Organic compounds in dairy manure undergo a series of reactions producing pollutants such as ammonia and methane. Because various organic compounds have different reaction rates, the emissions could be accurately determined if amounts and concentrations of individual nutrients in manure are known. A set of empirical models were developed for predicting faecal and urinary water, carbon (C), nitrogen (N), acid detergent fibre and neutral detergent fibre output (kg/day) from lactating Holstein cows. Dietary nutrient contents, milk yield and composition, bodyweight, age and days in milk were used with or without dry matter intake (DMI) as potential predictor variables. Multi-collinearity, goodness of fit, model complexity, and random study and animal effects were taken into account during model development, which used 742 measured faecal or urinary nutrient output observations (kg/day). The models were evaluated with an independent dataset (n ≤ 364). When DMI was used as a predictor variable, the models predicted faecal and urinary nutrient outputs successfully with root mean square prediction error as a percentage of average observed values (RMSPE%) ranging from 9.1% to 20.7%. All the predictions except urine output had RMSPE% ranging from 18.3% to 24.6% when DMI was not used. The nutrient output predictions were in reasonable agreement with observed values throughout the data range (systematic bias <14% of total bias). Fresh manure C:N ratio predictions were acceptable (RMSPE% ≤ 14.3-15.2%) although the systematic bias were notable (17.1-20.7% of total bias). The models could be integrated successfully with process-based manure or soil models to assess nutrient transformation in dairy production systems.

Reliable estimates of fresh manure water output from dairy cows help to improve storage design, enhance efficiency of land application, quantify the water footprint, and predict nutrient transformations during manure storage. The objective of the study was to construct a mechanistic, dynamic, and deterministic mathematical model to quantify urinary and fecal water outputs (kg/d) from individual lactating dairy cows. The model contained 4 body water pools: reticulorumen (QRR), post-reticulorumen (QPR), extracellular (QEC), and intracellular (QIC). Dry matter (DM) intake, dietary forage, DM, crude protein, acid detergent fiber and ash contents, milk yield, and milk fat and protein contents, days in milk, and body weight were input variables to the model. A set of linear equations was constructed to determine drinking, feed, and saliva water inputs to QRR and fractional water passage from QRR to QPR. Water transfer via the rumen wall was subjected to changes in QEC and total water input to QRR. Post-reticulorumen water passage was adjusted for DM intake. Metabolic water production and respiratory cutaneous water losses were estimated with functions of heat production in the model. Water loss in urine was driven by absorbed N left after being removed via milk. Model parameters were estimated simultaneously using observed fecal and urinary water output data from lactating Holstein cows (n=670). The model was evaluated with data that were not used for model development and optimization (n=377). The observations in both data sets were related to thermoneutral conditions. The model predicted drinking water intake, fecal, urinary, and total fresh manure water output with root mean square prediction errors as a percentage of average values of 18.1, 15.6, 30.6, and 14.6%, respectively. In all cases, >97% of the prediction error was due to random variability of data. The model can also be used to determine saliva production, heat and metabolic water production, respiratory cutaneous water losses, and size of major body water pools in lactating Holstein cows under thermoneutral conditions.

Monensin is a widely used feed additive with the potential to minimize methane (CH4) emissions from cattle. Several studies have investigated the effects of monensin on CH4, but findings have been inconsistent. The objective of the present study was to conduct meta-analyses to quantitatively summarize the effect of monensin on CH4 production (g/d) and the percentage of dietary gross energy lost as CH4 (Ym) in dairy cows and beef steers. Data from 22 controlled studies were used. Heterogeneity of the monensin effects were estimated using random effect models. Due to significant heterogeneity (>68%) in both dairy and beef studies, the random effect models were then extended to mixed effect models by including fixed effects of DMI, dietary nutrient contents, monensin dose, and length of monensin treatment period. Monensin reduced Ym from 5.97 to 5.43% and diets with greater neutral detergent fiber contents (g/kg of dry matter) tended to enhance the monensin effect on CH4 in beef steers. When adjusted for the neutral detergent fiber effect, monensin supplementation [average 32 mg/kg of dry matter intake (DMI)] reduced CH4 emissions from beef steers by 19±4 g/d. Dietary ether extract content and DMI had a positive and a negative effect on monensin in dairy cows, respectively. When adjusted for these 2 effects in the final mixed-effect model, monensin feeding (average 21 mg/kg of DMI) was associated with a 6±3 g/d reduction in CH4 emissions in dairy cows. When analyzed across dairy and beef cattle studies, DMI or monensin dose (mg/kg of DMI) tended to decrease or increase the effect of monensin in reducing methane emissions, respectively. Methane mitigation effects of monensin in dairy cows (-12±6 g/d) and beef steers (-14±6 g/d) became similar when adjusted for the monensin dose differences between dairy cow and beef steer studies. When adjusted for DMI differences, monensin reduced Ym in dairy cows (-0.23±0.14) and beef steers (-0.33±0.16). Monensin treatment period length did not significantly modify the monensin effects in dairy cow or beef steer studies. Overall, monensin had stronger antimethanogenic effects in beef steers than dairy cows, but the effects in dairy cows could potentially be improved by dietary composition modifications and increasing the monensin dose.