Development of a mechanistic model to represent the dynamics of particle flow out of the rumen and to predict rate of passage of forage particles in dairy cattle.

A mechanistic and dynamic model was developed to represent physiological aspects of particle dynamics in the reticulo-rumen (RR) and to predict rate of passage out of the RR (Kp) of forage particles quantitatively. The model consists of 2 conceptual pools with 3 spatial compartments of particles; the compartment the particle enters is based on functional specific gravity (FSG). The model assumes 2 major pressure gradient-driven flows of particles out of the RR through the reticulo-omasal orifice between 2 consecutive primary reticular contractions. One is associated with the second phase of primary reticular contraction and involves propulsion of particles in the vicinity of the honeycomb structure of the reticulum from the RR. The second flow involves movement of particles in the reticulum without selection by size. Particle outflow rate was assumed to be proportional to liquid outflow rate. The passage coefficient, defined as the ratio of particle to liquid outflow rate, was estimated for each particle group by an equation derived from the probability of passage based on FSG and particle size. Particles retained on a 1.18-mm screen were defined as large particles. When the model was evaluated with 41 observations in an independent database, it explained 66% of the variation in observed Kp of forage particles with a root mean square prediction error of 0.009. With 16 observations that also included measurements of liquid passage rate, the model explained 81 and 86% of the variation in observed Kp liquid and Kp forage, respectively. An analysis of model predictions using a database with 455 observations indicated that the assumptions underlying the model seemed to be appropriate to describe the dynamics of forage particle flow out of the RR. Sensitivity analysis showed that probability of a particle being in the pool likely to escape is most critical in the passage of large forage particles, whereas the probability of being in the reticulum as well as in the likely to escape pool is important in the passage of small forage and concentrate particles. The FSG of a particle is more important in determining the fate of a particle than its size although they are correlated, especially for forage particles. We conclude that this model can be used to understand the factors that affect the dynamics of particle flow out of the RR and predict Kp of particles out of the RR in dairy cattle.

Predicting milk and forage intake of nursing calves.

A theoretical model was developed to predict forage intake of nursing calves based on peak milk level (PML) and BW using data from 39 Holstein steer calves individually fed for 200 d with milk replacer reconstituted to equal the fat and protein contents of beef cow milk. Treatment levels were amounts of reconstituted milk allowed per day based on lactation curves, which were based on PML of 2.72, 5.44, 8.16, 10.88, and 13.6 kg/d, respectively. Chopped alfalfa hay was offered for ad libitum intake to allow maximum voluntary forage consumption in addition to the reconstituted milk. We observed that calves receiving increased amounts of milk (10.88 to 13.66 kg of milk/d at peak) consumed little forage during the first 60 d of age. Their consumption of forage was also less than those calves receiving reduced quantities of milk (2.72 to 5.44 kg of peak milk/d) at the same BW because milk intake was prioritized. The forage DMI of the calf depended on calf BW and quality of the forage. Furthermore, calf BW and forage DMI was correlated with calf milk intake. A significant (P < 0.05) relationship between total DE intake (DEI) and BW was identified. A theoretical model was developed to predict forage DMI of nursing calves based on total DEI. The total DEI was estimated using PML and BW. Equations were developed to adjust forage DMI for DE content of the forage. A sensitivity analysis using Monte Carlo simulation indicated that forage DMI of grazing, nursing calves is likely to be less than 4.26 kg/d 95% of the time and that variation in BW and PML have the greatest impact on forage DMI. We concluded that equations developed in this study can be used to evaluate different cow-calf production scenarios, including matching forage quality and availability with dam milk production potential.

Improved feed protein fractionation schemes for formulating rations with the cornell net carbohydrate and protein system.

Adequate predictions of rumen-degradable protein (RDP) and rumen-undegradable protein (RUP) supplies are necessary to optimize performance while minimizing losses of excess nitrogen (N). The objectives of this study were to evaluate the original Cornell Net Carbohydrate Protein System (CNCPS) protein fractionation scheme and to develop and evaluate alternatives designed to improve its adequacy in predicting RDP and RUP. The CNCPS version 5 fractionates CP into 5 fractions based on solubility in protein precipitant agents, buffers, and detergent solutions: A represents the soluble nonprotein N, B1 is the soluble true protein, B2 represents protein with intermediate rates of degradation, B3 is the CP insoluble in neutral detergent solution but soluble in acid detergent solution, and C is the unavailable N. Model predictions were evaluated with studies that measured N flow data at the omasum. The N fractionation scheme in version 5 of the CNCPS explained 78% of the variation in RDP with a root mean square prediction error (RMSPE) of 275 g/d, and 51% of the RUP variation with RMSPE of 248 g/d. Neutral detergent insoluble CP flows were overpredicted with a mean bias of 128 g/d (40% of the observed mean). The greatest improvements in the accuracy of RDP and RUP predictions were obtained with the following 2 alternative schemes. Alternative 1 used the inhibitory in vitro system to measure the fractional rate of degradation for the insoluble protein fraction in which A = nonprotein N, B1 = true soluble protein, B2 = insoluble protein, C = unavailable protein (RDP: R(2) = 0.84 and RMSPE = 167 g/d; RUP: R(2) = 0.61 and RMSPE = 209 g/d), whereas alternative 2 redefined A and B1 fractions as the non-amino-N and amino-N in the soluble fraction respectively (RDP: R(2) = 0.79 with RMSPE = 195 g/d and RUP: R(2) = 0.54 with RMSPE = 225 g/d). We concluded that implementing alternative 1 or 2 will improve the accuracy of predicting RDP and RUP within the CNCPS framework.

Nitrogen transactions along the gastrointestinal tract of cattle: A meta-analytical approach.

In ruminant animals, endogenous N (EN) secretions contribute to meeting the N requirement of the ruminal microflora. The EN also constitutes a sizable portion of the duodenal N flow, which might be available to the host animal. Most measures of EN have been accomplished with highly invasive techniques or unusual semisynthetic diets. By utilizing a statistical approach and data obtained from studies reporting duodenal, ileal, and fecal N flows in cattle, the EN losses and true digestibility of N were estimated for different segments of the gastrointestinal tract of cattle. A simulation for a reference diet (24.2 g of N/kg of OM, 32% NDF and carbohydrates of medium fermentation rate) consumed at 2% of BW daily estimated that the minimal contribution of EN to the N available in the rumen was 39%. The free EN represented 13% of the duodenal N flow, and when bacterial N of EN origin was considered, EN contributed 35% of the total N flow. The minimal entry of EN into various segments of the gastrointestinal tract was also estimated as: foregut, 10.54; small intestine, 3.10; and hindgut, 5.0 g/kg of OMI. Rumen dietary N degradability was 0.68, and true N digestibilities in the small intestine and hindgut were 0.75 and 0.49, respectively. A better understanding of the factors involved in EN losses will allow for a more accurate estimation of both N supply and N requirements. This will translate into improved accuracy of diet formulation and less N excreted into the environment.

Development of a mechanistic model to represent the dynamics of liquid flow out of the rumen and to predict the rate of passage of liquid in dairy cattle.

A mechanistic and dynamic model was developed to represent the physiological aspects of liquid dynamics in the rumen and to quantitatively predict liquid flow out of the reticulorumen (RR). The model is composed of 2 inflows (water consumption and salivary secretion), one outflow (liquid flow through the reticulo-omasal orifice (ROO), and one in-and-out flow (liquid flux through the rumen wall). We assumed that liquid flow through the ROO was coordinated with the primary reticular contraction, which is characterized by its frequency, duration, and amplitude during eating, ruminating, and resting. A database was developed to predict each component of the model. A random coefficients model was used with studies as a random variable to identify significant variables. Parameters were estimated using the same procedure only if a random study effect was significant. The input variables for the model were dry matter intake, body weight, dietary dry matter, concentrate content in the diet, time spent eating, and time spent ruminating. Total water consumption (kg/d) was estimated as 4.893 x dry matter intake (kg/d), and 20% of the water consumed by drinking was assumed to bypass the RR. The salivary secretion rate was estimated to be 210 g/min during chewing. During ruminating, however, the salivation rate was assumed to be adjusted for the proportion of liquid in the rumen. Resting salivation was exponentially related to dry matter intake. Liquid efflux through the rumen wall was assumed to be the mean value in the database (4.6 kg/h). The liquid outflow rate (kg/h) was assumed to be a product of the frequency of the ROO opening, its duration per opening, and the amount of liquid passed per opening. Simulations of our model suggest that the ROO may open longer for each contraction cycle than had been previously reported (about 3 s) and that it is affected by dry matter intake, body weight, and total digesta in the rumen. When compared with 28 observations in 7 experiments, the model accounted for 40, 70, and 90% of the variation, with root mean square prediction errors of 9.25 kg, 1.84 kg/h, and 0.013 h(-1) for liquid content in the rumen, liquid outflow rate, and fractional rate of liquid passage, respectively. A sensitivity analysis showed that dry matter intake, followed by body weight and time spent eating, were the most important input variables for predicting the dynamics of liquid flow from the rumen. We conclude that this model can be used to understand the factors that affect the dynamics of liquid flow out of the rumen and to predict the fractional rate of liquid passage from the RR in dairy cattle.

Evaluation of protein fractionation systems used in formulating rations for dairy cattle.

Production efficiency decreases when diets are not properly balanced for protein. Sensitivity analyses of the protein fractionation schemes used by the National Research Council Nutrient Requirement of Dairy Cattle (NRC) and the Cornell Net Carbohydrate and Protein System (CNCPS) were conducted to assess the influence of the uncertainty in feed inputs and the assumptions underlying the CNCPS scheme on metabolizable protein and amino acid predictions. Monte Carlo techniques were used. Two lactating dairy cow diets with low and high protein content were developed for the analysis. A feed database provided by a commercial laboratory and published sources were used to obtain the distributions and correlations of the input variables. Spreadsheet versions of the models were used. Both models behaved similarly when variation in protein fractionation was taken into account. The maximal impact of variation on metabolizable protein from rumen-undegradable protein (RUP) was 2.5 (CNCPS) and 3.0 (NRC) kg/d of allowable milk for the low protein diet, and 3.5 (CNCPS) and 3.9 (NRC) kg/d of allowable milk for the high protein diet. The RUP flows were sensitive to ruminal degradation rates of the B protein fraction in NRC and of the B2 protein fraction in the CNCPS for protein supplements, energy concentrates, and forages. Absorbed Met and Lys flows were also sensitive to intestinal digestibility of RUP, and the CNCPS model was sensitive to acid detergent insoluble crude protein and its assumption of complete unavailability. Neither the intestinal digestibility of the RUP nor the protein degradation rates are routinely measured. Approaches need to be developed to account for their variability. Research is needed to provide better methods for measuring pool sizes and ruminal digestion rates for protein fractionation systems.

Accounting for energy and protein reserve changes in predicting diet-allowable milk production in cattle.

Current ration formulation systems used to formulate diets on farms and to evaluate experimental data estimate metabolizable energy (ME)-allowable and metabolizable protein (MP)-allowable milk production from the intake above animal requirements for maintenance, pregnancy, and growth. The changes in body reserves, measured via the body condition score (BCS), are not accounted for in predicting ME and MP balances. This paper presents 2 empirical models developed to adjust predicted diet-allowable milk production based on changes in BCS. Empirical reserves model 1 was based on the reserves model described by the 2001 National Research Council (NRC) Nutrient Requirements of Dairy Cattle, whereas empirical reserves model 2 was developed based on published data of body weight and composition changes in lactating dairy cows. A database containing 134 individually fed lactating dairy cows from 3 trials was used to evaluate these adjustments in milk prediction based on predicted first-limiting ME or MP by the 2001 Dairy NRC and Cornell Net Carbohydrate and Protein System models. The analysis of first-limiting ME or MP milk production without adjustments for BCS changes indicated that the predictions of both models were consistent (r(2) of the regression between observed and model-predicted values of 0.90 and 0.85), had mean biases different from zero (12.3 and 5.34%), and had moderate but different roots of mean square errors of prediction (5.42 and 4.77 kg/d) for the 2001 NRC model and the Cornell Net Carbohydrate and Protein System model, respectively. The adjustment of first-limiting ME- or MP-allowable milk to BCS changes improved the precision and accuracy of both models. We further investigated 2 methods of adjustment; the first method used only the first and last BCS values, whereas the second method used the mean of weekly BCS values to adjust ME- and MP-allowable milk production. The adjustment to BCS changes based on first and last BCS values was more accurate than the adjustment to BCS based on the mean of all BCS values, suggesting that adjusting milk production for mean weekly variations in BCS added more variability to model-predicted milk production. We concluded that both models adequately predicted the first-limiting ME- or MP-allowable milk after adjusting for changes in BCS.

Using ultrasound measurements to predict body composition of yearling bulls.

Carcass traits have been successfully used to determine body composition of steers. Body composition, in turn, has been used to predict energy content of ADG to compute feed requirements of individual animals fed in groups. This information is used in the Cornell value discovery system (CVDS) to predict DM required (DMR) for the observed animal performance. In this experiment, the prediction of individual DMR for the observed performance of group-fed yearling bulls was evaluated using energy content of gain, which was based on ultrasound measurements to estimate carcass traits and energy content of ADG. One hundred eighteen spring-born purebred and crossbred bulls (BW = 288 +/- 4.3 kg) were sorted visually into 3 marketing groups based on estimated days to reach USDA low Choice quality grade. The bulls were fed a common high-concentrate diet in 12 slatted-floor pens (9 to 10 head/pen). Ultrasound measurements including back-fat (uBF), rump fat, LM area (uLMA), and intramuscular fat were taken at approximately 1 yr of age. Carcass measurements including HCW, backfat over the 12th to 13th rib (BF), marbling score (MRB), and LM area (LMA) were collected for comparison with ultrasound data for predicting carcass composition. The 9th to 11th-rib section was removed and dissected into soft tissue and bone for determination of chemical composition, which was used to predict carcass fat and empty body fat (EBF). The predicted EBF averaged 23.7 +/- 4.0%. Multiple regression analysis indicated that carcass traits explained 72% of the variation in predicted EBF (EBF = 16.0583 + 5.6352 x BF + 0.01781 x HCW + 1.0486 x MRB - 0.1239 x LMA). Because carcass traits are not available on bulls intended for use as herd sires, another equation using predicted HCW (pHCW) and ultrasound measurements was developed (EBF = 39.9535 x uBF - 0.1384 x uLMA + 0.0867 x pHCW - 0.0897 x uBF x pHCW - 1.3690). This equation accounted for 62% of the variation in EBF. The use of an equation to predict EBF developed with steer composition data overpredicted the EBF predicted in these experiments (28.7 vs. 23.7%, respectively). In a validation study with 37 individually fed bulls, the use of the ultrasound-based equation in the CVDS to predict energy content of gain accounted for 60% of the variation in the observed efficiency of gain, with 1.5% bias, and identified 3 of the 4 most efficient bulls.

Evaluation of the passage rate equations in the 2001 Dairy NRC model.

Dairy ration formulation to meet protein and amino acid requirements with the National Research Council Nutrient Requirements of Dairy Cattle (NRC, 2001) model depends on accuracy of predicting feed passage rates out of the rumen. The NRC (2001) passage rate (Kp) equations were evaluated for validity and sensitivity to input variables in predicting supplies of rumen degraded protein, rumen undegraded protein, and metabolizable protein. The database used in the development of the 3 Kp equations (for dry forage, wet forage, and concentrate) was used to independently derive the 3 equations using a meta-analysis technique. To extract quantitative relationships between statistically significant input variables and rate of passage, a random coefficients model that used each study effect as a random variable was used. The database was comprised of studies that only used rare earth markers. Outliers were identified by acceptance criteria defined a priori or the difference in fit statistic (DFFITS) value; 319, 63, and 139 treatment means were used to develop the Kp equations for dry forage, wet forage, and concentrate, respectively. We found that the sign of the regression coefficient for concentrate content in diet dry matter in the equation for Kp dry forage was inverted; it should be positive. A sensitivity analysis was conducted with a spreadsheet version of the NRC (2001) model developed for this study, using the Monte Carlo technique. The sensitivity analysis indicated that all Kp predictions were the most sensitive to variation in DM intake, and thus accurate measurement of DM intake is the most important factor in predicting Kp. Predictions for protein supply (rumen degraded protein, rumen undegraded protein, and metabolizable protein) were sensitive to variability in amount of feed crude protein (CP, %DM), digestion rate (Kd) of the B fraction of feed CP (%/h), and the Kp for concentrate (%/h), due to the high proportion of dietary CP in lactating dairy rations coming from concentrates. The sensitivity analysis indicated that accurate determinations of DMI, the Kd of the B fraction of feed CP, and feed CP are the most important variables needed to predict MP supply in lactating dairy cows with the NRC (2001) model. We conclude that the empirical Kp equations in the model are suitable for predicting passage rate in lactating dairy cows. More accurate predictions of Kp will require the development of a more mechanistic model that accounts for more of the biologically important variables (e.g., physical property of particles, liquid flow, and timely variation of intake) affecting passage rate.

Identifying differences in feed efficiency among group-fed cattle.

Identification of efficient animals in the postweaning growth phase for use in selection for improved feed efficiency is important to improve the economic and environmental sustainability of the beef cattle industry. Progeny testing using group-fed animals in commercial feedlots is the most common and practical method used to evaluate postweaning growth on large numbers of animals. We developed the Cornell Value Discovery System (CVDS) to dynamically predict growth rate, accumulated weight, days required to reach target body composition, carcass weight, and composition of individual beef cattle fed in group pens. Observed BW, ADG, BW at 28% empty body fat (EBF), breed type, environmental conditions, and dietary ME concentration are used by the CVDS to predict, for each animal in a pen, the feed DM required for maintenance (FFM), the feed DM required for gain, and the total DM required for maintenance and gain (DMR). The CVDS then computes DMR-to-ADG ratio (DMR:ADG), which is a feed conversion measure, and ADG-to-DMR ratio (ADG:DMR), which is a feed efficiency measure, for each animal. This study used the observed F:G ratio of 362 individually fed steers to evaluate CVDS-predicted indicators of feed efficiency and the Kleiber ratio. A subset of 37 data points was used to evaluate residual feed intake (RFI) as an indicator of feed efficiency. The database included 4 published studies, each with detailed individual animal description, environment, diet, and body composition information. The CVDS-predicted DMR:ADG accounted for 84% of the variation in the actual F:G ratio with a mean bias of 1.94% (P = 0.20). The predicted FFM to actual DMI ratio had a high correlation with actual ADG (R2 = 0.76), and indicated a decay-type nonlinear dilution of FFM as ADG increased. The CVDS-predicted ADG:DMR and the Kleiber ratio had a significant (R2 = 0.88) logarithmic relationship. In an analysis of a contemporary group within the database, RFI was highly correlated with the F:G ratio (r = 0.71). There was a positive relationship between RFI and EBF. The RFIM (DMI - DMR) was moderately correlated with DMI and ADG (0.37 and -0.38; respectively), suggesting that selecting for low RFI(M) would decrease DMI and increase ADG in this database. We conclude that the CVDS model can be used to identify differences in the F:G and G:F ratios by predicting DMR for individual growing cattle fed in groups.

The effect of milk intake on forage intake and growth of nursing calves.

Thirty-nine Holstein steer calves were assigned to one of five treatments at birth and individually fed for 200 d with milk replacer reconstituted to equal the fat and protein concentration of beef cow milk. Treatment levels were the quantities of reconstituted milk fed per day based on lactation curves, which were based on peak milk levels (PML) of 2.72, 5.44, 8.16, 10.88, and 13.6 kg/d, respectively. In addition to reconstituted milk, chopped alfalfa hay was offered ad libitum to allow for maximal voluntary forage consumption. All calves were fed a high-energy diet postweaning until they reached a similar degree of fatness in the 12th rib (4 to 5% chemical fat) as determined by ultrasound. There were differences (P < 0.05) among groups in weaning weight, preweaning ADG, age, and weight at slaughter. During the preweaning phase, there was a linear relationship (P < 0.01) for daily milk and forage DE intake; however, DE intake per unit of BW did not differ across treatments (P = 0.06). Increasing PML resulted in a linear (P < 0.01) decrease in alfalfa hay intake in the preweaning phase, and G:F increased quadratically (P < 0.01). During the postweaning phase, preweaning milk intake had no meaningful effect on postweaning ADG, but overall ADG had a linear relationship (P < 0.01) with preweaning milk level. There was no effect of PML on the 12th-rib lipid percent, marbling score, or quality grade, but protein and fat concentration in the carcass and empty BW increased linearly (P < 0.01) with PML. The group fed at 2.72 kg/d PML was 58 kg lighter (P = 0.03) and required 34 d more (P < 0.01) to reach the predetermined degree of fatness at slaughter than the group fed at 13.6 kg/d PML, suggesting that increased milk production by the dam can decrease the number of days to the slaughter weight at which a similar rib lipid concentration is reached.

Phosphorus reduction through precision feeding of dairy cattle.

A study was conducted on 4 dairy farms in the Cannonsville Reservoir Basin (Delaware County, NY) to identify feeding strategies in commercial dairy herds that will reduce manure phosphorus and mass farm phosphorus balance. Lactating cow diets on all 4 farms were evaluated monthly for 28 mo using the Cornell Net Carbohydrate and Protein System. Milk production and herd reproductive performance were measured monthly. Manure phosphorus content was measured every 6 mo. Reduced phosphorus diets (precision feeding) were implemented in 2 of the herds. Mean herd phosphorus intakes in the 4 herds ranged from 107 to 165% of requirement. Dietary phosphorus intakes in the 2 herds where diets were modified were reduced from 153% of requirement to 111%, an average reduction of 25%. Predicted phosphorus intakes and manure excretions were reduced 11.8 kg/yr per cow. After dietary adjustments in the 2 herds, fecal phosphorus concentrations decreased 33%. Milk production was not adversely affected by reduced phosphorus diets. Whole farm mass phosphorus balances (amount of phosphorus remaining on the farm) on the 2 farms were reduced 49%, with the percentage of imported phosphorus remaining on the farm reduced to less than 45%. Achieving feed phosphorus reductions similar to those of this study on all of the estimated 7000 to 8000 mature dairy cattle in the Cannonsville Basin could reduce feed phosphorus imports and manure phosphorus excretions more than 64,000 kg/yr. This would slow the rate of phosphorus accumulation in agricultural soils in the Cannonsville Basin, which over time could reduce the 50,000 kg/yr average total phosphorus loading of the Cannonsville Reservoir.

A mechanistic model for predicting the nutrient requirements and feed biological values for sheep.

The Cornell Net Carbohydrate and Protein System (CNCPS), a mechanistic model that predicts nutrient requirements and biological values of feeds for cattle, was modified for use with sheep. Published equations were added for predicting the energy and protein requirements of sheep, with a special emphasis on dairy sheep, whose specific needs are not considered by most sheep-feeding systems. The CNCPS for cattle equations that are used to predict the supply of nutrients from each feed were modified to include new solid and liquid ruminal passage rates for sheep, and revised equations were inserted to predict metabolic fecal N. Equations were added to predict fluxes in body energy and protein reserves from BW and condition score. When evaluated with data from seven published studies (19 treatments), for which the CNCPS for sheep predicted positive ruminal N balance, the CNCPS for sheep predicted OM digestibility, which is used to predict feed ME values, with no mean bias (1.1 g/100 g of OM; P > 0.10) and a low root mean squared prediction error (RMSPE; 3.6 g/100 g of OM). Crude protein digestibility, which is used to predict N excretion, was evaluated with eight published studies (23 treatments). The model predicted CP digestibility with no mean bias (-1.9 g/100 g of CP; P > 0.10) but with a large RMSPE (7.2 g/100 g of CP). Evaluation with a data set of published studies in which the CNCPS for sheep predicted negative ruminal N balance indicated that the model tended to underpredict OM digestibility (mean bias of -3.3 g/100 g of OM, P > 0.10; RMSPE = 6.5 g/100 g of OM; n = 12) and to overpredict CP digestibility (mean bias of 2.7 g/100 g of CP, P > 0.10; RMSPE = 12.8 g/100 g of CP; n = 7). The ability of the CNCPS for sheep to predict gains and losses in shrunk BW was evaluated using data from six studies with adult sheep (13 treatments with lactating ewes and 16 with dry ewes). It accurately predicted variations in shrunk BW when diets had positive N balance (mean bias of 5.8 g/d; P > 0.10; RMSPE of 30.0 g/d; n = 15), whereas it markedly overpredicted the variations in shrunk BW when ruminal balance was negative (mean bias of 53.4 g/d, P < 0.05; RMSPE = 84.1 g/d; n = 14). These evaluations indicated that the Cornell Net Carbohydrate and Protein System for Sheep can be used to predict energy and protein requirements, feed biological values, and BW gains and losses in adult sheep.

Production and economic potentials of cattle in pasture-based systems of the western Amazon region of Brazil.

Our objectives were to evaluate strategies to improve productivity and economic returns from beef and dual-purpose cattle systems based on data collected on one dual-purpose (Bos taurus x Bos indicus) and two beef (Nellore) cattle farms in the western Amazon region of Brazil. Forage chemical composition and digestion rates of carbohydrate fractions of grazed Brachiaria decumbens and Brachiaria brizantha cv. Marandu grasses and Pueraria phaseoloides (tropical kudzu) legume were measured monthly during a 9-mo period from the end of one dry season to the end of the subsequent rainy season. Measurements of milk and growth responses to grazing these forages were used to predict animal productivity responses to dietary nutrient availability throughout an annual cycle. The ME available for gain in our simulations was always more limiting than metabolizable protein. The predicted ME available for gain was 0.50 kg/d for steers grazing B. brizantha and 0.40 kg/d for finishing steers grazing B. decumbens. Grasses contained more NDF and neutral detergent insoluble protein and less ME (P < 0.05) in the rainiest months than in the less rainy season, which resulted in 20% less predicted weight gain by growing steers (P < 0.05). Supplementation with sorghum grain was required to increase milk production and growth by 25 or 50% per animal, respectively, but this strategy was less profitable than current forage-only diets. Greater productivity of land and labor from higher stocking indicated greater net margins for beef production, but not for milk. This study suggested that more intensive beef production by judicious fertilization of grass-legume pastures and greater stocking density is the preferable strategy for owners of these cattle systems to improve economic returns under current conditions. It also might help decrease the motivation for additional forest clearing.

The effect of a ruminal nitrogen (N) deficiency in dairy cows: evaluation of the cornell net carbohydrate and protein system ruminal N deficiency adjustment.

Twenty-four multiparous and fifteen first lactation Holstein cows averaging 263 days in milk and weighing 614 kg were fed diets adequate or deficient in ruminal nitrogen (N), based on predictions of the Cornell Net Carbohydrate and Protein System (CNCPS). After adjustment to a low crude protein (CP) total mixed rations (TMR; 12.6% CP), the cows were allocated to 13 blocks based on lactation number, milk production, body condition score, and body weight. Within each block, cows were randomly assigned to one of the 3 treatment (TRT) diets (9.4, 11.1 and 14.1% CP for TRT 1, 2, and 3, respectively). All diets contained the same proportion of high moisture corn, chopped grass hay, and minerals, with urea substituted for corn silage as needed to reach the three CP levels. The TRT diets were then fed to the cows for 4 wk. Milk production was significantly affected by TRT: 15.5, 18.8, and 21.7 kg/d for TRT diets 1, 2, and 3, respectively. DMI was increased significantly as the percentage of CP increased from 9.4 to 14.1% CP: 17.6, 20.0, and 21.2 kg/d for TRT diets 1,2, and 3, respectively. CNCPS predictions for production (with and without the N adjustment for ruminal N deficiency) of metabolizable protein (MP) allowable milk were compared with observed milk production. Using the average individual weekly cow data from all 3 TRT, we found that the CNCPS accounted for 72 and 68% of the variation in MP allowable milk without and with the N deficiency adjustment, respectively. The overall mean bias without the N adjustment was 3.3 kg of milk (over prediction model bias of 14.6%, P < 0.001), and the N adjustment reduced the model over-prediction bias to 0.01 kg of milk (P = 0.96).

The effects of implant strategy on finished body weight of beef cattle.

We summarized experimental data to quantify the change in final BW due to a particular implant strategy when cattle are adjusted to the same final body composition. The database developed for this study included 13 implant trials involving a total of 13,640 animals (9,052 steers and 4,588 heifers). Fifteen different implant strategies were used among these trials, including no implant (control), single implants, and combinations of implants. Individual carcass data collected at slaughter were used to calculate the adjusted final shrunk BW at 28% empty body fat (AFBW) for each treatment group within a trial, then the implant treatments were grouped into categories according to their effect on weight at 28% empty body fat (four groups for steers and two groups for heifers). All differences in AFBW between categories were significant (P < 0.01), indicating an incremental anabolic implant dose response in AFBW over unimplanted animals. Values for AFBW ranged from 520 kg in unimplanted steers to 564 kg in steers implanted and reimplanted with Revalor-S. For heifers, AFBW ranged from 493 kg in unimplanted heifers to 535 kg in heifers implanted and reimplanted with Revalor-H. After accounting for differences in mean BW and composition of gain, implanted steers and heifers had 4.2 and 3.1% higher apparent diet ME values, respectively. Increasing the anabolic implant dose increases the weight at which animals reach a common body composition. This study indicates that anabolic implant response is due to a combination of a reduced proportion of the DMI required for maintenance, reduced energy content of gain, and efficiency of use of absorbed energy.

Energy requirement for maintenance and growth of Nellore bulls and steers fed high-forage diets.

Data from three comparative slaughter experiments with individually fed Nellore bulls (n = 31) and steers (n = 66) were utilized to determine their NEm and NEg requirements when fed high-forage diets. The experimental design provided ranges in ME intake, BW, and ADG for the development of regression equations to predict NEm and NEg requirements. The Nellore bulls (Trial 1) were divided into two intake levels (ad libitum and 65% of the ad libitum). The steers (Trials 2 and 3) were allocated to three intake levels (ad libitum and 55 and 70% of the ad libitum). In both trials, there were three slaughter groups within each intake level. The three end points for the bulls were different days on treatment (100, 150, and 190 d and 130, 180, and 200 d, respectively, for older and younger animal subgroups). The steers were slaughtered when animals of the ad libitum treatment reached 400, 440, and 480 kg shrunk BW (SBW) on average for the first, second, and third group, respectively. For all body composition determinations, whole empty body components were weighed, ground, and subsampled for chemical analysis. In each of the trials, initial body composition was determined with equations developed from a baseline slaughter group, using SBW and empty BW (EBW), fat (EBF), and protein (EBP) as variables. The NEm was similar for bulls and steers; NEm averaged 77.2 kcal/ kg0.75 EBW. However, the efficiency of conversion of ME to net energy for maintenance was greater for steers than for bulls (68.8 and 65.6%, respectively), indicating that bulls had a greater ME requirement for maintenance than steers (5.4%; P < 0.05). Our analyses do not support the NRC (2000) conclusion that Nellore, a Bos indicus breed, has a lower net energy requirement for maintenance than Bos taurus breeds. An equation developed with the pooled data to predict retained energy (RE) was similar to the NRC (2000) equation. A second equation was developed to predict RE adjusted for degree of maturity (u): RE = (6.45 - 2.58/u) x EWG x e(0.469) x u), where u = current EBW/final EBW in which final EBW was 365 kg for steers and younger bulls and 456 kg for older bulls at 22% EBF, respectively.

Predicting individual feed requirements of cattle fed in groups.

A published model designed to predict individual feed required for the observed shrunk BW and ADG of growing cattle when fed in groups was modified and evaluated to improve its accuracy. This model is needed to accurately bill feed and compute cost of gain in marketing programs based on individual animal management. Because of its importance in predicting energy required for growth, a database of 401 steers was used to develop an equation to predict percentage of empty-body fat (EBF) from carcass measurements (12th rib fat thickness, hot carcass weight, USDA quality grade, and longissimus muscle area), which accounted for 61% of the variation in EBF with no bias (P > 0.1). When tested with an independent data set of 951 steers, the equation accounted for 51% of the variation with 1% proportional bias. The large variation in the carcass measurements at a particular EBF observed in this study indicates further improvement is limited by the inability of carcass measurements to account for variation in fat distribution in the various carcass components. Because of its importance in setting the target end point, a database of 1,355 steers and heifers was used to determine the relationship between EBF and USDA quality grade. These data indicate growing and finishing cattle reach Select and low-Choice quality grades at an EBF of 26.15 +/- 0.19 and 28.61 +/- 0.20%, respectively (P < 0.05). A data set of 228 steers from different breeds from two serial slaughter studies indicated 14.26 +/- 1.52 kg of empty BW change are required to increase EBF one percentage unit for cattle fed high-energy diets; this adjustment is needed to adjust final shrunk BW to the target EBF end point. The model to predict DM required with modifications developed in this study was evaluated with data from 365 individually fed cattle and it accounted for 74% of the variation in observed DM consumed with no bias (P > 0.1). When the revised model was applied to a commercial feedlot data set containing 12,105 steers and heifers, the total observed DM consumed was predicted with a bias of less than 1%. The model presented in this study accounts for differences known to affect animal requirements (breed type, BW and ADG, and weight at the target EBF end point) and can be used to fairly allocate feed to individuals fed in a group under commercial feedlot conditions.

Effect of monensin on the performance and nitrogen utilization of lactating dairy cows consuming fresh forage.

We conducted a lactation trial with a fresh forage diet in order to evaluate 1) the effects of monensin on nitrogen metabolism, and 2) the Cornell Net Carbohydrate and Protein System (CNCPS). Thirty Holstein cows in midlactation (eight fitted with ruminal fistulas) were gradually introduced to a fresh forage diet. A concentrate mix based on corn meal was fed before the a.m. and p.m. milking times 0730 and 1730 h, then the fresh forage was fed at 0830 and 1830 h. Fifteen cows each were allocated to a control (no monensin) and a treatment group receiving 350 mg/cow per day of monensin in the p.m. concentrate feeding. A 7-d fecal and urine collection period and a 3-d rumen sampling period were conducted with the fistulated cows. After the lactation study was concluded, the fistulated cows were fed forage regrowth and a 3-d rumen sampling period was repeated. Monensin increased milk production by 1.85 kg. Milk fat and protein concentrations decreased and milk fat and protein yields increased, but the effects were nonsignificant. Monensin did not significantly affect DMI. Ruminal ammonia and the acetate-to-propionate ratio decreased with the addition of monensin in both fed forages. Monensin decreased fecal N output, and increased apparent N digestibility by 5.4%. Because of the decrease in ruminal ammonia and increase in apparent N digestibility, we concluded monensin was sparing amino acids from wasteful rumen degradation with a fresh forage diet. The precision of the CNCPS in predicting performance was high (r2 = 0.76), and the bias was low (overprediction of 3.6%). These results indicate that the CNCPS can be used for dairy cows consuming fresh forage and gives realistic predictions of performance.

Optimization of rate and efficiency of dietary nitrogen utilization through the use of animal by-products and(or) urea and their effects on nutrient digestion in Holstein steers.

The objective of this N balance study was to determine the potential for improving the efficiency and rate of dietary N utilization in Holstein steers by feeding an amino acid-balanced mixture of animal by-product protein sources in combination with urea. The Beef NRC 1996 Model Level 2 was used to formulate a corn-based (86:14 concentrate-hay) control diet with soybean meal as the primary N supplement that would provide ME and metabolizable protein (MP) allowable ADG of 1.4 kg in 250-kg steers with an estrogenic implant and fed an ionophore. A combination of porcine meat and bone meal, fish meal, hydrolyzed feather meal, and blood meal was also formulated as an undegradable intake protein (UIP) blend to complement those amino acids (AA) derived from microbial protein synthesis. Four steers with an average initial BW of 259 kg were assigned in a 4 x 4 Latin square design to treatments consisting of control, two levels of UIP inclusion (2.6 and 5.2%; DM basis) in combination with urea, and a negative control "urea diet" containing no UIP and no SBM. The steers were fed at hourly intervals 95% of ad libitum intake and were injected with 500 microg of estradiol-17beta twice daily. Nitrogen intakes were 155, 160, 162, and 145 g/d, and N balances were 47, 51, 42, and 47 g/d when the 0, 2.6, 5.2% UIP and the urea diets were fed, respectively. Nitrogen balance was reduced with the 5.2% UIP diet (P < 0.05), and was less than the capacity estimate derived from abosmasal casein infusion studies. Apparent N digestibilities averaged 69%, but DM, OM, and nonstructural carbohydrate digestibilities were significantly reduced for the urea diet. Feeding 5.2% UIP in the diet reduced (P < 0.05) the biological value from 46 to 38%, which was accompanied by a significant elevation of plasma urea N. Results indicate that genetic capacity for N retention was approximately 51 g/d. Results demonstrate that use of an AA-balanced blend of animal by-product protein sources did not improve the efficiency of dietary N usage when added to corn-based diets formulated with the Beef NRC 1996 Model Level 2 to meet nutrient requirements of rapidly growing steers. Using urea as the only N supplement achieved equal rate and efficiency of N use.