The goal of this review was to analyze published data related to mitigation of enteric methane (CH4) emissions from ruminant animals to document the most effective and sustainable strategies. Increasing forage digestibility and digestible forage intake was one of the major recommended CH4 mitigation practices. Although responses vary, CH4 emissions can be reduced when corn silage replaces grass silage in the diet. Feeding legume silages could also lower CH4 emissions compared to grass silage due to their lower fiber concentration. Dietary lipids can be effective in reducing CH4 emissions, but their applicability will depend on effects on feed intake, fiber digestibility, production, and milk composition. Inclusion of concentrate feeds in the diet of ruminants will likely decrease CH4 emission intensity (Ei; CH4 per unit animal product), particularly when inclusion is above 40% of dietary dry matter and rumen function is not impaired. Supplementation of diets containing medium to poor quality forages with small amounts of concentrate feed will typically decrease CH4 Ei. Nitrates show promise as CH4 mitigation agents, but more studies are needed to fully understand their impact on whole-farm greenhouse gas emissions, animal productivity, and animal health. Through their effect on feed efficiency and rumen stoichiometry, ionophores are likely to have a moderate CH4 mitigating effect in ruminants fed high-grain or mixed grain-forage diets. Tannins may also reduce CH4 emissions although in some situations intake and milk production may be compromised. Some direct-fed microbials, such as yeast-based products, might have a moderate CH4-mitigating effect through increasing animal productivity and feed efficiency, but the effect is likely to be inconsistent. Vaccines against rumen archaea may offer mitigation opportunities in the future although the extent of CH4 reduction is likely to be small and adaptation by ruminal microbes and persistence of the effect is unknown. Overall, improving forage quality and the overall efficiency of dietary nutrient use is an effective way of decreasing CH4 Ei. Several feed supplements have a potential to reduce CH4 emission from ruminants although their long-term effect has not been well established and some are toxic or may not be economically feasible.

The objective of this paper is to review the literature concerning nitrogen utilisation in lactating dairy cows with an emphasis on their contribution to environmental pollution. Nitrogen, as oxides or ammonia, is one of the green houses gases contributing to air pollution and through leaching to rivers and ground water resources. A quantitative analysis of the contribution of dairy cows to pollution at the farm level is given and the effect of different types of carbohydrate and protein supplementation discussed. The relationship between nitrogen intake and nitrogen balance was investigated using data from 580 dairy cows and 90 treatments published in the literature. Regression analysis described the relationships between nitrogen intake and output in faeces, urine and milk. Inefficient utilisation of nitrogen by dairy cows indicates that about 72% of consumed nitrogen is excreted in faeces and urine. There were positive linear relationships between nitrogen intake and output in faeces, urine and milk up to an intake of 400 g N/d. However, above 400 g N/d, excretion in urine increased exponentially while the rate of increase in nitrogen excretion in faeces and milk declined linearly. To reduce nitrogen pollution, it is recommended to decrease the amount of crude protein in the total diet to approximately 150 g/kg DM which compared with levels of 200 g/crude protein/kg DM consumption can reduce annual nitrogen excretion in faeces by 21% and more importantly in urine by 66%. Management practices with respect to silage making and the choice of supplements need to be considered with the aim of reducing total nitrogen in excreta and if possible shifting nitrogen excretion from urine to faeces.

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.

SU MMARYMethane, in addition to being a significant source of energy loss to the animal that can range from 0 . 02 to 0 . 12 of gross energy intake, is one of the major greenhouse gases being targeted for reduction by the Kyoto protocol. Thus, one of the focuses of recent research in animal science has been to develop or improve existing methane prediction models in order to increase overall understanding of the system and to evaluate mitigation strategies for methane reduction. Several dynamic mechanistic models of rumen function have been developed which contain hydrogen gas balance sub-models from which methane production can be predicted. These models predict methane production with varying levels of success and in many cases could benefit from further development. Central to methane prediction is accurate volatile fatty acid prediction, representation of the competition for substrate usage within the rumen, as well as descriptions of protozoal dynamics and pH. Most methane models could also largely benefit from an expanded description of lipid metabolism and hindgut fermentation. The purpose of the current review is to identify key aspects of rumen microbiology that could be incorporated into, or have improved representation within, a model of ruminant digestion and environmental emissions.