Methane emissions from beef and dairy cattle: Quantifying the effect of physiological stage and diet characteristics1

Abstract

The prediction of methane outputs from ruminant livestock data at farm, national, and global scales is a vital part of greenhouse gas calculations. The objectives of this work were to quantify the effect of physiological stage (lactating or nonlactating) on predicting methane (CH4) outputs and to illustrate the potential improvement for a beef farming system of using more specific mathematical models to predict CH4 from cattle at different physiological stages and fed different diet types. A meta-analysis was performed on 211 treatment means from 38 studies where CH4, intake, animal, and feed characteristics had been recorded. Additional information such as type of enterprise, diet type, physiological stage, CH4 measurement technique, intake restriction, and CH4 reduction treatment application from these studies were used as classificatory factors. A series of equations for different physiological stages and diet types based on DMI or GE intake explained 96% of the variation in observed CH4 outputs (P<0.001). Resulting models were validated with an independent dataset of 172 treatment means from 20 studies. To illustrate the scale of improvement on predicted CH4 outputs from the current whole-farm prediction approach (Intergovernmental Panel on Climate Change [IPCC]), equations developed in the present study (NewEqs) were compared with the IPCC equation {CH4 (g/d)=[(GEI×Ym)×1,000]/55.65}, in which GEI is GE intake and Ym is the CH4 emission factor, in calculating CH4 outputs from 4 diverse beef systems. Observed BW and BW change data from cows with calves at side grazing either hill or lowland grassland, cows and overwintering calves and finishing steers fed contrasting diets were used to predict energy requirements, intake, and CH4 outputs. Compared with using this IPCC equation, NewEqs predicted up to 26% lower CH4 on average from individual lactating grazing cows. At the herd level, differences between equation estimates from 10 to 17% were observed in total annual accumulated CH4 when applied to the 4 diverse beef production systems. Overall, despite the small number of animals used it was demonstrated that there is a biological impact of using more specific CH4 prediction equations. Based on this approach, farm and national carbon budgets will be more accurate, contributing to reduced uncertainty in assessing mitigation options at farm and national level.

An evaluation of the accuracy and precision of methane prediction equations for beef cattle fed high-forage and high-grain diets

“…Data used to develop the extant equations were included in the database, but to avoid bias due to the same data being used between studies to develop a particular equation, common data were excluded from the evaluation of that equation. This comprised 9.2% of the records for Ellis et al (2007) and 17.8% for Ricci et al (2013). Data used by Ellis et al (2009), Yan et al (2009, Ricci et al (2013) were from local experiments that were not published in peer-reviewed literature.…”

“…This comprised 9.2% of the records for Ellis et al (2007) and 17.8% for Ricci et al (2013). Data used by Ellis et al (2009), Yan et al (2009, Ricci et al (2013) were from local experiments that were not published in peer-reviewed literature.…”

“…Yan et al (2009) equations are based on contents of energy and DMI. Ricci et al (2013) equations consider GEI (MJ/day) and DMI (kg/kg DM), as well as feed type (1 or 0 according to level of concentrate > or ⩽500 g/kg DM diet) and state variables (0 = non-lactating cows; 1 = lactating cows). Moraes et al (2014) presented separate equations for heifers (H) and steers (S) with hierarchical levels based on GEI (gross energy level (GEL), MJ/day), dietary level (DL), which included GEI (MJ/day) and NDF (g/kg DM), and animal level (AL) based on BW (kg), GEI (MJ/day) and NDF (g/kg DM).…”

“…Moraes et al (2014) did not report the range of dietary forage used to develop their equations, therefore the range of NDF proportion of the diets was used instead. Conditional arguments were used to determine appropriate variable values in the Ricci et al (2013) and Moraes et al (2014) equations that consider categorical variables.…”

“…Various prediction equations have been developed specifically for beef cattle (e.g. Ellis et al, 2009;Ricci et al, 2013;Moraes et al, 2014), but the accuracy of these equations over a range of diet compositions has not been determined using an independent data set.…”