measurement of methane production or methane yield of dairy cows.