Evaluation of methane prediction equations for Australian feedlot cattle fed barley and wheat-based diets

Abstract

Context. Accurately predicting baseline methane (CH4) emissions from beef cattle is of utmost importance for the beef industry and governments alike. It serves as a vital component for accounting as part of national GHG inventories and enables the development and implementation of greenhouse gas (GHG) mitigation strategies.

Aims. The aim of this study was to evaluate equations in the literature for predicting CH4 emissions of beef cattle when fed barley and wheat-based diets typical of the Australian feedlot industry. Then, propose the best prediction equation to accurately reflect CH4 emissions of feedlot cattle under Australian conditions.

Methods. As part of the project, a large database of methane measurements performed in respiratory calorimeters taken from beef cattle fed a range of feedlot diets was assembled. The dataset included a wide range of factors that are known to impact CH4 production, such as dry matter intake (DMI), ether extract (EE), crude protein (CP), and cell wall components, amongst others. The database contained 713 individual measurements, from 175 animals and 12 studies.

Key results. The equation currently utilised by the Australian National Inventory Report had poor accuracy, with mean bias overprediction of 115 g/day (P < 0.01), along with significant linear bias (P < 0.01) and poor precision (r2 = 0.05). The mean bias was 144% of average observed CH4 production. All evaluated equations lacked accuracy and precision in predicting CH4 emissions for the diets fed in this study. Roughage concentrations (DM basis) ranged from 5.54 to 43.0% with a mean of 20.5 ± 11.1%. Given these findings, two specific equations were developed, (1) a CH4 yield equation based on DMI: CH4 (g/day) = 9.89 ± 1.54 × DMI (n = 384; P < 0.01; root mean square error (RMSE) = 32.6 g/day; r2 = 0.85); and (2) an equation based on DMI, neutral detergent fibre (NDF) and EE: CH4 (g/day) = 5.11 ± 1.58 × DMI − 4.00 ± 0.821 × EE + 2.26 ± 0.125 × NDF (n = 384; P < 0.05; RMSE = 22.2 g/day; r2 = 0.91). When validated, the second equation yielded a mean bias of 6.10 g overprediction, with no linear bias, and better fit than any of the literature equations.

Conclusions. Based on a thorough model evaluation, our findings support the need to revise current methods to predict CH4 for barley and wheat-based diets.

Implications. This study contributes to developing accurate estimations of enteric CH4 emissions for cattle fed barley and wheat-based diets.