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

Digestion kinetics of dried cereal grains

Grain fermentability largely determines the feed value of grains for ruminants. Our objective was to evaluate the variation in kinetics of gas production of cereal grains and the relationship among gas production, chemical composition and feed value. Eighteen barley, 99 corn, 23 sorghum, and 57 wheat samples were fermented in vitro for 48 h. Gas production was measured with a computerized system and an exponential model was fitted to the data. The impact of the variation in composition and kinetics on the feed value of grains in feedlot rations was assessed with the Cornell Net Carbohydrate and Protein System (CNCPS). Fractional gas rates were significantly different between grains (P\u3c0.001), with a mean and S.D. of 0.24 (0.029) h-1 for barley (n=20), 0.15 (0.026) h-1 for corn (n=98), 0.06 (0.016) h-1 for sorghum (n=23) and 0.26 (0.039) h-1 for wheat (n=57). Fermentation rates were more variable than the chemical components. Fractional rates were poorly correlated with chemical composition within grain with the highest correlations for acid detergent insoluble crude protein (ADICP) (r=-0.31, P\u3c0.01) and ADF (r=-0.27, P\u3c0.01) for corn and neutral detergent insoluble crude protein (NDICP) (r=0.35, P\u3c0.05) for wheat. The impact of the variation in composition and kinetics on the feed value of grains in feedlot rations was assessed. The CNCPS predicted a maximal variation of \u3c2.1 MJ/day and \u3c60 g/day in metabolizable energy (ME) and metabolizable protein (MP) supply from grains, respectively. For sorghum, the fermentation rate was predicted to be a major determinant of the site of starch fermentation. A detailed evaluation of feed values for grains needs to include information on rates of fermentation

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

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

A revised CNCPS feed carbohydrate fractionation scheme for formulating rations for ruminants

Balancing ruminant diets for appropriate levels and types of dietary carbohydrates (CHO) is necessary to maximize production while assuring the health of the animals. Several feed fractions (i.e., volatile fatty acids (VFA), lactate, sugars, starch) are now being measured in some commercial feed laboratories and this information may assist in better formulating diets. A CHO fractionation scheme based on ruminal degradation characteristics needed for nutritional models is described and its impact on predictions with the Cornell Net Carbohydrate and Protein System (CNCPS) is assessed. Dietary CHO are divided into eight fractions: the CA1 is volatile fatty acids (VFA), CA2 is lactic acid, CA3 is other organic acids, CA4 is sugars, CB1 is starch, CB2 is soluble fiber, CB3 is available neutral detergent fiber (NDF), and CC is unavailable NDF. A Monte Carlo analysis was conducted with an example lactating dairy cow ration to compare the original CNCPS CHO scheme (CA=sugars and organic acids, CB1=starch and soluble fiber, CB2=available NDF, CC=unavailable NDF) with the developed CHO scheme. A database was used to obtain distributions and correlations of the feed inputs used in the schemes for the ingredients of the ration (corn and grass silages, high moisture corn, soybean meal, and distillers\u27 grains). The CHO fractions varied in a decreasing order as VFAs, soluble fiber, lactic acid, sugar, NDF, starch, and total non-fiber carbohydrates (NFC). Use of the expanded scheme in the CNCPS decreased the microbial CP production, which was sensitive (standard regression coefficient in parenthesis) to corn silage starch (0.55), grass silage NDF rate (0.46), high moisture corn grain starch rate (0.44), and corn silage NDF rate (0.33). Predicted ruminal NFC digestibility remained similar. The expanded CHO scheme provides a more appropriate feed description to account for variation in changes in silage quality and diet NFC composition. However, to fully account for differences in feed CHO utilization, further improvements in the methodology used to estimate the fractions and their corresponding degradation rates, inclusion of dietary factors in dry matter intake predictions, and prediction of ruminal VFA production and pH are necessary

Tracing the origin of the East-West population admixture in the Altai region (Central Asia)

A recent discovery of Iron Age burials (Pazyryk culture) in the Altai Mountains of Mongolia may shed light on the mode and tempo of the generation of the current genetic east-west population admixture in Central Asia. Studies on ancient mitochondrial DNA of this region suggest that the Altai Mountains played the role of a geographical barrier between West and East Eurasian lineages until the beginning of the Iron Age. After the 7th century BC, coinciding with Scythian expansion across the Eurasian steppes, a gradual influx of East Eurasian sequences in Western steppes is detected. However, the underlying events behind the genetic admixture in Altai during the Iron Age are still unresolved: 1) whether it was a result of migratory events (eastward firstly, westward secondly), or 2) whether it was a result of a local demographic expansion in a 'contact zone' between European and East Asian people. In the present work, we analyzed the mitochondrial DNA lineages in human remains from Bronze and Iron Age burials of Mongolian Altai. Here we present support to the hypothesis that the gene pool of Iron Age inhabitants of Mongolian Altai was similar to that of western Iron Age Altaians (Russia and Kazakhstan). Thus, this people not only shared the same culture (Pazyryk), but also shared the same genetic east-west population admixture. In turn, Pazyryks appear to have a similar gene pool that current Altaians. Our results further show that Iron Age Altaians displayed mitochondrial lineages already present around Altai region before the Iron Age. This would provide support for a demographic expansion of local people of Altai instead of westward or eastward migratory events, as the demographic event behind the high population genetic admixture and diversity in Central Asia