Previous attempts to apply statistical models, which correlate nutrient intake with methane production, have been of limited value where predictions are obtained for nutrient intakes and diet types outside those used in model construction. Dynamic mechanistic models have proved more suitable for extrapolation, but they remain computationally expensive and are not applied easily in practical situations. The first objective of this research focused on employing conventional techniques to generate statistical models of methane production appropriate to United Kingdom dairy systems. The second objective was to evaluate these models and a model published previously using both United Kingdom and North American data sets. Thirdly, nonlinear models were considered as alternatives to the conventional linear regressions. The United Kingdom calorimetry data used to construct the linear models also were used to develop the three nonlinear alternatives that were all of modified Mitscherlich (monomolecular) form. Of the linear models tested, an equation from the literature proved most reliable across the full range of evaluation data (root mean square prediction error = 21.3%). However, the Mitscherlich models demonstrated the greatest degree of adaptability across diet types and intake level. The most successful model for simulating the independent data was a modified Mitscherlich equation with the steepness parameter set to represent dietary starch-to-ADF ratio (root mean square prediction error = 20.6%). However, when such data were unavailable, simpler Mitscherlich forms relating dry matter or metabolizable energy intake to methane production remained better alternatives relative to their linear counterparts.

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A partially balanced change-over design experiment involving 192 beef steers, which were initially 14 months old and 415 kg live weight, was carried out to determine the intakes of 136 silages from commercial farms in Northern Ireland. Each silage was offered ad libitum as the sole food to 10 animals, with eight silages offered in each of 17 periods over 2 years. A standard grass hay was offered to 16 animals in each period to enable period effects on intake to be removed. Detailed chemical and biological compositions of the silages were also determined. The ranges for pH and dry matter (DM), crude protein, ammonia-nitrogen and apparent digestible organic matter fin vivo) concentrations in the silages and silage dry DM intakes were 3-50 to 5-49 (s.d. 0-396); 155 to 413 (s.d. 43-1) g/kg; 79 to 212 (s.d. 24-4) g/kg DM; 45 to 384 (s.d. 63-2) g/kg total nitrogen; 528 to 769 (s.d. 58) g/kg DM and 4-3 to 10-9 (s.d. 1-13) kg/day respectively. Relationships between intake and individual parameters or groups of parameters have been developed using simple and multiple linear regression analysis and partial least-squares analyses. Silage intake was closely related to factors which influence the extent of digestion and rate of passage of the material through the animal, as indicated by the strong relationships (R 2 of regressions = 0-28 to 0-50) with in vivo apparent digestibility and rumen degradability and the concentrations of the fibre and nitrogen factors. Intake was poorly correlated with factors such as pH, total acidity, buffering capacity and the concentrations of lactic, acetic and butyric acids (R 2 of regressions = zero to 0-11). Near infrared reflectance spectrometry (NIRS) provided the best fit relationship with intake (R 2 of relationship = 0-90). The results also indicate that the intake potential of silages can be directly predicted with a high degree of accuracy from the NIRS of both dried and undried samples of silage, provided the appropriate sample preparation and scanning methods are used.

The data set used in the present study was obtained from 20 energy metabolism studies involving 579 lactating dairy cows (511 Holstein-Friesian, 36 Norwegian Red, and 32 Jersey-Holstein crossbreds) varying in genetic merit, lactation number, stage of lactation, and live weight. These cows were offered diets based on grass silage (n=550) or fresh grass (n=29), and their energy intake and outputs, including methane energy (CH(4)-E), were measured in indirect open-circuit respiration calorimeter chambers. The objective was to use these data to evaluate relationships between CH(4)-E output and a range of factors in animal production and energetic efficiency in lactating dairy cows under normal feeding regimens. The CH(4)-E as a proportion of milk energy output (E(l)), E(l) adjusted to zero energy balance (E(l(0))), or intakes of gross energy (GE), digestible energy (DE), or metabolizable energy (ME) was significantly related to a wide range of variables associated with milk production (E(l) and E(l(0))) and energy parameters (energy intake, metabolizability, partitioning, and utilization efficiencies). Three sets of linear relationships were developed with experimental effects removed. The CH(4)-E/GE intake (r(2)=0.50-0.62) and CH(4)-E/E(l) (r(2)=0.41-0.68) were reduced with increasing feeding level, E(l)/metabolic body weight (MBW; kg(0.75)), E(l(0))/MBW, GE intake/MBW, DE intake/MBW, and ME intake/MBW. Increasing dietary ME/DE decreased CH(4)-E/E(l) (r(2)=0.46) and CH(4)-E/GE intake (r(2)=0.72). Dietary ME concentration and ME/GE were also negatively related to CH(4)-E/GE intake (r(2)=0.47). However, increasing heat production/ME intake increased CH(4)-E as a proportion of E(l) (r(2)=0.41), E(l(0)) (r(2)=0.67) and energy intake (GE, DE, and ME; r(2)=0.62 and 0.70). These proportional CH(4)-E variables were reduced with increasing ratios of E(l)/ME intake and E(l(0))/ME intake and efficiency of ME use for lactation (r(2)=0.49-0.70). Fitting CH(4)-E/E(l) or CH(4)-E/E(l(0)) against these energetic efficiencies in quadratic rather than linear relationships significantly increased r(2) values (0.49-0.67 vs. 0.59-0.87). In conclusion, CH(4)-E as a proportion of energy intake (GE, DE, and ME) and milk production (E(l) and E(l(0))) can be reduced by increasing milk yield and energetic efficiency of milk production or by reducing energy expenditure for maintenance. The selection of dairy cows with high energy utilization efficiencies and milk productivity offers an effective approach to reducing enteric CH(4) emission rates.

Twelve perennial ryegrass (Lolium perenne L.) varieties of different ploidy and maturity classifications were compared under a frequent cutting management in their second harvest year, equivalent to the simulated rotational grazing system employed in UK testing protocols. Varietal differences in canopy structure (proportion of lamina, green leaf mass, sward surface height, extended tiller height, bulk density) and in herbage nutritive value factors (water-soluble carbohydrate content and proportion of linoleic and α-linolenic fatty acids) were assessed and their importance evaluated with reference to total herbage production. Significant variety variation (P<0·001) was recorded in the annual means of all the canopy structure characteristics. Significant differences associated with ploidy were also recorded, with tetraploid varieties having significantly higher values than diploids in most plant characters, indicating better intake characteristics for these grasses. Temporal patterns of variation associated with maturity were also observed in several characters, thus making it impossible to designate a single assessment that would be representative of the annual ranking of varieties. Water-soluble carbohydrate concentration differed significantly (P<0·001) between varieties and although the tetraploids tended to have high contents, the highest value of all was recorded in a diploid variety, which had been selectively bred for this trait. The varieties did not differ in total lipid content but there were significant differences in the proportion of linoleic acid between varieties (P<0·001) while the proportion of α-linolenic acid differed between varieties (P<0·001), ploidy (P<0·001) and maturity (P<0·05) classes.Overall evaluation of the extensive variety variation highlighted the need for better quantification of animal responses to differences of these magnitudes, before the high workload of including them in routine variety testing protocols could be justified. Potential for breeding improvement in these factors was also indicated and the future prospects for their use in farmer decision support systems was considered.