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.     

Implications of dairy systems on enteric methane and postulated effects on total greenhouse gas emission

The effects of feeding total mixed ration (TMR) or pasture forage from a perennial sward under a management intensive grazing (MIG) regimen on grain intake and enteric methane (EM) emission were measured using chambers. Chamber measurement of EM was compared with that of SF₆ employed both within chamber and when cows grazed in the field. The impacts of the diet on farm gate greenhouse gas (GHG) emission were also postulated using the results of existing life cycle assessments. Emission of EM was measured in gas collection chambers in Spring and Fall. In Spring, pasture forage fiber quality was higher than that of the silage used in the TMR (47.5% v. 56.3% NDF; 24.3% v. 37.9% ADF). Higher forage quality from MIG subsequently resulted in 25% less grain use relative to TMR (0.24 v. 0.32 kg dry matter/kg milk) for MIG compared with TMR. The Fall forage fiber quality was still better, but the higher quality of MIG pasture was not as pronounced as that in Spring. Neither yield of fat-corrected milk (FCM) which averaged 28.3 kg/day, nor EM emission which averaged 18.9 g/kg dry matter intake (DMI) were significantly affected by diet in Spring. However, in the Fall, FCM from MIG (21.3 kg/day) was significantly lower than that from TMR (23.4 kg/day). Despite the differences in FCM yield, in terms of EM emission that averaged 21.9 g/kg DMI was not significantly different between the diets. In this study, grain requirement, but not EM, was a distinguishing feature of pasture and confinement systems. Considering the increased predicted GHG emissions arising from the production and use of grain needed to boost milk yield in confinement systems, EM intensity alone is a poor predictor of the potential impact of a dairy system on climate forcing.     

Evaluation of enteric methane prediction equations for dairy cows used in whole farm models

The importance of evaluating greenhouse gas (GHG) emissions from dairy cows within the whole farm setting is being realized as more important than evaluating these emissions in isolation. Current whole farm models aimed at evaluating GHG emissions make use of simple regression equations to predict enteric methane (CH₄) production. The objective of the current paper is to evaluate the performance of nine CH₄ prediction equations that are currently being used in whole farm GHG models. Data used to evaluate the prediction equations came from a collection of individual (IND) and treatment averaged (TRT) data. Equations were compared based on mean square prediction error (MSPE) and concordance correlation coefficient (CCC) analysis. In general, predictions were poor, with root MSPE (as a percentage of observed mean) values ranging from 20.2 to 52.5 for the IND database and from 24.0 to 38.2 for the TRT database and CCC values ranging from 0.009 to 0.493 for the IND database and from 0.000 to 0.271 for the TRT database. Overall, the equations of Moe & Tyrrell and IPCC Tier II performed best on the IND dataset, and the equations of Moe & Tyrrell and Kirchgeßner et al., performed best on the TRT dataset. Results show that the simple more generalized equations performed worse than those that attempted to represent important aspects of diet composition, but in general significant amounts of bias and deviation of the regression slope from unity existed for all equations. The low prediction accuracy of CH₄ equations in whole farm models may introduce substantial error into inventories of GHG emissions and lead to incorrect mitigation recommendations.     

Herd-level versus animal-level variation in methane emission prediction in grazing dairy cattle

In response to the increased concern over agriculture’s contribution to greenhouse gas (GHG) emissions, more detailed assessments of current methane emissions and their variation, within and across individual dairy farms and cattle, are of interest for research and policy development. This assessment will provide insights into possible changes needed to reduce GHG emissions, the nature and direction of these changes, ways to influence farmer behavior and areas to maximize the adoption of emerging mitigation technologies. The objectives of this study were to (1) quantify the variation in enteric fermentation methane emissions within and among seasonal calving dairy farms with the majority of nutritional requirements met through grazed pasture; (2) use this variation to assess the potential of new individual animal emission monitoring technologies and their impact on mitigation policy. We used a large database of cow performance records for milk production and survival from 2 398 herds in New Zealand, and simulation to account for unobserved variation in feed efficiency and methane emissions per unit of feed. Results showed an average of 120 ± 31.4 kg predicted methane (CH₄) per cow per year after accounting for replacement costs, ranging 8.9–323 kg CH₄/cow per year. Whereas milk production, survival and predicted live weight were reasonably effective at predicting both individual and herd average levels of per cow feed intake, substantial within animal variation in emissions per unit of feed reduced the ability of these variables to predict variation in per animal methane output. Animal-level measurement technologies predicting only feed intake but not emissions per unit of feed are unlikely to be effective for advancing national policy goals of reducing dairy farming enteric methane output. This is because farmers seek to profitably utilize all farm feed resources available, so improvements in feed efficiency will not result in the reduction in feed utilization required to reduce methane emissions. At a herd level, average per cow milk production and live weight could form the basis of assigning a farm-level point of obligation for methane emissions. In conclusion, a comprehensive national database infrastructure that was tightly linked to animal identification and movement systems, and captured live weight data from existing farm-level recording systems, would be required to make this effective. Additional policy and incentivization mechanisms would still be required to encourage farmer uptake of mitigation interventions, such as novel feed supplements or vaccines that reduce methane emissions per unit of feed.     

Prediction of enteric methane emissions from cattle

Agriculture has a key role in food production worldwide and it is a major component of the gross domestic product of several countries. Livestock production is essential for the generation of high quality protein foods and the delivery of foods in regions where animal products are the main food source. Environmental impacts of livestock production have been examined for decades, but recently emission of methane from enteric fermentation has been targeted as a substantial greenhouse gas source. The quantification of methane emissions from livestock on a global scale relies on prediction models because measurements require specialized equipment and may be expensive. The predictive ability of current methane emission models remains poor. Moreover, the availability of information on livestock production systems has increased substantially over the years enabling the development of more detailed methane prediction models. In this study, we have developed and evaluated prediction models based on a large database of enteric methane emissions from North American dairy and beef cattle. Most probable models of various complexity levels were identified using a Bayesian model selection procedure and were fitted under a hierarchical setting. Energy intake, dietary fiber and lipid proportions, animal body weight and milk fat proportion were identified as key explanatory variables for predicting emissions. Models here developed substantially outperformed models currently used in national greenhouse gas inventories. Additionally, estimates of repeatability of methane emissions were lower than the ones from the literature and multicollinearity diagnostics suggested that prediction models are stable. In this context, we propose various enteric methane prediction models which require different levels of information availability and can be readily implemented in national greenhouse gas inventories of different complexity levels. The utilization of such models may reduce errors associated with prediction of methane and allow a better examination and representation of policies regulating emissions from cattle.     

Development of methane emission factors for enteric fermentation in cattle from Benin using IPCC Tier 2 methodology

The objective of this study was to develop emission factors (EF) for methane (CH₄) emissions from enteric fermentation in cattle native to Benin. Information on livestock characteristics and diet practices specific to the Benin cattle population were gathered from a variety of sources and used to estimate EF according to Tier 2 methodology of the 2006 Intergovernmental Panel on Climate Change (IPCC) Guidelines for National Greenhouse Gas Inventories. Most cattle from Benin are Bos taurus represented by Borgou, Somba and Lagune breeds. They are mainly multi-purpose, being used for production of meat, milk, hides and draft power and grazed in open pastures and crop lands comprising tropical forages and crops. Estimated enteric CH₄ EFs varied among cattle breeds and subcategory owing to differences in proportions of gross energy intake expended to meet maintenance, production and activity. EFs ranged from 15.0 to 43.6, 16.9 to 46.3 and 24.7 to 64.9 kg CH₄/head per year for subcategories of Lagune, Somba and Borgou cattle, respectively. Average EFs for cattle breeds were 24.8, 29.5 and 40.2 kg CH₄/head per year for Lagune, Somba and Borgou cattle, respectively. The national EF for cattle from Benin was 39.5 kg CH₄/head per year. This estimated EF was 27.4% higher than the default EF suggested by IPCC for African cattle with the exception of dairy cattle. The outcome of the study underscores the importance of obtaining country-specific EF to estimate global enteric CH₄ emissions.     

Long-term effect of linseed plus nitrate fed to dairy cows on enteric methane emission and nitrate and nitrite residuals in milk

A previous study showed the additive methane (CH₄)-mitigating effect of nitrate and linseed fed to non-lactating cows. Before practical application, the use of this new strategy in dairy cows requires further investigation in terms of persistency of methanogenesis reduction and absence of residuals in milk products. The objective of this experiment was to study the long-term effect of linseed plus nitrate on enteric CH₄ emission and performance in dairy cows. We also assessed the effect of this feeding strategy on the presence of nitrate residuals in milk products, total tract digestibility, nitrogen (N) balance and rumen fermentation. A total of 16 lactating Holstein cows were allocated to two groups in a randomised design conducted in parallel for 17 weeks. Diets were on a dry matter (DM) basis: (1) control (54% maize silage, 6% hay and 40% concentrate; CON) or (2) control plus 3.5% added fat from linseed and 1.8% nitrate (LIN+NIT). Diets were equivalent in terms of CP (16%), starch (28%) and NDF (33%), and were offered twice daily. Cows were fed ad libitum, except during weeks 5, 16 and 17 in which feed was restricted to 95% of dry matter intake (DMI) to ensure complete consumption of meals during measurement periods. Milk production and DMI were measured weekly. Nitrate and nitrite concentrations in milk and milk products were determined monthly. Daily CH₄ emission was quantified in open circuit respiration chambers (weeks 5 and 16). Total tract apparent digestibility, N balance and rumen fermentation parameters were determined in week 17. Daily DMI tended to be lower with LIN+NIT from week 4 to 16 (−5.1 kg/day on average). The LIN+NIT diet decreased milk production during 6 non-consecutive weeks (−2.5 kg/day on average). Nitrate or nitrite residuals were not detected in milk and associated products. The LIN+NIT diet reduced CH₄ emission to a similar extent at the beginning and end of the trial (−47%, g/day; −30%, g/kg DMI; −33%, g/kg fat- and protein-corrected milk, on average). Diets did not affect N efficiency and nutrients digestibility. In the rumen, LIN+NIT did not affect protozoa number but reduced total volatile fatty acid (−12%) and propionate (−31%) concentrations. We concluded that linseed plus nitrate may have a long-term CH₄-mitigating effect in dairy cows and that consuming milk products from cows fed nitrate may be safe in terms of nitrate and nitrite residuals. Further work is required to optimise the doses of linseed plus nitrate to avoid reduced cows performance.     

微生态制剂与反刍动物甲烷减排

反刍动物瘤胃中产甲烷菌可以利用氢气、甲醇和甲胺等物质生成甲烷,不仅造成饲料能量的浪费,同时甲烷作为一种主要的温室气体也对环境构成了严重的威胁。因此,众多学者都在寻找降低反刍动物甲烷排放的方法,其中有学者提出在饲粮中添加适量可直接饲喂的微生物(Direct-fed microbes,DFM)是一种很有潜力的方法,但目前还处于初步探索阶段。本文综述了几种重要的DFM,并介绍了其作用机制及应用效果。     

Terrestrial plant methane production and emission

In this minireview, we evaluate all experimental work published on the phenomenon of aerobic methane (CH(4) ) generation in terrestrial plants and plant. Clearly, despite much uncertainty and skepticism, we conclude that the phenomenon is true. Four stimulating factors have been observed to induce aerobic plant CH(4) production, i.e. cutting injuries, increasing temperature, ultraviolet radiation and reactive oxygen species. Further, we analyze rates of measured emission of aerobically produced CH(4) in pectin and in plant tissues from different studies and argue that pectin is very far from the sole contributing precursor. In consequence, scaling up of aerobic CH(4) emission needs to take into consideration other potential sources than pectin. Due to the large uncertainties related to effects of stimulating factors, genotypic responses and type of precursors, we conclude that current attempts for upscaling aerobic CH(4) into a global budget is inadequate. Thus it is too early to draw the line under the aerobic methane emission in plants. Future work is needed for establishing the relative contribution of several proven potential CH(4) precursors in plant material.     

东北黑土地区稻田甲烷排放时空演变及排放潜力分析

稻田甲烷排放是农业源甲烷排放的主要来源。东北黑土地区是我国最大的粮食生产基地,农业温室气体减排是实现黑土地永续利用的关键议题之一。运用稻田甲烷排放模型(CH4MOD)核算并分析了2009-2018年东北黑土地区稻田甲烷排放的时空演变特征,结合GOSAT卫星遥感数据探究了水稻生产与区域甲烷排放的时空动态联系,进一步量化了稻田甲烷对区域甲烷排放的贡献程度及不同情景下的排放潜力。结果表明,受水稻生产面积扩张和排放强度提高的影响,东北黑土地区稻田甲烷排放总量从2009年的39.05万t增加到2018年的79.53万t。东北黑土地区区域甲烷排放在季节变化和栅格单元上表现出与稻田甲烷排放较为一致的时空动态,大规模的稻田耕作可能会增加水稻生产与区域甲烷排放直接相关的可能性。随着水稻持续扩种稳产,2018年东北黑土地区水稻生产贡献了区域甲烷排放总量的15.04%,其中黑龙江省的贡献率高达31.06%。在基准发展情景下,预计2035年东北黑土地区稻田CH₄排放量较2018年增加19.5%;在粮食供给保障情景下,维持当前稻田耕作面积,水稻生产集约化程度提高,预计其稻田CH₄排放量较2018年减少0.88%;在此基础上,采取促进秸秆还田、增施有机肥、实施节水间歇灌溉等稻田管理措施将使稻田CH₄排放量增加17.8%-63.6%。以满足膳食需求和供给保障为导向,优化水稻种植结构、控制稻田耕作面积,推动技术进步、品种改良以提升单产水平,采取化肥和有机肥搭配施用、节水间歇灌溉等途径能够缓解稻田甲烷排放。研究综合运用自上而下的遥感数据和自下而上的模型运算,刻画了水稻生产与区域甲烷排放的时空联系,进一步评估了稻田甲烷的排放潜力及减排措施的减排效果,为促进东北黑土地区农业甲烷减排和生产布局优化提供了理论依据和决策参考。     

Role of rice in mediating methane emission

Methane emitted at different plant conditions through the different organs of rice plants was studied using a closed chamber technique under the laboratory, phytotron, and greenhouse conditions in order to clarify and quantify the role of different organs of rice plant as methane emission sites. Rice plants grown in flooded soils emit methane to the atmosphere via the aerenchyma of leaves, nodes and panicles. Emission through the rice plants is controlled by diffusion. No methane is emitted via the transpiration stream. Leaves are the major release sites at the early growth stage while nodes become more important later. Cracks and porous structure were found in the nodes. Panicles generally contribute little to methane emission. Increasing water depth temporarily reduces methane emission while concentration gradients in rice plants readjust to unsubmerged emission sites. Methane emissions in rice plants cease only when the plants become totally submerged.     

湿地甲烷排放研究若干问题的探讨

甲烷是大气中最重要的温室气体之一,天然湿地是全球目前已知的最大排放源,每年向大气中排放的CH4约占全球CH4排放量的21％。本文就天然湿地甲烷排放研究的若干问题,包括研究方法、影响因素以及排放通量的时空变异性进行了探讨,最后对有关湿地甲烷排放模型进行了简单介绍,并对今后的研究方向提出了几点建议。     

Mode of action of Saccharomyces cerevisiae in enteric methane mitigation in pigs

The objectives of this study were to determine the effect and mode of action of Saccharomyces cerevisiae (YST2) on enteric methane (CH₄) mitigation in pigs. A total of 12 Duroc×Landrace×Yorkshire male finisher pigs (60±1 kg), housed individually in open-circuit respiration chambers, were randomly assigned to two dietary groups: a basal diet (control); and a basal diet supplemented with 3 g/YST2 (1.8×10¹⁰ live cells/g) per kg diet. At the end of 32-day experiment, pigs were sacrificed and redox potential (Eh), pH, volatile fatty acid concentration, densities of methanogens and acetogens, and expression of methyl coenzyme-M reductase subunit A gene were determined in digesta contents from the cecum, colon and rectum. Results showed that S. cerevisiae YST2 decreased (P<0.05) the average daily enteric CH₄ production by 25.3%, lowered the pH value from 6.99 to 6.69 in the rectum, and increased the Eh value in cecum and colon by up to −55 mV (P<0.05). Fermentation patterns were also altered by supplementation of YST2 as reflected by the lower acetate, and higher propionate molar proportion in the cecum and colon (P<0.05), resulting in lower acetate : propionate ratio (P<0.05). Moreover, there was a 61% decrease in Methanobrevibacter species in the upper colon (P<0.05) and a 19% increase in the acetogen community in the cecum (P<0.05) of treated pigs. Results of our study concluded that supplementation of S. cerevisiae YST2 at 3 g/kg substantially decreased enteric CH₄ production in pigs.     

Variation in enteric methane emissions among cows on commercial dairy farms

Methane (CH₄) emissions by dairy cows vary with feed intake and diet composition. Even when fed on the same diet at the same intake, however, variation between cows in CH₄ emissions can be substantial. The extent of variation in CH₄ emissions among dairy cows on commercial farms is unknown, but developments in methodology now permit quantification of CH₄ emissions by individual cows under commercial conditions. The aim of this research was to assess variation among cows in emissions of eructed CH₄ during milking on commercial dairy farms. Enteric CH₄ emissions from 1964 individual cows across 21 farms were measured for at least 7 days/cow using CH₄ analysers at robotic milking stations. Cows were predominantly of Holstein Friesian breed and remained on the same feeding systems during sampling. Effects of explanatory variables on average CH₄ emissions per individual cow were assessed by fitting a linear mixed model. Significant effects were found for week of lactation, daily milk yield and farm. The effect of milk yield on CH₄ emissions varied among farms. Considerable variation in CH₄ emissions was observed among cows after adjusting for fixed and random effects, with the CV ranging from 22% to 67% within farms. This study confirms that enteric CH₄ emissions vary among cows on commercial farms, suggesting that there is considerable scope for selecting individual cows and management systems with reduced emissions.     

Plant-mediated methane emission from an Indian mangrove

Mangroves have been considered for a long time to be a minor methane source, but recent reports have shown that polluted mangroves may emit substantial amounts of methane. In an unpolluted Indian mangrove, we measured annual methane emission rates of 10 g CH₄ yr^?1 from the stands of Avicennia marina. This rate is of the same order of magnitude as rates from Northern wetlands. Methane emission from a freshwater‐influenced area was higher, but was lower from a stunted mangrove growing on a hypersaline soil. Methane emission was mediated by the pneumatophores of Avicennia. This was consistent with the methane concentration in the aerenchyma, which decreased on average from 350 ppm_v in the cable roots to 10 ppm_v in the emergent part of the pneumatophores. However, the number of pneumatophores varied seasonally. The minimum number occurred during the monsoon season, which reduced methane emissions largely. Ebullition from unvegetated areas may also be important, at least during monsoon season when measured bubble fluxes were occasionally about five times as high as pneumatophore‐mediated emissions.     

Measurement of methane emission from sheep by the sulphur hexafluoride tracer technique and by the calorimetric chamber: failure and success

The aim of this study was to evaluate the sulphur hexafluoride (SF6) tracer technique for methane (CH4) emission measurement in sheep. Ten cryptorchid Romney sheep were involved in two indoor trials (T1 and T2), where daily CH4 emissions were individually measured both by the SF6 tracer ('tracer CH4') and by the indirect calorimetry chamber ('chamber CH4') techniques while fed on lucerne hay at 1.2 times maintenance requirements. Separate sets of permeation tubes with pre-calibrated permeation rates ('pre-calibrated PRs') were used in the two trials (for tracer CH4) and at the time of T1 and T2 these tubes had been deployed in the rumen for 250 and 30 days, respectively. The tracer CH4 measurements were carried out for 2 (T1) and 5 (T2) days in digestibility crates housed within a building (T1) or a well-ventilated covered yard (T2). Sheep were transferred to calorimetry chambers for 3 days acclimatisation, followed by measurement of CH4 emission for 7 (T1) and 3 (T2) days. In T1 samples from the chamber, outflow and inflow (collected over ～22 h) were analysed for CH4 and SF6 concentrations using the tracer protocol. Thus, PRs of SF6 at the time of the trials ('calculated PRs') could be inferred and the corresponding CH4 emissions are then calculated using either the pre-calibrated PR or calculated PR. Permeation tubes were recovered at the end of the animal trials and their 'post-recovery PR' determined. In trial T1, the tracer CH4 estimates (based on the pre-calibrated PR) were much higher and more variable than the chamber CH4 values. In this trial, the calculated PR and the post-recovery PR were similar from each other but smaller than the pre-calibrated PR, and when the calculated PR was used in place of the pre-calibrated PR the CH4 emission estimates agreed well with the chamber CH4 values. This suggested that the discrepancy was due to a declining PR during the long deployment time of the tubes in T1, an observation reported elsewhere. When the long intra-ruminal deployment was avoided in T2, good agreement between the techniques for CH4 emission measurement was observed.     

Production, oxidation and emission of methane in rice paddies

Abstract Production and emission of methane from submerged paddy soil was studied in laboratory rice cultures and in Italian paddy fields. Up to 80% of the CH₄ produced in the paddy soil did not reach the atmosphere but was apparently oxidized in the rhizosphere. CH₄ emission through the rice plants was inhibited by an atmosphere of pure O₂ but was stimulated by an atmosphere of pure N₂ or an atmosphere containing 5% acetylene. Gas bubbles taken from the submerged soil contained up to 60% CH₄, but only < 1% CH₄ after the bubbles had passed the soil-water interface or had entered the intercellular gas space system of the rice plants. CH₄ oxidation activities were detected in the oxic surface layer of the submerged paddy soil. Flooding the paddy soil with water containing > 0.15% sea salt (0.01% sulfate) resulted in a strong inhibition of the rates of methanogenesis and a decrease in the rates of CH₄ emission. This result explains the observation of relatively low CH₄ emission rates in rice paddy areas flooded with brackish water.     

植物在CH4产生、氧化和排放中的作用

综合评述了植物对CH4产生、内源CH4氧化和CH4排放的影响．不同植物释放根系分泌物能力的不同是造成CH4产生量差异的主要原因。而植物不同生育期分泌分泌物能力的差异是造成季节性变化的关键．植物泌O2能力的高低和季节性变化通过影响内源CH4的氧化来改变CH4的排放数量．植物问通气组织数量和密度的差异及其随生育期的变化,通过影响对CH4的传输能力来改变CH4的排放量．因此,植物排放CH4的通量及其季节性变化规律是由植物根系分泌分泌物能力、分泌O2能力和传输CH4能力综合决定的．     

Net protein contribution and enteric methane production of pasture and grain-finished beef cattle supply chains

Ruminant red meat production systems around the world often include a grain feeding phase. The role of red meat in the food system is therefore often discussed in terms of the food vs feed debate, as well as invoking the comparatively poor feed conversion efficiency of ruminants and climate impacts from enteric methane. The concept of net protein contribution (NPC) incorporates the quality attributes of protein produced by livestock systems into estimates of the efficiency of production systems. We applied the NPC method to two Australian beef supply chains, i) Grass-fed and ii) Grain-finished beef, using an established model of ruminant grazing systems (GrassGro®) and these are reflective of beef production systems in other countries. The beef supply chains evaluated did not compete with humans for protein. The Grain-finished beef supply chain, while positively contributing to human protein requirements (NPC value 1.96), had markedly lower NPC values than the Grass-fed system (NPC value 1 597). However, Grass-fed beef production systems have a higher methane intensity than the Grain-finished supply chain. The two examples of pasture-based beef production systems examined provide a positive net protein contribution to human food supply, even with extended periods of finishing on grain-based diets. This is achieved by ruminant grazing on pastures converting low-quality forage into high value human edible protein. The efficiency of protein production varies according to the system design, and other considerations such as land use and enteric methane production are elements that need consideration in the overall assessment of the production footprint.