Ability of three dairy feed evaluation systems to predict postruminal outflows of amino acids in dairy cows: A meta-analysis

Adequate prediction of postruminal outflows of essential AA (EAA) is the starting point of balancing rations for EAA in dairy cows. The objective of this meta-analysis was to compare the performance of 3 dairy feed evaluation systems (National Research Council [NRC], Cornell Net Protein and Carbohydrate System version 6.5.5 [CNCPS], and National Academies of Sciences, Engineering and Medicine [NASEM]) to predict EAA outflows (Trp was not tested). The data set included a total of 354 treatment means from 70 duodenal and 24 omasal studies. To avoid Type I error, mean and linear biases were considered of concern if statistically significant and representing > 5.0% of the observed mean. Analyses were conducted on raw observed values and on observations adjusted for the random effect of study. The analysis on raw data indicates the ability of the feed evaluation system to predict absolute values whereas the analysis on adjusted values indicates its ability to predict responses of EAA outflows to dietary changes. For the prediction of absolute values (based on raw data), NRC underpredicted outflows of all EAA, from 5.3 to 8.6% of the observed mean (%obs.mean) except for Leu, Lys, and Val; NASEM overpredicted Lys (10.8%obs.mean); and CNCPS overpredicted Arg, His, Lys, Met, and Val (5.2 to 26.0%obs.mean). No EAA had a linear bias of concern with NASEM, followed by NRC for His (6.8%obs.mean), and CNCPS for all EAA (5.6 to 12.2%obs.mean) except Leu, Phe, and Thr. On the other hand, for the prediction of responses to dietary changes (based on adjusted data), NRC had 2 EAA presenting a linear bias of concern, followed by NASEM and CNCPS with 4 and 6 EAA, respectively. Predictions of His showed a linear bias of concern (5.3 to 9.6%obs.mean) with the 3 feed evaluation systems. Measured chemistry of crude protein and EAA were reported for 1 or more feed ingredients of the ration in 36% of the studies, and resulted in decreased linear biases in the 3 feed evaluation systems. The difference in mean biases of Met outflows was systematically positive when comparing omasal versus duodenal studies. Predictions of Met outflows with NRC had a higher concordance correlation coefficient in duodenal (used to develop NRC equations) versus omasal studies, whereas the opposite was observed with CNCPS, the latter showing the lowest mean bias for Met in omasal sampling studies. The 30% difference in Met mean biases between sampling sites appeared related to a similar difference found for observed Met versus NAN outflows between duodenal and omasal studies, which is independent of predictions. In conclusion, NRC and NASEM yielded accurate predictions of EAA outflows, with a small superiority of NASEM to predict absolute values, and slight superiority of NRC to predict the responses to dietary changes. In comparison, CNCPS may present mean and linear biases of concern for many EAA. Moreover, it remains to determine which sampling site is more representative of the true supply of EAA to the cows.

Predicting orthophosphate in feces and manure from dairy cattle

Dairy cattle excreta are a valuable source of orthophosphate (Ortho-P), an inorganic form of phosphorus (P) that is readily available for microorganisms, plant growth, and development. There is, however, a growing environmental concern about the potential negative environmental impact of excessive amounts of Ortho-P excretion, which can lead to the eutrophication of water bodies. As a result, the development of mathematical equations to quantify and manage Ortho-P excretion on dairy farms could prove valuable for environmental sustainability. This study aimed to use literature data to develop empirical predictions for Ortho-P (g/kg dry matter [DM]) excretion using total P (TP [g/kg DM]) content of dairy cattle feces (Ortho-Pf) and manure (Ortho-Pm). Data sets from studies that evaluated and characterized the different forms of P in feces and manure from dairy cattle were compiled. After outlier exclusion, the final retained database for feces included 37 treatment means from 4 published papers while the manure comprised 23 treatment means from 7 published papers. A linear-mixed model was used to develop the predictive equations, incorporating the random effect of the study. A leave-one-out cross-validation procedure was used to evaluate the predictive ability of the developed models, whereby studies were regarded as folds. The fecal equation was determined as Ortho-Pf (g/kg DM) = -2.447 (0.572) + 0.966 (0.083) × TP (g/kg DM) (R2 = 0.79) and resulted in a root mean square prediction error as a percentage of mean observed value (RMSPE, %) of 32.8% and error due to random sources of 97.6%. Additionally, the manure equation was determined as Ortho-Pm (g/kg) = -0.204 (0.446) + 0.590 (0.065) × TP (g/kg) (R2 = 0.77) and had an RMSPE of 43.3% with a random error of 93.9%. Both models revealed minimal mean and slope biases on feces and manure data. Findings suggest that these sets of equations can be used to estimate excreted Ortho-P from total excreted P, helping nutritionists and farmers to understand the impact of dietary P changes on the environment. Further, these equations can be incorporated into extant models such as the Cornell Net Carbohydrate and Protein System (CNCPS) to aid in understanding and mitigating P and Ortho-P excretion from dairy cattle and to clarify the portion of P that migrates more rapidly into watersheds.

Ability of three dairy feed evaluation systems to predict postruminal outflows of nitrogenous compounds in dairy cows: A meta-analysis

Adequate prediction of postruminal outflow of protein fractions is the starting point for the determination of metabolizable protein supply in dairy cows. The objective of this meta-analysis was to compare the performance of 3 dairy feed evaluation systems (National Research Council [NRC], Cornell Net Protein and Carbohydrate System [CNCPS], and National Academies of Sciences, Engineering and Medicine [NASEM]) to predict outflows (g/d) of nonammonia nitrogren (NAN), microbial N (MiN), and nonammonia nonmicrobial N (NANMN). Predictions of rumen degradabilities (% of nutrient) of protein (RDP), NDF, and starch were also evaluated. The data set included 1,294 treatment means from 312 digesta flow studies. The 3 feed evaluation systems were compared using the concordance correlation coefficient (CCC), the ratio of root mean square prediction error (RMSPE) on standard deviation of observed values (RSR), and the slope between observed and predicted values. Mean and linear biases were deemed biologically relevant and are discussed if higher than a threshold of 5% of the mean of observed values. The comparisons were done on observed values adjusted or not for the study effect; the adjustment had a small effect on the mean bias but the linear bias reflected a response to a dietary change rather than absolute predictions. For the absolute predictions of NAN and MiN, CNCPS had the best-fit statistics (8% greater CCC; 6% lower RMSPE) without any bias; NRC and NASEM underpredicted NAN and MiN, and NASEM had an additional linear bias indicating that the underprediction of MiN increased at increased predictions. For NANMN, fit statistics were similar among the 3 feed evaluation systems with no mean bias; however, the linear bias with NRC and CNCPS indicated underprediction at low predictions and overprediction at elevated predictions. On average, the CCC were smaller and RSR ratios were greater for MiN versus NAN indicating increased prediction errors for MiN. For NAN responses to a dietary change, CNCPS also had the best predictions, although the mean bias with NASEM was not biologically relevant and the 3 feed evaluation systems did not present a linear bias. However, CNCPS, but not the 2 other feed evaluation systems, presented a linear bias for MiN, with responses being overpredicted at increased predictions. For NANMN, responses were overpredicted at increased predictions for the 3 feed evaluation systems, but to a lesser extent with NASEM. The site of sampling had an effect on the mean bias of MiN and NANMN in the 3 feed evaluation systems. The mean bias of MiN was higher in omasal than duodenal studies in the 3 feed evaluation systems (from 55 to 61 g/d) and this mean bias was twice as large when 15N labeling was used as a microbial marker compared with purines. Such a difference was not observed for duodenal studies. The reasons underlying these systematic differences are not clear as the type of measurements used in the current meta-analysis does not allow to delineate if one site or one microbial marker is yielding the "true" postruminal N outflows. Rumen degradabilities of protein was underpredicted with CNCPS, and RDP responses to a dietary change was underpredicted by the 3 feed evaluation systems with increased RDP predictions. Rumen degradability of NDF was underpredicted and had poor fit statistics for NASEM compared with CNCPS. Fit statistics were similar between CNCPS and NASEM for rumen degradability of starch, but with an underprediction of the response with NASEM and absolute values being overpredicted with CNCPS. Multivariate regression analyses showed that diet characteristics were correlated with prediction errors of N outflows in each feed evaluation system. Globally, compared with NAN and NANMN, residuals of MiN were correlated with several moderators in the 3 feed evaluation systems reflecting the complexity to measure and model this outflow. In addition, residuals of NANMN were correlated positively with RDP suggesting an overestimation of this parameter. In conclusion, although progress is still to be made to improve equations predicting postruminal N outflows, the current feed evaluation systems provide sufficient precision and accuracy to predict postruminal outflows of N fractions.

Enteric Methane Emissions Prediction in Dairy Cattle and Effects of Monensin on Methane Emissions: A Meta-Analysis

Greenhouse gas emissions, such as enteric methane (CH₄) from ruminant livestock, have been linked to global warming. Thus, easily applicable CH₄ management strategies, including the inclusion of dietary additives, should be in place. The objectives of the current study were to: (i) compile a database of animal records that supplemented monensin and investigate the effect of monensin on CH₄ emissions; (ii) identify the principal dietary, animal, and lactation performance input variables that predict enteric CH₄ production (g/d) and yield (g/kg of dry matter intake DMI); (iii) develop empirical models that predict CH₄ production and yield in dairy cattle; and (iv) evaluate the newly developed models and published models in the literature. A significant reduction in CH₄ production and yield of 5.4% and 4.0%, respectively, was found with a monensin supplementation of ≤24 mg/kg DM. However, no robust models were developed from the monensin database because of inadequate observations under the current paper's inclusion/exclusion criteria. Thus, further long-term in vivo studies of monensin supplementation at ≤24 mg/kg DMI in dairy cattle on CH₄ emissions specifically beyond 21 days of feeding are reported to ensure the monensin effects on the enteric CH₄ are needed. In order to explore CH₄ predictions independent of monensin, additional studies were added to the database. Subsequently, dairy cattle CH₄ production prediction models were developed using a database generated from 18 in vivo studies, which included 61 treatment means from the combined data of lactating and non-lactating cows (COM) with a subset of 48 treatment means for lactating cows (LAC database). A leave-one-out cross-validation of the derived models showed that a DMI-only predictor model had a similar root mean square prediction error as a percentage of the mean observed value (RMSPE, %) on the COM and LAC database of 14.7 and 14.1%, respectively, and it was the key predictor of CH₄ production. All databases observed an improvement in prediction abilities in CH₄ production with DMI in the models along with dietary forage proportion inclusion and the quadratic term of dietary forage proportion. For the COM database, the CH₄ yield was best predicted by the dietary forage proportion only, while the LAC database was for dietary forage proportion, milk fat, and protein yields. The best newly developed models showed improved predictions of CH₄ emission compared to other published equations. Our results indicate that the inclusion of dietary composition along with DMI can provide an improved CH₄ production prediction in dairy cattle.

Balancing dairy cattle diets for rumen nitrogen and methionine or all essential amino acids relative to metabolizable energy

Improving the ability of diet formulation models to more accurately predict AA supply while appropriately describing requirements for lactating dairy cattle provides an opportunity to improve animal productivity, reduce feed costs, and reduce N intake. The goal of this study was to evaluate the sensitivity of a new version of the Cornell Net Carbohydrate and Protein System (CNCPS) to formulate diets for rumen N, Met, and all essential AA (EAA). Sixty-four high-producing dairy cattle were randomly assigned to 1 of the 4 following diets in a 14-wk longitudinal study: (1) limited metabolizable protein (MP), Met, and rumen N (Base), (2) adequate Met but limited MP and rumen N (Base + M), (3) adequate Met and rumen N, but limited MP (Base + MU), and (4) adequate MP, rumen N, and balanced for all EAA (Positive). All diets were balanced to exceed requirements for ME relative to maintenance and production, assuming a nonpregnant, 650-kg animal producing 40 kg of milk at 3.05% true protein and 4.0% fat. Dietary MP was 97.2, 97.5, 102.3, and 114.1 g/kg of dry matter intake for the Base, Base + M, Base + MU, and Positive diets, respectively. Differences were observed for dry matter intake and milk yield (24.1 to 24.7 and 39.4 to 41.1 kg/d, among treatments). Energy corrected milk, fat, and true protein yield were greater (2.9, 0.13, and 0.08 kg/d, respectively) in cows fed the Positive compared with the Base diet. Using the updated CNCPS, cattle fed the Base, Base + M, and Base + MU diets were predicted to have a negative MP balance (-231, -310, and -142 g/d, respectively), whereas cattle fed the Positive diet consumed 33 g of MP/d excess to ME supply. Bacterial growth was predicted to be depressed by 16 and 17% relative to adequate N supply for the Base and Base + M diets, respectively, which corresponded with the measured lower apparent total-tract NDF degradation. The study demonstrates that improvements in lactation performances can be achieved when rumen N and Met are properly supplied and further improved when EAA supply are balanced relative to requirements. Formulation using the revised CNCPS provided predictions for these diets, which were sensitive to changes in rumen N, Met, all EAA, and by extension MP supply.

Eucalcemia during lipopolysaccharide challenge in postpartum dairy cows: II. Calcium dynamics

Hypocalcemia induced by immune activation is a conserved response among mammals. Early postpartum cows will experience decreased circulating Ca concentrations following acute immune activation; however, the cause for decreased Ca concentration is unknown. Our objectives were to (1) describe Ca dynamics following an intravenous (IV) LPS challenge in early postpartum cows, and (2) compare inflammatory-induced changes in Ca dynamics between IV Ca-treated cows and control cows. Cows (n = 14, 8 ± 1 d in milk) were enrolled in a matched-pair randomized controlled design to receive IV Ca (IVCa) in a eucalcemic clamp for 12 h, or 0.9% NaCl (CTRL) following an IV LPS infusion (0.040 or 0.045 µg of LPS/kg of body weight over 1 h). During the 24 h following LPS infusion, circulating concentrations of parathyroid hormone and serotonin were measured, serum and urine samples were collected to calculate urinary fractional excretion of Ca (FECa), and fecal samples were collected to calculate Ca apparent digestibility (ADCa) using amylase-treated and ash-corrected undigested neutral detergent fiber after 240 h (uNDFom₂₄₀) as an internal marker. Changes in Ca intake and milk Ca secretion were also quantified and compared with baseline values. Cows were fasted during challenge and dry matter intake was 20 ± 5% less than baseline values on the day of challenge and did not differ between groups. On the day of challenge, milk Ca concentration increased, but milk yield decreased such that total Ca secreted in milk did not change from baseline. Urine FECa was low overall, but an interaction of treatment and time was identified such that FECa increased in IVCa but decreased in CTRL. Concentrations of parathyroid hormone increased and serotonin decreased following challenge. Fecal dry matter decreased from baseline, but did not differ between 6, 12, and 24 h, and did not differ between groups. An interaction of treatment and time was identified for ADCa and apparent digestibility of dry matter such that digestibility was decreased in CTRL but not IVCa at 6 h. Acute immune activation induced hypocalcemia in CTRL, and although urinary Ca excretion was not a primary cause, it is unclear to what degree hypocalcemia was due to altered ADCa. Eucalcemia appeared to alter adaptations in Ca homeostasis during immune activation as FECa was increased in IVCa animals.

Rumen metabolism, omasal flow of nutrients, and microbial dynamics in lactating dairy cows fed fresh perennial ryegrass (Lolium perenne L.) not supplemented or supplemented with rolled barley grain

The objective of this study was to evaluate the effect of rolled barley grain (RB) supplementation on rumen metabolism, omasal flow of nutrients, and microbial dynamics in lactating dairy cows fed fresh perennial ryegrass (Lolium perenne L.; PRG)-based diets. Ten ruminally cannulated Holstein cows averaging (mean ± standard deviation) 49 ± 23 d in milk and 513 ± 36 kg of body weight were assigned to 1 of 2 treatments in a switchback design. The treatment diets were PRG only (G) or PRG plus 3.5 kg of dry matter RB (G+RB). The study consisted of three 29-d periods where each period consisted of 21 d of diet adaptation and 8 d of data and sample collection. A double marker system was used to quantify nutrient flow entering the omasal canal along with labeled ¹⁵N-ammonium sulfate to measure bacterial, protozoal, and nonmicrobial N flow. Rumen evacuation techniques were used to determine nutrient and microbial pool size, allowing the calculation of fractional rates of digestion and microbial growth. There was no difference in daily milk yield or energy-corrected milk yield between treatments. Milk fat concentration and milk urea N decreased, whereas milk protein concentration increased in cows fed the G+RB diet. During the omasal sampling phase, dry matter intake was higher in cows fed the G+RB diet. Ruminal and total-tract neutral detergent fiber digestibility was lower in G+RB cows; however, no difference was observed in reticulorumen pH. The rumen pool size of fermentable carbohydrate was increased in cows fed the G+RB diet; however, the fractional rate of digestion was decreased. Flow of nonammonia N and bacterial N at the omasal canal increased in cows fed the G+RB diet compared with the G diet. Protozoa N flow was not different between diets; however, protozoa appeared to supply a much larger amount of microbial N and exhibited shorter generation time than previously considered. Feed N ruminal digestibility, corrected for microbial contribution, was similar for both treatments (88.4 and 89.0% for G and G+RB, respectively). In conclusion, RB supplementation did not benefit overall animal performance; however, it reduced ruminal neutral detergent fiber digestibility and increased bacterial N flow. The results demonstrate the large dependence of cows consuming PRG-based diets on microbial N as the main source of nonammonia N supply. Additional quantitative research is required to further describe the supply of nutrients and microbial dynamics in cows consuming PRG-based diets in an effort to determine most limiting nutrients.

Intake and growth in transported Holstein calves classified as diarrheic or healthy within the first 21 days after arrival in a retrospective observational study

Strategies that can improve health and maximize growth in the preweaning period should improve the subsequent production and longevity of replacement animals. Few data are available that quantify feed and water consumption, as well as growth, in healthy versus non-healthy calves—the objective of this study. A database of Holstein calves (<1 wk of age; n = 313) was developed to compare calves that developed diarrhea in the first 21 d after arrival from commercial farms to the research facility versus calves that remained healthy. Individual calf data from 4 experiments included daily intake of milk replacer, free water, electrolyte solution, and starter grain, as well as weekly body weight (BW) and frame measures for 21 d after arrival. Calves with a fecal score of >2 for ≥3 consecutive days over the first 21 d of each experiment were retrospectively classified as diarrheic (DIA; n = 96); the remainder were classified as healthy (HEA; n = 217). Other health issues were minimal. The likelihood of elevated fecal score occurrence and the cumulative number of days with an elevated score were greater for DIA calves than for HEA calves. The initial total protein concentration in blood did not differ between classifications. Cumulative milk replacer dry matter intake (DMI) and water consumed from milk replacer were significantly less for DIA calves than for HEA calves, because DIA calves were more likely to refuse milk replacer. Cumulative starter DMI was decreased for DIA versus HEA calves. As a result, cumulative total DMI was significantly less for DIA calves than for HEA calves. Cumulative free water intake did not differ between classifications. The DIA calves were more likely to receive electrolyte solution and have more days given electrolyte solution than HEA calves. As a result, total cumulative intake of electrolyte solution was greater in DIA calves than in HEA calves. Cumulative total water intake did not differ between classifications. Initial BW did not differ between classifications; however, a classification × time interaction for BW indicated that HEA calves were heavier than DIA calves and had greater ADG. Significant classification × time interactions for hip height and heart girth revealed that HEA calves had a larger frame size. Gain–feed ratios for both milk replacer intake and total DMI differed between classifications: DIA calves were less feed-efficient than HEA calves. In conclusion, diarrhea in young calves decreases DMI, BW gain, and feed efficiency relative to HEA calves within 21 d of arrival.