Supplementary concentrate type affects nitrogen excretion of grazing dairy cows

These experiments were designed to investigate nutritional means of reducing urine N excretion by grazing cows. In experiment 1, 36 Holstein-Friesian cows averaging 92 d in milk were fed either 1 or 6 kg of a high protein concentrate or 6 kg of a low protein concentrate. Pasture dry matter (DM) intake was higher for cows fed 1 kg of high protein concentrate (15.4 +/- 0.62 kg/d) than for cows fed 6 kg of low protein concentrate (13.4 +/- 0.55) but not for cows fed 6 kg of high protein concentrate (13.9 +/- 0.96). The reduction in pasture intake per kg of concentrate DM ingested amounted to 0.35 and 0.47 kg of pasture DM for cows fed 6 kg of high protein and 6 kg of low protein concentrate, respectively. Milk yield and milk protein yield were higher for cows fed 6 kg of high protein concentrate than for cows fed 1 kg of high protein concentrate. Cows fed 6 kg of high protein concentrate had the highest levels of N intake, total N excretion, and urine N excretion. The proportion of N excreted in the urine was lowest for cows fed 6 kg of low protein concentrate. Milk N excretion as a proportion of ingested N was higher for cows fed 6 kg of low protein concentrate than for cows fed 6 kg of high protein concentrate but not for cows fed 1 kg of high protein concentrate. In experiment 2, 24 Holstein-Friesian cows averaging 211 d in milk were supplemented with 4 kg of rolled barley or 4.32 kg of NaOH-treated barley. Milk yield and milk protein yield tended to be higher for cows fed rolled barley than for cows fed NaOH-treated barley. There was no difference in N intake, fecal N excretion, urinary N excretion, or milk N output between diets. Milk urea N concentration was lower for cows fed rolled barley. Significant positive linear relationships were found between N intake and fecal N excretion, urine N excretion, and milk N excretion in experiment 1. In experiment 2, the relationships between N intake and fecal N excretion and urine N excretion were curvilinear, with urine N excretion increasing at a decreasing rate, and fecal N excretion increasing at an increasing rate, as N intake increased. The N excreted by dairy cows may be partitioned to fecal N if supplements based on high concentrations of fermentable organic matter and low concentrations of N are fed. Refinement of this nutritional strategy may allow reduced N excretion without reducing animal performance.     

Effect of forage source and a supplementary methionine hydroxy analog on nitrogen balance in lactating dairy cows offered a low crude protein diet

Four primiparous and 4 multiparous midlactation dairy cows were stratified by pre-experimental milk yield (23.5 ± 2.3 kg/d), protein yield (0.75 ± 0.066 kg/d), parity, and days in lactation (121 ± 10 d) into 4 groups of 2 in a 2 × 2 factorial, Latin square design (n = 8) to assess the effect of forage source and a supplementary methionine hydroxy analog on nitrogen (N) balance where low crude protein (CP) diets (13.3%) are offered. Diets contained either predominantly grass silage [GS (G− and G+)] or corn silage [CS (C− and C+)] as the forage source and were offered with (G+ and C+) or without (G− and C−) the isopropyl ester of 2-hydroxy-4 methylthio butanoic acid (HMBi). The G− and G+ contained 46% GS and 10% CS in the dry matter (DM), whereas C− and C+ contained 12% GS and 52% CS in the DM. Supplementary HMBi was included at a rate of 0.2% of DM in G+ and C+ diets. Diets were isonitrogenous (9.8 ± 0.4% protein truly digested in the small intestine) and isoenergetic (0.96 ± 0.01 units of energy for lactation; kg/DM). Each of the 4 experimental periods lasted 24 d: 14 d for dietary adaptation, followed by 10 d of housing in individual metabolism stalls; N balance was conducted on the last 5 d of each experimental period. Intake of DM was higher for CS-based vs. GS-based diets (20.23 vs. 18.41 kg/d). No effect of dietary treatment was found on milk yield or yields of milk fat, protein, and lactose. Supplementing with HMBi tended to improve milk solids yield (1.69 vs. 1.59 kg/d), casein yield (0.59 vs. 0.55 kg/d), and concentrations of casein (2.89 vs. 2.73%) and protein (3.58 vs. 3.49%) in the milk. Dietary N intake was higher for CS-based vs. GS-based diets (0.460 vs. 0.422 kg/d). However, forage source or supplementary HMBi had no effect on N excretion in the feces, urine, or milk. Excretion of urinary urea was positively related to N intake. Concentrations of urea N in the plasma (2.34 vs. 1.72 mmol/L), milk (2.54 vs. 2.24 mmol/L), and urine (123.32 vs. 88.79 mmol/L), and total excretion of urinary urea N (40.23 vs. 35.09 g/d) were higher for animals offered CS-based vs. GS-based diets. Corn silage improved N intake through improved DM intake. However, neither forage source nor HMBi supplementation affects N output in the feces, urine, or milk.     

Prediction of nitrogen excretion from data on dairy cows fed a wide range of diets compiled in an intercontinental database: A meta-analysis

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.     

Milk production and nitrogen excretion of dairy cows fed different amounts of protein and varying proportions of alfalfa and corn silage

Four trials were conducted to determine the effect of dietary protein amount on lactation performance and N utilization. Each trial used one of the following alfalfa-to-corn-silage ratios for the forage part of the diet: 100:0, 75:25, 50:50, and 25:75. All trials utilized 16 mid-lactation Holstein cows (days in milk averages ranging from 80 to 140 among trials) in a replicated 4 × 4 Latin square design with 3-wk periods, including 2 wk for adaptation and 1 wk for data collection. Diets consisted of 50% forage and 50% concentrate (dry matter basis) and were formulated to contain 15.00, 16.25, 17.50, or 18.75% protein in each trial. The analyzed protein content of the diets was 15.7, 16.9, 18.0, and 19.2% when averaged across trials. Milk yield was similar among dietary protein levels in each trial, ranging from 35.2 to 36.1 kg/d when data were combined across trials. Changes in milk fat and protein due to the protein content of the diet were small and inconsistent. Both milk urea nitrogen and blood urea nitrogen concentrations increased linearly as the protein content of the diet was increased, ranging from 9.9 to 13.1 and from 9.9 to 13.8 mg/dL, respectively, across trials. As dietary protein was increased from the lowest to the highest concentrations when data were combined and analyzed, mean fecal N concentration increased from 2.8 to 3.0%, and urinary N from 5.8 to 7.3 g/L. At the same time, mean total N excretion increased from 484 to 571 g/d, and conversion of intake N to milk N decreased from 0.27 to 0.22, resulting in an average change of 18%. Of the N excreted, urinary N accounted for an increasing proportion, ranging from 41 to 48%, as dietary protein was increased. Overall, based on N utilization as well as milk production, 17% protein in diets utilizing various proportions of alfalfa and corn silage as the forage source appeared sufficient for cows producing 38 kg/d of milk in this study.     

The effects of rumen nitrogen balance on nutrient intake,nitrogen partitioning,and microbial protein synthesis in lactating dairy cows offered different dietary protein sources

The aim was to study the effects of rumen N balance (RNB), dietary protein source, and their interaction on feed intake, N partitioning, and rumen microbial crude protein (MCP) synthesis in lactating dairy cows. Twenty-four lactating Holstein cows were included in a replicated 4 × 4 Latin square experimental design comprising four 20-d periods, each with 12 d of adaptation to the experimental diets and 8 d of sampling. The dietary treatments followed a 2 × 2 factorial arrangement (i.e., 4 treatments) with 2 main protein sources [faba bean grain (FB) and SoyPass (SP; Beweka Kraftfutterwerk GmbH, Heilbronn, Germany)] offered at 2 dietary RNB levels each [0 g/kg of dry matter, DM (RNB0) and ?3.2 g/kg of DM (RNB?)]. The RNB was calculated as the difference between dietary crude protein (CP) intake and the rumen outflow of undegraded feed CP and MCP and divided by 6.25. Composition of concentrate mixtures was adjusted to create diets with desired RNB levels. Each of these protein sources supplied ≥35% of total dietary CP. Both diets for each protein source were isoenergetic but differed in CP concentrations. The DM intake (kg/d) was lower for RNB? than for RNB0 in diets containing FB, whereas no differences were seen between the RNB levels for SP diets. The RNB? decreased N intake and urinary N excretion but increased milk N use efficiency in both FB and SP diets, with greater differences between the RNB levels for FB diets than for SP diets. Similarly, duodenal MCP synthesis (g/kg of digestible organic matter intake) estimated from purine derivatives in the urine was lower for RNB? than for RNB0 in FB diets but similar between the RNB levels in diets containing SP. Low RNB of approximately ?65 g/d (approximately ?3.2 g/kg of DM) in diets reduced feed intake, N balance, and performance in high-yielding dairy cows with possibly more pronounced effects in diets containing rapidly degradable protein sources.     

The effects of rumen nitrogen balance on intake,nutrient digestibility,chewing activity,and milk yield and composition in dairy cows vary with dietary protein sources

The objective was to study the interaction effects of rumen nitrogen balance (RNB) and dietary protein source on feed intake, apparent total-tract digestibility (ATTD), eating and ruminating activity, milk yield (MY), and milk composition in lactating dairy cows. Twenty-four lactating Holstein cows were divided in 4 groups, which were randomly assigned to the dietary treatments included in a replicated 4 × 4 Latin square experimental design that consisted of four 20-d periods, each with 12 d of adaptation to the experimental diets and 8 d of sampling. The dietary treatments followed a 2 × 2 factorial arrangement with 2 main protein sources, faba bean grain (FB) and SoyPass (SP; Beweka Kraftfutterwerk GmbH), offered at 2 dietary RNB levels: RNB0 (RNB of 0 g/kg of dry matter) and RNB? (RNB of –3.2 g/kg of dry matter; i.e., 4 treatments). The composition of concentrate mixtures was adjusted to create diets with the desired RNB levels. Each of the protein sources supplied ≥35% of the total dietary crude protein (CP). Both diets within a protein source had similar forage sources and forage to concentrate ratios and were iso-energetic, but differed in CP concentrations. The main effects of RNB, protein source, and their interactions were tested by PROC MIXED in SAS 9.4 (SAS Institute Inc.). Interaction effects were observed for daily dry matter intake and energy-corrected MY, which were lower for RNB? than RNB0 in diets containing FB (23.5 vs. 24.4 kg dry matter/d; 28.6 vs. 30.6 kg milk/d), but similar in diets containing SP (24.2 vs. 24.3 kg dry matter/d; 31.3 vs. 31.7 kg milk/d). The ATTD of NDF was lower for RNB? compared with RNB0 in the FB (44.9 vs. 49.1 g/100 g) and SP (48.5 vs. 51.9 g/100 g) diets, and greater for the SP than for FB diets. There were interaction effects for ATTD of CP and concentrations of milk urea nitrogen, which were lower for RNB? compared with RNB0 in both, FB (55 vs. 63.1 g/100 g of CP; 5.65 vs. 11.3 mg/dL milk) and SP diets (60 vs. 64.4 g/100 g of CP; 8.74 vs. 13.4 mg/dL milk). However, differences between RNB levels were greater for FB than for SP diets. Furthermore, proportions of milk fatty acids followed the same pattern as that of dietary fatty acids, but biohydrogenation appeared to be greater for RNB? than RNB0 for both protein sources and in FB than in SP diets for both RNB levels. There was an interaction effect on total number of chews per unit of NDF intake, which was greater for RNB? compared with RNB0 for both protein sources. However, the differences between RNB levels were greater in FB than in SP diets. Overall, differences in the animal responses to negative RNB between FB and SP diets suggest a need to better understand the effect of negative RNB levels with different dietary ingredients at similar utilizable CP supply.     

A dynamic model to simulate potassium balance in dairy cows

High-performing dairy cows require a particular composition of nutritional ingredients, adapted to their individual requirements and depending on their production status. The optimal dimensioning of minerals in the diet, one being potassium, is indispensable for the prevention of imbalances. Potassium balance in cows is the result of potassium intake, distribution in the organism, and excretion, and it is closely related to glucose and electrolyte metabolism. In this paper, we present a dynamical model for potassium balance in lactating and nonlactating dairy cows based on ordinary differential equations. Parameter values were obtained from clinical trial data and from the literature. To verify the consistency of the model, we present simulation outcomes for 3 different scenarios: potassium balance in (1) nonlactating cows with varying feed intake, (2) nonlactating cows with varying potassium fraction in the diet, and (3) lactating cows with varying milk production levels. The results give insights into the short- and long-term potassium metabolism, providing an important step toward the understanding of the potassium network, the design of prophylactic feed additives, and possible treatment strategies.     

Effects of the method of conservation of timothy on nitrogen metabolism in lactating dairy cows

Six ruminally and duodenally cannulated lactating primiparous Holstein cows were used to study the effects of different methods of conservation of timothy on N metabolism. Cows were assigned randomly to 2 replicated 3 × 3 Latin squares (35-d periods). Because of missing data from 2 cows, data were analyzed as a 3 × 4 Youden square. Diets contained a similar concentrate (44% of total ration on a dry matter basis) plus first-cut timothy conserved as hay, or as restrictively (formic) or extensively fermented silage (inoc). Crude protein contents were 10.4, 13.6, and 14.8% for hay, formic, and inoc, respectively. Hay and formic had a high soluble carbohydrate content (≥8.0% of dry matter) and formic and inoc had a high soluble protein content (≥8.0% of dry matter). Haying and restricting fermentation resulted in increased efficiency of partition to milk N (30.9, 28.2, 24.7% of N intake for hay, formic, and inoc, respectively). Despite a 14% lower N intake with hay, no effects of treatments were detected on microbial protein synthesis and apparent intestinal digestion of essential AA. Haying reduced feed protein degradation in the rumen, whereas this effect was not observed when restricting fermentation in the silage. Haying and restricting fermentation induced a lipogenic fermentation pattern in the rumen (4.55, 4.23, and 3.78 ratio of acetate to propionate for hay, formic, and inoc), but no effects on milk fat yield and plasma glucose were observed. Whole-body protein metabolism was unaffected by treatments.     

Estimation of energy balance at the individual and herd level using blood and milk traits in high-yielding dairy cows

This study aimed to estimate individual and herd-level energy balance (EB) using blood and milk traits in 90 multiparous high-yielding Holstein cows, held on a research farm, from wk 1 to 10 postpartum (p.p.) and to investigate the precision of prediction with successively decreased data sets simulating smaller herd sizes and with pooled samples. Dry matter intake, milk yield, and BW were measured daily from parturition through wk 10 p.p. Milk composition was determined 4 times per week, and milk acetone was measured weekly. Blood samples for the determination of metabolites, hormones, electrolytes, and enzyme activities were taken weekly from wk 1 to 10 p.p. between 0730 and 0900. Body condition scores and ultrasonic measurements of backfat thickness and fat depth in the pelvic area were evaluated in wk 1, 4, and 8 p.p. Concentrations of glucose, cholesterol, urea, insulin, insulin-like growth factor-1, triiodothyronine, and thyroxine (T4) in blood plasma and of lactose and urea in milk were positively correlated with EB, whereas concentrations of nonesterified fatty acids (NEFA), creatinine, albumin, beta-hydroxybutyrate, and growth hormone and enzyme activities in blood, and concentrations of fat, protein, fat:lactose ratio, and acetone in milk were negatively correlated with EB. Leptin concentration was not correlated to EB over the first 10 wk p.p. To estimate EB linear mixed-effects, models were developed by backward selection procedures. The most informative traits for estimation of EB were the fat:lactose ratio in milk and NEFA and T4 concentrations in blood. The precision of estimation of EB in individual cows was low. Using blood in addition to milk traits did not result in higher precision of estimation of herd-level EB, and decreasing sample sizes considerably lowered the precision of EB prediction. Estimation of overall mean herd-level EB over the first 10 wk p.p. using pooled samples was precise even with small sample sizes, but does not consider the level of EB in particular weeks. In conclusion, estimation of herd-level EB at individual weeks using milk traits only has practical implication with herd sizes of > or = 100 cows if calving is highly seasonal and of or = 400 cows if calving is uniformly distributed. Using blood in addition to milk traits does not improve precision of estimation of herd-level EB, regardless of sample size.     

Factors affecting energy and nitrogen efficiency of dairy cows: A meta-analysis

A meta-analysis was performed to explore the correlation between energy and nitrogen efficiency of dairy cows, and to study nutritional and animal factors that influence these efficiencies, as well as their relationship. Treatment mean values were extracted from 68 peer-reviewed studies, including 306 feeding trials. The main criterion for inclusion of a study in the meta-analysis was that it reported, or permitted calculation of, energy efficiency (Eeff; energy in milk/digestible energy intake) and nitrogen efficiency (Neff; nitrogen in milk/digestible nitrogen intake) at the digestible level (digestible energy or digestible protein). The effect of nutritional and animal variables, including neutral detergent fiber, acid detergent fiber (ADF), digestible energy, digestible protein, proportion of concentrate (PCO), dry matter intake, milk yield, days in milk, and body weight, on Eeff, Neff, and the Neff:Eeff ratio was analyzed using mixed models. The interstudy correlation between Eeff and Neff was 0.62, whereas the intrastudy correlation was 0.30. The higher interstudy correlation was partly due to milk yield and dry matter intake being present in both Eeff and Neff. We, therefore, also explored the Neff:Eeff ratio. Energy efficiency was negatively associated with ADF and PCO, whereas Neff was negatively associated with ADF and digestible energy. The Neff:Eeff ratio was affected by ADF and PCO only. In conclusion, the results indicate a possibility to maximize feed efficiency in terms of both energy and nitrogen at the same time. In other words, an improvement in Eeff would also mean an improvement in Neff. The current study also shows that these types of transverse data are not sufficient to study the effect of animal factors, such as days in milk, on feed efficiency. Longitudinal measurements per animal would probably be more appropriate.     

Effect of supplement crude protein concentration on milk production over the main grazing season and on nitrogen excretion in late-lactation grazing dairy cows

The objectives of this study are to evaluate the effects of (1) a potential interaction between supplement crude protein (CP) concentration and differing cow genotypes on milk production, (2) differing cow genotypes on milk production, and (3) decreasing the supplement CP concentration on milk production and N excretion during the main grazing season within a spring-calving herd. A 2 × 2 factorial arrangement experiment, with 2 feeding strategies [14%; n = 30 (lower CP; LCP) and 18%; n = 28 (higher CP; HCP) CP concentrate supplements] offered at varying levels according to pasture availability and days in milk (DIM) was conducted over the main grazing season from April 3 to September 3, 2019, at University College Dublin Lyons Farm. Cows were also grouped into 2 genotype groups: lower milk genotype; n = 30 [LM; milk kg predicted transmitting ability (PTA): 45 ± 68.6 (mean ± SD); fat kg PTA: 10 ± 4.9; and protein kg PTA: 7 ± 2.3] and higher milk genotype; n = 28 [HM; milk kg PTA: 203 ± 55.0; fat kg PTA: 13 ± 3.8; and protein kg PTA: 10 ± 2.4]. A total of 46 multiparous and 12 primiparous (total; 58) Holstein Friesian dairy cows were blocked on parity and balanced on DIM, body condition score, and Economic Breeding Index. Cows were offered a basal diet of grazed perennial ryegrass pasture. The N partitioning study took place from August 25 to 30, 2019 (187 ± 15.2 DIM). No interactions were observed for any milk production or milk composition parameter. No effect of supplement CP concentration was observed for any total accumulated milk production, daily milk production, or milk composition parameter measured. The HM cows had increased daily milk yield (+1.9 kg), fat and protein (+0.15 kg), and energy-corrected milk (+1.7 kg), compared with the LM cows. Furthermore, HM cows had decreased milk protein concentration (?0.1%) compared with LM cows. For the N partitioning study, cows offered LCP had increased pasture dry matter intake (PDMI; +0.9 kg/d), dietary N intake (+0.022 kg/d), feces N excretion (+0.016 kg/d), and decreased N partitioning to milk (?2%), and N utilization efficiency (?2.3%). In conclusion, offering cows LCP had no negative influence on milk production or milk composition over the main grazing season where high pasture quality was maintained. However, any potential negative effects of offering LCP on milk production may have been offset by the increased PDMI. Furthermore, offering cows LCP decreased N utilization efficiency due to the higher PDMI and feed N intake associated with cows on this treatment in our study.     

Effects of feeding time on nitrogen capture by lactating dairy cows grazing rye pasture

The objective of this experiment was to determine whether varying times at which a partial mixed ration was fed, either before or after grazing, affected N utilization from rye pasture and thus affected milk yield and components. Sixteen Holstein cows were fed a partial mixed ration (PMR) either at 0700, 0830, or 1100 h. Cows were milked at 0900 h and turned out to graze at 0930 h. Treatments represented feeding times 2.5 h and 1 h before grazing and immediately after grazing. The study was conducted as a 3 x 3 Latin square with three 17-d periods. There were no significant differences among treatments for pasture intake or yield of milk or milk components. Milk yield, fat %, and protein % were 29.4, 29.6, and 29.3 kg, 3.5, 3.5, and 3.4%, and 3.4, 3.5, and 3.4% for treatments, respectively. The milk urea levels were 15.6, 15.1, and 15.5 mg/dl, and were not different among treatments. Blood samples were collected on the last day of each period at 0645, 0845, 1045, 1200, and 1400 h. Blood urea nitrogen (BUN) was measured as an indicator of ruminal N capture. Concentrations were not significantly different among diets before grazing; however, they were significantly different among all treatments approximately 1 h after cows were removed from pasture. Cows fed at 0700 h, 2 h before grazing, maintained lower BUN levels across the 7 h during which the blood samples were collected. Cows that ate the PMR immediately after grazing maintained the highest BUN. Feeding a PMR to cows that graze at different times before and after grazing affected the capture of ruminal N, as indicated by differences in the levels of BUN, but there was no effect on yield of milk or milk components.     

Relationships among manure nitrogen output and dietary and animal factors in lactating dairy cows

A large data set derived from total diet digestibility assessments on lactating dairy cows (535 Holstein-Friesian and 29 Norwegian) was used to examine effects of dietary and animal factors on manure (feces and urine) nitrogen (N) output and to develop mitigation strategies and prediction equations for manure N output in lactating dairy cows. Manure N output was positively and significantly related to live weight, milk yield, dietary crude protein (CP) concentration, dry matter intake, and N intake. Reducing the dietary CP concentration or increasing the milk yield decreased manure N output per kilogram of milk yield. Prediction equations for manure N output using live weight and milk yield, either alone or combined, had relatively low R² (0.227 to 0.474) and large standard error (70.6 to 85.6) values. Addition of dietary CP concentration to these relationships considerably increased R² to 0.754 and reduced the standard error to 48.2. Relating manure N output to N intake produced a very high r² (0.901) and a very low standard error (30.6). The addition of live weight and milk yield to this relationship as supporting predictors only marginally increased R² to 0.910 and reduced the standard error to 29.3. The internal validation of these equations revealed that use of N intake as the primary predictor produced a very accurate prediction of manure N output. In situations in which data on N intake are not available, prediction equations based on dietary CP concentration, live weight, and milk yield together can produce a relatively accurate assessment of manure N output.     

Alternatives to linear analysis of energy balance data from lactating dairy cows

The current energy requirements system used in the United Kingdom for lactating dairy cows utilizes key parameters such as metabolizable energy intake (MEI) at maintenance (MEm), the efficiency of utilization of MEI for 1) maintenance, 2) milk production (kl), 3) growth (kg), and the efficiency of utilization of body stores for milk production (kt). Traditionally, these have been determined using linear regression methods to analyze energy balance data from calorimetry experiments. Many studies have highlighted a number of concerns over current energy feeding systems particularly in relation to these key parameters, and the linear models used for analyzing. Therefore, a database containing 652 dairy cow observations was assembled from calorimetry studies in the United Kingdom. Five functions for analyzing energy balance data were considered: straight line, two diminishing returns functions, (the Mitscherlich and the rectangular hyperbola), and two sigmoidal functions (the logistic and the Gompertz). Meta-analysis of the data was conducted to estimate kg and kt. Values of 0.83 to 0.86 and 0.66 to 0.69 were obtained for kg and kt using all the functions (with standard errors of 0.028 and 0.027), respectively, which were considerably different from previous reports of 0.60 to 0.75 for kg and 0.82 to 0.84 for kt. Using the estimated values of kg and kt, the data were corrected to allow for body tissue changes. Based on the definition of kl as the derivative of the ratio of milk energy derived from MEI to MEI directed towards milk production, MEm and kl were determined. Meta-analysis of the pooled data showed that the average kl ranged from 0.50 to 0.58 and MEm ranged between 0.34 and 0.64 MJ/kg of BW0.75 per day. Although the constrained Mitscherlich fitted the data as good as the straight line, more observations at high energy intakes (above 2.4 MJ/kg of BW0.75 per day) are required to determine conclusively whether milk energy is related to MEI linearly or not.     

Predicting energy balance for dairy cows using high-density single nucleotide polymorphism information

The objective of this study was to investigate the genetic basis of energy balance (EB) and the potential use of genomic selection to enable EB to be incorporated into selection programs. Energy balance provides an essential link between production and nonproduction traits because both depend on a common source of energy. A small number (527) of Dutch Holstein-Friesian heifers with phenotypes for EB were genotyped. Direct genomic values were predicted for these heifers using a model that included the genotypic information. A polygenic model was also applied to predict estimated breeding values using only pedigree information. A 10-fold cross-validation approach was employed to assess the accuracies of the 2 sets of predicted breeding values by correlating them with phenotypes. Because of the small number of phenotypes, accuracies were relatively low (0.29 for the direct genomic values and 0.21 for the estimated breeding values), where the maximum possible accuracy was the square root of heritability (0.57). Despite this, the genomic model produced breeding values with reliability double that of the breeding values produced by the polygenic model. To increase the accuracy of the genomic breeding values and make it possible to select for EB, measurement and recording of EB would need to improve. The study suggests that it may be possible to select for minimally recorded traits; for instance, those measured on experimental farms, using genomic selection. Overall, the study demonstrated that genomic selection could be used to select for EB, confirming its genetic background.     

Effect of dietary N-carbamoylglutamate on milk production and nitrogen utilization in high-yielding dairy cows

The objective of the current study was to investigate the effect of N-carbamoylglutamate (NCG) supplementation on milk production and nitrogen (N) utilization in Chinese Holstein dairy cows. Sixty multiparous cows (78 ± 17.3 d in milk, 635 ± 61.00 kg of body weight, and 41.9 ± 7.9 kg/d milk yield; mean ± SD) were blocked by parity, days in milk, and milk yield and randomly allocated to 1 of 4 groups, each of which was fed a dietary treatment containing 0 (control), 10, 20, or 30 g of NCG/d. Milk yield was recorded weekly. Dry matter intake, milk composition, plasma variables, and urea N contents in plasma, urine, and milk were determined every other week. Blood samples were collected from the coccygeal vein. Rumen microbial protein synthesis was estimated based on the purine derivatives in the urine. Dry matter intake was found to be similar between the treatments. Addition of 20 g of NCG/d tended to increase milk yield (40.2 vs. 38.1 kg/d) and increased the content (2.83 vs. 2.74%) and yield (1.12 vs. 1.02 kg/d) of milk protein compared with the control. The yield and content of milk fat were similar between the treatments, whereas the contents of lactose and total solids increased linearly with an increase in NCG. Dietary supplementation of NCG linearly increased the plasma nitric oxide level and decreased the plasma ammonia N level. Compared with the control, the plasma Arg concentration in cows fed 10, 20, and 30 g of NCG/d was increased by 1.1, 10.4, and 16.0%, respectively. The urea N concentrations in the milk, plasma, and urine decreased with the addition of NCG, although the lowest urea N concentrations were observed with the addition of 20 g of NCG/d. The conversion of dietary crude protein to milk protein exhibited quadratic trends of improvement by NCG supplementation, with a peak at 20 g of NCG/d. The rumen microbial protein synthesis was not altered by NCG supplementation, but the metabolizable protein tended to show a quadratic increase in cows fed 20 g of NCG/d. In conclusion, supplementation of 20 g of NVG/d may alter the plasma metabolites, optimize the AA profile, increase the metabolizable protein utilization, and thereby improve the lactation performance and N utilization of high-yielding dairy cows.     

Effect of varying dietary ratios of alfalfa silage to corn silage on production and nitrogen utilization in lactating dairy cows

Twenty-eight (8 ruminally cannulated) lactating, multiparous Holstein cows were blocked by DIM and randomly assigned to 7 replicated 4 × 4 Latin squares (28-d periods) to investigate the effects of different dietary ratios of alfalfa silage (AS) to corn silage (CS) on production, N utilization, apparent digestibility, and ruminal metabolism. The 4 diets contained (dry matter basis): A) 51% AS, 43% rolled high-moisture shelled corn (HMSC), and 3% solvent soybean meal (SSBM); B) 37% AS, 13% CS, 39% HMSC, and 7% SSBM; C) 24% AS, 27% CS, 35% HMSC, and 12% SSBM; and D) 10% AS, 40% CS, 31% HMSC, and 16% SSBM. Dietary crude protein contents were 17.2, 16.9, 16.6, and 16.2% for diets A, B, C, and D. All 4 diets were high in energy, averaging 49% nonfiber carbohydrates and 24% neutral detergent fiber. Intake of dry matter, yield of milk, 3.5% fat-corrected milk and fat, milk fat content, and apparent digestibility of neutral detergent fiber and acid detergent fiber all decreased linearly when CS replaced AS. Effects on fiber digestion and milk fat may have been due to increasing fluctuation in ruminal pH and time the pH remained <6.0 when CS replaced AS. Milk protein content increased linearly with increasing CS, but there were no differences in protein yield. There were linear increases in apparent N efficiency and decreases in N excreted in urine and feces when CS replaced AS. Production was depressed on the diet highest in CS. Quadratic analysis indicated that milk and protein yields were maximal at dietary AS:CS ratios of, respectively, 37:13 and 31:19. No diet minimized N excretion without negatively affecting production. Diet C, with an AS:CS ratio of 24:27, was the best compromise between improved N efficiency and sustained production. Because CS is complementary with AS, it is recommended that CS be fed in AS-based diets to maintain milk yield while improving N utilization.     

Energy profiling of dairy cows from routine milk mid-infrared analysis

The balance of body energy within and across lactations can have health and fertility consequences for the dairy cow. This study aimed to create a large calibration data set of dairy cow body energy traits across the cow's productive life, with concurrent milk mid-infrared (MIR) spectral data, to generate a prediction tool for use in commercial dairy herds. Detailed phenotypic data from 1,101 Holstein Friesian cows from the Langhill research herd (SRUC, Scotland) were used to generate energy balance (EB) and effective energy intake (EI), both in megajoules per day. Pretreatment of spectral data involved standardization to account for drift over time and machine. Body energy estimates were aligned with their spectral data to generate a prediction of these traits based on milk MIR spectroscopy. After data edits, partial least squares analysis generated prediction equations with a coefficient of determination from split sample 10-fold cross validation of 0.77 and 0.75 for EB and EI, respectively. These prediction equations were applied to national milk MIR spectra on over 11 million animal test dates (January 2013 to December 2016) from 4,453 farms. The predictions generated from these were subject to phenotypic analyses with a fixed regression model highlighting differences between the main dairy breeds in terms of energy traits. Genetic analyses generated heritability estimates for EB and EI ranging from 0.12 to 0.17 and 0.13 to 0.15, respectively. This study shows that MIR-based predictions from routinely collected national data can be used to generate predictions of dairy cow energy turnover profiles for both animal management and genetic improvement of such difficult and expensive-to-record traits.     

Effects of intraruminal urea-nitrogen infusions on feed intake,nitrogen utilization,and milk yield in dairy cows

The objective of this study was to determine the effects of supplementation of protein deficient diet with increasing amounts of urea-N on feed intake, milk yield, rumen fermentation, and nutrient digestibility in dairy cows. The hypothesis was that low rumen ammonia-N concentrations provide suboptimal conditions for rumen microbes and these conditions can be alleviated by urea-N that increases rumen ammonia-N concentrations. To evaluate this hypothesis, the diet was formulated slightly deficient with respect to rumen-degradable protein. To supplement the diet with rumen degradable N, 5 levels of urea-N (0, 17, 33, 49, and 66 g/d) were continuously infused into the rumen of 5 dairy cows according to a 5 × 5 Latin square. Increasing levels of urea-N infusion increased N intake and N excretion in urine and feces in a linear manner and tended to increase milk and milk protein yields. Feed intake and fiber digestibility were not affected by urea-N infusion levels. Rumen ammonia-N concentrations remained low (3.5 mg/100 mL) and did not respond to urea-N infusions levels between 0 to 49 g/d, whereas the highest level of urea-N (66 g/d) increased rumen ammonia-N concentration to 5.1 mg/100 mL (quadratic effect). These observations suggested that rumen microbes efficiently captured ammonia-N from rumen fluid until sufficient intracellular ammonia-N concentrations were attained, after which ammonia-N concentrations started to increase in extracellular rumen fluid. In contrast, milk urea-N concentrations increased in a curvilinear manner (cubic effect) from 4.4 to around 6 mg/100 mL for the medium levels of urea-N and then to 7.9 mg/100 mL for the highest level of urea-N infusion. The current results indicated that 18% of supplementary N intake was secreted in milk and 53% in urine. In spite of low rumen ammonia-N concentrations observed for the basal diet, it was estimated that only 43% of supplementary N was captured by rumen microbes. Estimated true digestibility for supplementary N (93%) provided further evidence that urea-N stimulated microbial N synthesis. The current results indicate that rumen ammonia-N concentration was an insensitive indicator of N deficiency at low levels of diet CP, whereas milk urea-N was responsive to diet CP concentrations at all urea-N infusion levels.     

On the use of milk composition measures to predict the energy balance of dairy cows

Milk composition varies with energy status and was proposed for measuring energy balance on-farm, but the accuracy of prediction using monthly samples is not high. With automated sampling and inline milk analysis, a much higher measurement frequency is possible, and thus improved accuracy of energy balance determination may be expected. Energy balance was evaluated using data in which milk composition was measured at each milking. Three breeds (Danish Holstein, Danish Red, and Jerseys) of cows (623 lactations from 299 cows) in parities 1, 2, and 3+ were used. Data were smoothed using a rolling local regression. Energy balance (EBal) was calculated from changes in body reserves (body weight and body condition score). The relationship between EBal and milk measures was quantified by partial least squares regression (PLS) using group means data. For each day in lactation, the within-breed and parity mean EBal and mean milk measures were used. Further PLS was done using the individual cow data. The initial PLS models included 25 combinations of milk measures allowing a range of nonlinear effects. These combinations were as follows: days in milk (DIM); DIM raised to the powers 2, 3, and 4; milk yield; fat content; protein content; lactose content; fat yield; protein yield; lactose yield; fat:protein ratio; fat:lactose ratio; protein:lactose ratio; and milk yield:lactose ratio, together with 10 “diff()” variables. These variables are the current minus the previous value of the milk measure in question. Using group means data, a very high proportion (96%) of the variability in EBal was explained by the PLS model. A reduced model with only 6 variables explained 94% of the variation in EBal. This model had a prediction error of 3.82 MJ/d; the 25-variable model had a prediction error of 3.11 MJ/d. When using individual rather than group means data, the PLS prediction error was 17.3 MJ/d. In conclusion, the mean Ebal of different parities of Holstein, Danish Red, and Jersey cows can be predicted throughout lactation using 1 common equation based on DIM, milk yield, milk fat, and milk protein measures.