Prediction of methane emission from beef cattle using data measured in indirect open-circuit respiration calorimeters.

The objectives of the present study were to examine relationships between methane (CH4) output and animal and dietary factors, and to use these relationships to develop prediction equations for CH4 emission from beef cattle. The dataset was obtained from 108 growing-to-finishing beef steers in five studies and CH4 production and energy metabolism data were measured in indirect respiration calorimeter chambers. Dietary forage proportion ranged from 29.5% to 100% (dry matter (DM) basis) and forages included grass silage, fresh grass, dried grass and fodder beet. Linear and multiple regression techniques were used to examine relationships between CH4 emission and animal and dietary variables, with the effects of experiment or forage type removed. Total CH4 emission was positively related to live weight (LW), feeding level and intake of feed (DM and organic matter) and energy (gross energy (GE), digestible energy (DE) and metabolisable energy (ME)) (P < 0.001), while CH4/DM intake (DMI) was negatively related to energy digestibility and ME/GE (P < 0.05 or less). Using LW alone to predict CH4 emission produced a poor relationship when compared to DMI and GE intake (GEI) (R2 = 0.26 v. 0.68 and 0.70 respectively). Adding feeding level, dietary NDF concentration and CP/ME or feeding level, energy digestibility and ME/GE to support LW resulted in a R2 of 0.66 or 0.84. The high R2 (0.84) was similar to that obtained using DMI or GEI together with energy digestibility and ME/GE as predictors. Further inclusion of dietary forage proportion and ADF and NDF concentration to the multiple relationships using GEI as the primary predictor resulted in a R2 of 0.87. These equations were evaluated through internal validation, by developing a range of similar new equations from two-thirds of the present data and then validating these new equations with the remaining one-third of data. The validation indicated that addition of energy digestibility and ME/GE to support LW with feeding level, DMI and GEI considerably increased the prediction accuracy. It is concluded that CH4 emission of beef steers can be accurately predicted from LW plus feeding level, DMI or GEI together with energy digestibility and ME/GE. The dataset was also used to validate a range of prediction equations for CH4 production of cattle published elsewhere.