G. van Duinkerken

Update of the Dutch protein evaluation system for ruminants: the DVE/OEB2010 system

In the current Dutch protein evaluation system (the DVE/OEB 1991 system), two characteristics are calculated for each feed: true protein digested in the intestine (DVE) and the rumen degradable protein balance (OEB). Of these, DVE represents the protein value of a feed, while OEB is the difference between the potential microbial protein synthesis (MPS) on the basis of available rumen degradable protein and that on the basis of available rumen degradable energy. DVE can be separated into three components: (i) feed crude protein undegraded in the rumen but digested in the small intestine, (ii) microbial true protein synthesized in the rumen and digested in the small intestine, and (iii) endogenous protein lost in the digestive processes. Based on new research findings, the DVE/OEB 1991 system has recently been updated to the DVE/OEB 2010 system. More detail and differentiation is included concerning the representation of chemical components in feed, the rumen degradation characteristics of these components, the efficiency of MPS and the fractional passage rates. For each chemical component, the soluble, washout, potentially degradable and truly non-degradable fractions are defined with separate fractional degradation rates. Similarly, fractional passage rates for each of these fractions were identified and partly expressed as a function of fractional degradation rate. Efficiency of MPS is related to the various fractions of the chemical components and their associated fractional passage rates. Only minor changes were made with respect to the amount of DVE required for maintenance and production purposes of the animal. Differences from other current protein evaluation systems, viz. the Cornell Net Carbohydrate and Protein system and the Feed into Milk system, are discussed.

A review of factors influencing milk urea concentration and its relationship with urinary urea excretion in lactating dairy cattle

Milk urea nitrogen (MUN) concentration in dairy cows may serve as an on-farm indicator to guide nutritional strategies and to help reduce emissions of nitrogen (N) to the environment. Excretion of urinary urea nitrogen (UUN) is positively related to MUN, but the relationship is highly variable. The accuracy of MUN as a predictor of UUN may improve when various factors that affect this relationship can be taken into account. The current review discusses the impact of a number of UUN : MUN ratio influencing factors related to: physiological mechanisms in the dairy cow, farm management, differences between individual cows, nutrition and analysis methods for MUN. Factors related to variation in water intake, urine production, dietary protein level, body weight (BW) and time and frequency of feeding and milking are shown to affect MUN and its relationship with UUN. In addition, a number of factors are discussed that are likely to affect this relationship such as biological rhythm, renal reabsorption of urea during periods of protein deficiency and breeding value for MUN. Accounting for these above-mentioned factors in the relationship between MUN and UUN might substantially improve the applicability and accuracy of MUN as a predictor of protein utilization efficiency and UUN.

Prediction of urinary nitrogen and urinary urea nitrogen excretion by lactating dairy cattle in northwestern Europe and North America: A meta-analysis

A meta-analysis was conducted on the effect of dietary and animal factors on the excretion of total urinary nitrogen (UN) and urinary urea nitrogen (UUN) in lactating dairy cattle in North America (NA) and northwestern Europe (EU). Mean treatment data were used from 47 trials carried out in NA and EU. Mixed model analysis was used with experiment included as a random effect and all other factors, consisting of dietary and animal characteristics, included as fixed effects. Fixed factors were nested within continent (EU or NA). A distinction was made between urinary excretions based on either urine spot samples or calculated assuming a zero N balance, and excretions that were determined by total collection of urine only. Moreover, with the subset of data based on total collection of urine, a new data set was created by calculating urinary N excretion assuming a zero N balance. Comparison with the original subset of data allowed for examining the effect of such an assumption on the relationship established between milk urea N (MUN) concentration and UN. Of all single dietary and animal factors evaluated to predict N excretion in urine, MUN and dietary crude protein (CP) concentration were by far the best predictors. Urinary N excretion was best predicted by the combination of MUN, CP, and dry matter intake, whereas UUN was best predicted by the combination of MUN and CP. All other factors did not improve or only marginally improved the prediction of UN or UUN. The relationship between UN and MUN differed between NA and EU, with higher estimated regression coefficients for MUN for the NA data set. Precision of UN and UUN prediction improved substantially when only UN or UUN data based on total collection of urine were used. The relationship between UN and MUN for the NA data set, but not for the EU data set, was substantially altered when UN was calculated assuming a zero N balance instead of being based on the total collection of urine. According to results of the present meta-analysis, UN and UUN are best predicted by the combination of MUN and CP and that, in regard to precision and accuracy, prediction equations for UN and UUN should be derived from the total collection of urine.

Milk urea concentration as an indicator of ammonia emission from dairy cow barn under restricted grazing

Bulk milk urea concentration was evaluated to assess its potential as an indicator of ammonia emission from a dairy cow barn in a situation with restricted grazing. An experiment was carried out with a herd of, on average, 52 Holstein-Friesian dairy cows. The cows were housed in a naturally ventilated barn with cubicles and a slatted floor, were fed ensiled forages and feed supplements, and each day were allowed 8.5 h of grazing. The experiment was a balanced randomized block design, replicated 3 times. The experimental factor was the bulk milk urea level, which was adjusted to levels of 15, 35, and 55 mg of urea per 100 g of milk, respectively, by changing the level of nitrogen fertilization of the pasture, the herbage mass and grass regrowth age, and the level and type of feed supplement. Ammonia emission from the barn was measured using sulfur hexafluoride as the tracer gas. Ammonia emission generally increased upon an increase in adjusted milk urea levels. A dynamic regression model was used to predict ammonia emission from bulk milk urea concentration, temperature, and a slurry mixing index. This model accounted for 66% of the total variance in ammonia emission and showed that emission increases exponentially with increasing milk urea concentration. At levels of 20 and 30 mg of urea per 100 g of milk, ammonia emission increased by about 2.5 and 3.5%, respectively, when milk urea concentration increased by 1 mg/100 g. Furthermore, emissions from the barn increased 2.6% when temperature increased by 1°C. The study showed that bulk milk urea concentration is a useful indicator for ammonia emissions from a dairy cow barn in a situation with restricted grazing.

Economic potential of individual variation in milk yield response to concentrate intake of dairy cows

The objectives of the current study were to quantify the individual variation in daily milk yield response to concentrate intake during early lactation and to assess the economic prospects of exploiting the individual variation in milk yield response to concentrate intake. In an observational study, data from 299 cows on four farms in the first 3 weeks of the lactation were collected. Individual response in daily milk yield to concentrate intake was analysed by a random coefficient model. Marked variation in individual milk yield response to concentrate intake was found on all four farms. An economic simulation was carried out, based on the estimated parameter values in the observational study. Individual optimization of concentrate supply is compared with conventional strategies for concentrate supply based on averaged population response parameters. Applying individual economic optimal settings for concentrate supply during early lactation, potential economic gain ranges from €0·20 to €2·03/cow/day.

Adaptive models for online estimation of individual milk yield response to concentrate intake and milking interval length of dairy cows

Automated feeding and milking of dairy cows enables the application of individual cow settings for concentrate supply and milking frequency. Currently, general settings are used, based on knowledge about energy and nutrient requirements in relation to milk production at the group level. Individual settings, based on the actual individual response in milk yield, have the potential for a marked increase in economic profits. In the present study, adaptive dynamic models for online estimation of milk yield response to concentrate intake and length of milking interval are evaluated. The parameters in these models may change over time and are updated through a Bayesian approach for online analysis of time series. The main use of dynamic models lies in their ability to determine economically optimal settings for concentrate intake and milking interval length for individual cows at any day in lactation. Three adaptive dynamic models are evaluated, a model with linear terms for concentrate intake and length of milking interval, a model that also comprises quadratic terms, and an enhanced model (EM) in order to obtain more stable parameter estimates. The linear model is useful only for forecasting milk production and the estimated parameters of the quadratic model were found to be unstable. The parsimony of the EM leads to far more stable parameter estimates. It is shown that the EM is suitable for control and monitoring, and therefore promises to be a valuable tool for application within precision livestock farming

Relationship between chemical composition and in situ rumen degradation characteristics of maize silages in dairy cows

Several in situ studies have been conducted on maize silages to determine the effect of individual factors such as maturity stage, chop length and ensiling of maize crop on the rumen degradation but the information on the relationship between chemical composition and in situ rumen degradation characteristics remains scarce. The objectives of this study were to determine and describe relationships between the chemical composition and the rumen degradation characteristics of dry matter (DM), organic matter (OM), CP, starch and aNDFom (NDF assayed with a heat stable amylase and expressed exclusive of residual ash) of maize silages. In all, 75 maize silage samples were selected, with a broad range in chemical composition and quality parameters. The samples were incubated in the rumen for 2, 4, 8, 16, 32, 72 and 336 h, using the nylon bag technique. Large range was found in the rumen degradable fractions of DM, OM, CP, starch and aNDFom because of the broad range in chemical composition and quality parameters. The new database with in situ rumen degradation characteristics of DM, OM, CP, starch and aNDFom of the maize silages was obtained under uniform experimental conditions; same cows, same incubation protocol and same chemical analysis procedures. Regression equations were developed with significant predictors (P<0.05) describing moderate and weak relationships between the chemical composition and the washout fraction, rumen undegradable fraction, potentially rumen degradable fraction, fractional degradation rate and effective rumen degradable fraction of DM, OM, CP, starch and aNDFom.