Evaluation of a sheep rumen model with fresh forages of diverse chemical composition

The sheep rumen sub-model MollyRum14 (Vetharaniam et al. 2015; J Anim Sci 10.2527/jas.2015-9037) was evaluated on its methane and VFA predictions against data from respiration-chamber trials conducted with sheep fed perennial ryegrass, white clover, chicory, forage rape, turnip (leafy and bulb varieties), swede, kale or forage radish. We assessed the model’s sensitivity to substrate degradation rate (settings that affect the rate of cellulose and hemicellulose digestion) and to fermentation stoichiometry (settings that alter non-glucogenic to glucogenic volatile fatty acids ratios). Model predictions were evaluated against data for methane production (pCH4: g/d), methane yield (yCH4: g/kg DMI), and acetate to propionate ratio (A:P). The predictive ability of the model for both pCH4 and yCH4 was superior for perennial ryegrass than for other forages. Except for swede and chicory, predictions for yCH4 were correctly ranked across the forages evaluated. Except for forage rape and swedes, robust predictions were obtained for all forages using fast degradation kinetics and a predominantly acetogenic stoichiometry. Model predictions for forage rape and swedes were enhanced using slow degradation kinetics and a predominantly propionic stoichiometry. These results indicate that MollyRum14 is suitable to predict methane emissions from sheep fed a variety of fresh forages including annual fodder crops. However, a clear understanding of degradation rates and stoichiometries is needed to enhance the utility of the model as a predictive tool. This would allow continuous adjustment of digestion rates and stoichiometries, to be potentially tailored to individual forage species.