Manure nitrogen (N) from cattle contributes to nitrous oxide and ammonia emissions and nitrate leaching. Measurement of manure N outputs on dairy farms is laborious, expensive, and impractical at large scales; therefore, models are needed to predict N excreted in urine and feces. Building robust prediction models requires extensive data from animals under different management systems worldwide. Thus, the study objectives were (1) to collate an international database of N excretion in feces and urine based on individual lactating dairy cow data from different continents; (2) to determine the suitability of key variables for predicting fecal, urinary, and total manure N excretion; and (3) to develop robust and reliable N excretion prediction models based on individual data from lactating dairy cows consuming various diets. A raw data set was created based on 5,483 individual cow observations, with 5,420 fecal N excretion and 3,621 urine N excretion measurements collected from 162 in vivo experiments conducted by 22 research institutes mostly located in Europe (n = 14) and North America (n = 5). A sequential approach was taken in developing models with increasing complexity by incrementally adding variables that had a significant individual effect on fecal, urinary, or total manure N excretion. Nitrogen excretion was predicted by fitting linear mixed models including experiment as a random effect. Simple models requiring dry matter intake (DMI) or N intake performed better for predicting fecal N excretion than simple models using diet nutrient composition or milk performance parameters. Simple models based on N intake performed better for urinary and total manure N excretion than those based on DMI, but simple models using milk urea N (MUN) and N intake performed even better for urinary N excretion. The full model predicting fecal N excretion had similar performance to simple models based on DMI but included several independent variables (DMI, diet crude protein content, diet neutral detergent fiber content, milk protein), depending on the location, and had root mean square prediction errors as a fraction of the observed mean values of 19.1% for intercontinental, 19.8% for European, and 17.7% for North American data sets. Complex total manure N excretion models based on N intake and MUN led to prediction errors of about 13.0% to 14.0%, which were comparable to models based on N intake alone. Intercepts and slopes of variables in optimal prediction equations developed on intercontinental, European, and North American bases differed from each other, and therefore region-specific models are preferred to predict N excretion. In conclusion, region-specific models that include information on DMI or N intake and MUN are required for good prediction of fecal, urinary, and total manure N excretion. In absence of intake data, region-specific complex equations using easily and routinely measured variables to predict fecal, urinary, or total manure N excretion may be used, but these equations have lower performance than equations based on intake.

The enzymatic digestibility of organic matter (EDOM) method is an in vitro multi-enzymatic method for estimating the organic matter (OM) digestibility of feeds. The EDOM method previously showed high accuracy with in vivo values for compound feeds. The aim of this study was to evaluate the precision of the EDOM method and determine its additivity, compared with the long-assumed additive property of the chemical components of compound feeds. 149 feed samples, 70 commercial compound feeds and 79 associated ingredients, were analyzed in a laboratory (lab1) for OM digestibility measured by EDOM (OMDEDOM) with 2 repetitions separated in time to estimate repeatability. Of the total samples, 49 compound feeds were further analyzed in a commercial laboratory (lab2) for OMDEDOM to determine reproducibility. The 49 compounds and their 69 associated ingredients were also analyzed by lab2 for dry matter (DM), ash, crude protein (CP), neutral detergent fiber (NDF), and starch. The EDOM method resulted in an intralaboratory correlation of 98.9% and an interlaboratory correlation of 92.6%, with no significant mean bias between the 2 laboratories tested. The formulation of compound feeds, total mixed rations, and mixtures in general assumes that their nutrient content can be calculated by adding together the nutrient supply of individual ingredients. This is of great importance in the feed industry for the creation of compound feeds. Additivity of OMDEDOM for the compound feed samples was evaluated by comparing the sum of the digestible OM (DOMEDOM) of the ingredients (predicted) with DOMEDOM estimated directly in the compound feed (observed). The regression of predicted versus observed showed a coefficient of determination (R2) of 0.93 and root mean square error (RMSE) of 1.07% of total DM, with no linear bias but with a mean bias (0.83% of DM). Additivity of CP, starch, crude fat, and NDF showed an R2 of 0.95, 0.98, 0.95, and 0.93, and RMSE of 1.56, 1.90, 0.39, and 1.46% of DM, respectively, all presenting linear bias. Crude fat also presented mean bias. Although significant, all linear and mean bias for DOMEDOM and chemical components were within the acceptable error limits for declaration of feeds. The results demonstrate the high precision of the EDOM method and its additive property, which is an advantage for the estimation of OM digestibility in compound feeds. Moreover, results of the tests of chemical components confirm their additive property.

The aim of this study was to develop a basic model to predict enteric methane emission from dairy cows and to update operational calculations for the national inventory in Norway. Development of basic models utilized information that is available only from feeding experiments. Basic models were developed using a database with 63 treatment means from 19 studies and were evaluated against an external database (n = 36, from 10 studies) along with other extant models. In total, the basic model database included 99 treatment means from 29 studies with records for enteric CH₄ production (MJ/day), dry matter intake (DMI) and dietary nutrient composition. When evaluated by low root mean square prediction errors and high concordance correlation coefficients, the developed basic models that included DMI, dietary concentrations of fatty acids and neutral detergent fiber performed slightly better in predicting CH₄ emissions than extant models. In order to propose country-specific values for the CH₄ conversion factor Y_m (% of gross energy intake partitioned into CH₄) and thus to be able to carry out the national inventory for Norway, the existing operational model was updated for the prediction of Y_m over a wide range of feeding situations. A simulated operational database containing CH₄ production (predicted by the basic model), feed intake and composition, Y_m and gross energy intake (GEI), in addition to the predictor variables energy corrected milk yield and dietary concentrate share were used to develop an operational model. Input values of Y_m were updated based on the results from the basic models. The predicted Y_m ranged from 6.22 to 6.72%. In conclusion, the prediction accuracy of CH₄ production from dairy cows was improved with the help of newly published data, which enabled an update of the operational model for calculating the national inventory of CH₄ in Norway.

The current study assessed the effects of red macroalgae Asparagopsis taxiformis (AT)—included as an enteric methane inhibitor—in dairy cow diets on feed intake and eating–rumination behaviour. Fifteen early lactating Norwegian Red dairy cows were offered ad libitum access to drinking water and a total mixed ration (TMR) composed of 35% concentrate feed and 65% grass silage on a dry matter (DM) basis. The experiment lasted for 74 days with the first 22 days on a common diet used as the covariate period. At the end of the covariate period, the cows were randomly allocated into one of three dietary treatments: namely, 0% AT (control), 0.125% AT and 0.25% AT in the TMR. The TMR was offered in individual feed troughs with AT blended in a 400 g (w/w) water–molasses mixture. Eating–rumination behaviour was recorded for 11 days using RumiWatchSystem after feeding the experimental diets for 30 days. The 0.25% AT inclusion significantly reduced the DM intake (DMI). Time (min/d) spent on eating and eating in a head-down position increased with the increasing AT level in the diet, whereas rumination time was not affected. The greater time spent on eating head-down with the 0.25% AT group resulted in a significantly higher chewing index (min/kg DMI). Estimated saliva production per unit DMI (L/kg DMI, SE) increased from 10.9 (0.4) in the control to 11.3 (0.3) and 13.0 (0.3) in the 0.125% and 0.25% AT groups, respectively. This aligned with the measured ruminal fluid pH (6.09, 6.14, and 6.37 in the control, 0.125% AT and 0.25% AT groups, respectively). In conclusion, either the level of the water–molasses mixture used was not sufficient to mask the taste of AT, or the cows used it as a cue to sort out the AT. Studies with relatively larger numbers of animals and longer adaptation periods than what we used here, with varied modes of delivery of the seaweed may provide novel strategies for administering the additive in ruminant diets.

In this study, we tested a response function comprising responses in milk to changes in organic matter digestibility of silages and concentrate supply. We studied the effect of changes in silage digestibility and concentrate supply on milk yield, feed intake, body weight, and methane production using 60 Norwegian Red cows. The experiment was a complete randomized block design comprising 3 periods. The pre-experimental period lasted 20 d and all the cows were fed a common silage for ad libitum intake and concentrate according to yield. Next, response period 1 lasted 17 d and the cows were divided into 2 treatments, where a low-digestible silage (LDS) was fed to half of the cows, and the other half were fed a high-digestible silage (HDS). Both groups were fed silage for ad libitum silage intake. Concentrate was optimized according to the yield and type of silage offered. In this period, the effect of silage was evaluated using a mixed model, including the results from pre-experimental period, with parity as a covariate and animal as a random effect. In response period 2, which lasted 20 d, the concentrate level was evaluated by dividing the silage digestibility treatments further into 3 subgroups. Concentrate was increased by 2 kg of dry matter (DM) per day, decreased by 2 kg of DM/d, or remained unchanged. In response period 1, silage treatments were optimized to obtain similar yields and resulted in a lower concentrate offer to HDS treatment. However, the HDS treatment showed a 3.0 kg of DM/d higher total feed intake due to a higher than expected silage intake. This resulted in 3.5 kg higher energy-corrected milk (ECM). Methane emissions were similar between silage treatments, but HDS showed lower methane per kilogram of DM due to its higher intake. The effect of concentrate supply level and interaction with silage digestibility was evaluated using mixed models, including the results for response period 1, with parity as a covariate and animal as a random effect. The reduction in concentrate offer by 2 kg/d in response period 2 was compensated for by increased 1.3 kg of DM/d of silage intake for HDS, resulting in similar intake (22.1 kg of DM/d and 21.7 kg of DM/d without and with concentrate reduction, respectively) and ECM yields (29.4 and 29 kg of ECM without and with concentrate reduction, respectively). However, concentrate offer reduction could not be compensated for by increased silage intake for LDS and resulted in lower milk yields (27.5 kg of ECM). Increased concentrate showed a higher marginal ECM response (kg of ECM per kg of additional concentrate intake) for LDS (1.8 vs. 3.3 kg of ECM for HDS and LDS, respectively). Thus, the drop in milk yields could be compensated for by increased concentrate offers if LDS are fed. Total methane production increased with increased concentrate intake, regardless of silage digestibility. Methane emissions per unit of milk were affected by total DM intake rather than by changes in silage digestibility and concentrate level. The results of this study are based on short-term periods and could show differences if study periods were longer; the results should be interpreted accordingly.