Description and evaluation of the AusBeef model of beef production

Abstract

As demand for animal products such as meat and milk increases, and concern over environmental impact grows, mechanistic models can be useful tools to better represent and understand ruminant systems and evaluate mitigation options to reduce greenhouse gas emissions without compromising productivity. AusBeef is a whole-animal, dynamic, mechanistic model of beef production that calculates methane emissions from net ruminal hydrogen balance. AusBeef incorporates a unique fermentation stoichiometry that represents four different microbial groups, as well as the effects of ruminal pH on microbial degradation of feed. The objectives of this study were to evaluate the performance of the AusBeef model of beef production with regard to predicting daily methane production (DMP, g/d), dry matter intake (DMI, kg/d), gross energy intake (GEI, MJ/d) and methane yield (MY, %GEI), using independent data derived from the literature. AusBeef predictions were compared for the full dataset (n=37) as well as for high-forage diets (n=21) and mixed diets (n=16) using a root mean square predicted error expressed as a percentage of the observed mean (RMSPE%). AusBeef predicted DMP with RMSPE% of 26.6, 30.1, and 21.3% for the full dataset, high-forage, and mixed diets, respectively. AusBeef predicted MY, DMI, and GEI with a RMSPE% of 38.5, 8.91, and 9.86% for the full dataset, respectively. There were prediction differences between forage and mixed diets with a RMSPE% of 9.32 and 8.43% for DMI; 6.38 and 11.1% for GEI and 41.7 and 28.4% for MY. AusBeef prediction errors for DMI ranged from -18 to +42%, with AusBeef underpredicting DMI 76% of the time. AusBeef underpredicted methane emissions 65% of the time, with prediction error ranging from - 51 to +59%, and underpredicted GEI 90% of the time, with prediction error ranging from -1 to +30%. Further studies are required to improve the prediction of methane on forage only diets.