Global beef cattle methane emissions: yield prediction by cluster and meta-analyses

Abstract

Abstract.Methane yield values (MY; g methane/kg dry-matter intake) in beef cattle reported in the global literature (expanded MitiGate database of methane-mitigation studies) were analysed by cluster and meta-analyses. The Ward and k means cluster analyses included accounting for the categorical effects of methane measurement method, cattle breed type, country or region of study, age and sex of cattle, and proportion of grain in the diet and the standardised continuous variables of number of animals, liveweight and MY. After removal of data from outlier studies, meta-analyses were conducted on subsets of data to produce prediction equations for MY. Removing outliers with absolute studentised residual values of >1, followed by meta-analysis of data accounting for categorical effects, is recommended as a method for predicting MY. The large differences among some countries in MY values were significant but difficult to interpret. On the basis of the datasets available, a single, global MY or percentage of gross energy in feed converted to methane (Y m ) value is not appropriate for use in Intergovernmental Panel on Climate Change (IPCC) greenhouse accounting methods around the world. Therefore, ideally country-specific MY values should be used in each country's accounts (i.e. an IPCC Tier 2 or 3 approach) from data generated within that country.

Methane emissions of extensive grazing breeding herds in relation to the weaning and yearling stages in the Eastern Plains of Colombia

“…To the best knowledge of the authors, the Colombian GHG livestock inventory relies on a standard Intergovernmental Panel on Climate Change [IPCC (2006)] Tier 1 approach that does not consider CH 4 emission factors measured from native or adapted cattle to the local low tropics, but are derived from international temperate scenarios (56 kg CH 4 /head per year). Collectively, our observations are in agreement with the cluster and metaanalysis study of Cottle and Eckard (2018) which noted that for GHG inventory reporting, country-beef specific estimates of daily and yield CH 4 emissions are required from data generated in each country rather than that derived from the standard IPCC GHG account method. As noted by Cottle and Eckard (2018) a number of reasons may contribute to discrepancies between world and local accounting approaches including, but not limited to, the physio-metabolic interactional framework adopted in this paper.…”

The Dietary Supplemental Effect of Nitroethanol in Comparison with Monensin on Methane Emission, Growth Performance and Carcass Characteristics in Female Lambs

“…The reduction in CH 4 production with monensin and NEOH supplementation, which represented less energy loss and increasing energy metabolism, may also improve feed efficiency of female lambs. Due to the requirement of a specialized methodology [ 37 ] and expensive equipment [ 38 ] in determination of CH 4 production for individual ruminants, some empirical models have been developed to estimate specific CH 4 emissions from ruminant animals [ 24 , 39 , 40 ]. Based on DMI, GEI and DEI, specific models for accurate estimation of CH 4 emissions (CH 4 DMI , CH 4 GEI and CH 4 DEI ) from sheep were obtained from Patra et al [ 26 ].…”

Dietary mitigation of enteric methane emissions from ruminants: A review of plant tannin mitigation options

“…This assumes that CH 4 production is constant for all DMI values and there is a 0-intercept in the prediction equation ( Charmley et al., 2016 ). However, Cottle and Eckard (2018) reported that the differences in CH 4 production values from beef cattle studies using different CH 4 -measurement methods, cattle breeds, diets, and geographic location are so diverse that a universal CH 4 production value may not be recommended at this stage. This agrees with our current study which indicated that the 3 different CH 4 -measurement methods (IRC, SF 6 , and GF) may misrepresent the relationship between daily CH 4 production and DMI (g/kg DMI; Fig.…”

“…Animals that consumed a concentrate-based diet had lower CH 4 emissions than those fed a forage-based diet ( Wallace et al., 2014 ; Roehe et al., 2016 ). This variation was due to higher propionic acid production [decrease A:P ratio] from digestible carbohydrates in the rumen, which leads to reduction of H 2 available for typical CH 4 producing pathway ( Beauchemin and McGinn, 2005 ; Cottle and Eckard, 2018 ). Thus, CH 4 reduction strategies that reduce available H 2 may be antagonistic to cellulose digestion ( Wolin et al., 1997 ).…”