Predicting methane production in dairy cows

摘要: Methane is a potent greenhouse gas, to which enteric fermentation from ruminants contributes significantly. Reliable and accurate predictions of methane (CH₄) production dairy cows would be interest develop mitigation strategies for national inventories. Thus, the overall aim this thesis was predict CH₄ in by modelling approaches. Predicted vivo decreased with increased sample size gas vitro system. Molar proportion acetate at expense propionate. Digestibility also size. Predicted based on stoichiometric equations volatile fatty acids good agreement observed values Dry matter intake per kilogram body weight, organic digestibility dietary concentrations neutral detergent fibre, non-fibre carbohydrates ether extract were variables best fit model predicting energy as gross (prediction error 4.65% mean). The non-linear models developed proved more applicable over wider range total than linear models. Adjusting exponents concentration fat, improved model. The sub-model Karoline revised. Modifications made digesta passage kinetics, microbial cell synthesis, digestion hind-gut utilisation hydrogen. sensitivity analysis suggested that kinetic are required acceptable mechanistic evaluated against published data (n=184 diets) reporting trials. There relationship between predicted production, small root mean square prediction (10.1% 6.1% fixed mixed models, respectively). bias (<2%) but statistically significant, there no slope bias. Most due random (96.4%), whereas contributions (3.4 0.2%,