Prediction of crude protein and amino acid passage to the duodenum of lactating cows by models compared with in vivo data

Ability of commercially available dairy ration programs to predict duodenal flows of protein and essential amino acids in dairy cows

The objective of this analysis was to compare the rumen submodel predictions of 4 commonly used dairy ration programs to observed values of duodenal flows of crude protein (CP), protein fractions, and essential AA (EAA). The literature was searched and 40 studies, including 154 diets, were used to compare observed values with those predicted by AminoCow (AC), Agricultural Modeling and Training Systems (AMTS), Cornell-Penn-Miner (CPM), and National Research Council 2001 (NRC) models. The models were evaluated based on their ability to predict the mean, their root mean square prediction error (RMSPE), error bias, and adequacy of regression equations for each protein fraction. The models predicted the mean duodenal CP flow within 5%, with more than 90% of the variation due to random disturbance. The models also predicted within 5% the mean microbial CP flow except CPM, which overestimated it by 27%. Only NRC, however, predicted mean rumen-undegraded protein (RUP) flows within 5%, whereas AC and AMTS underpredicted it by 8 to 9% and CPM by 24%. Regarding duodenal flows of individual AA, across all diets, CPM predicted substantially greater (>10%) mean flows of Arg, His, Ile, Met, and Lys; AMTS predicted greater flow for Arg and Met, whereas AC and NRC estimations were, on average, within 10% of observed values. Overpredictions by the CPM model were mainly related to mean bias, whereas the NRC model had the highest proportion of bias in random disturbance for flows of EAA. Models tended to predict mean flows of EAA more accurately on corn silage and alfalfa diets than on grass-based diets, more accurately on corn grain-based diets than on non-corn-based diets, and finally more accurately in the mid range of diet types. The 4 models were accurate at predicting mean dry matter intake. The AC, AMTS, and NRC models were all sufficiently accurate to be used for balancing EAA in dairy rations under field conditions.

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.

Metabolic Models of Ruminant Metabolism: Recent Improvements and Current Status

The NC-1009 regional research project has two broad goals of quantifying the properties of feeds and the metabolic interactions among nutrients that influence nutrient availability for milk production and that alter synthesis of milk, and using those quantitative relationships to challenge and refine computer-based nutrition systems for dairy cattle. The objective of this paper was to review progress in modeling. Significant progress has been made in model refinements over the past 10 yr as exemplified by the most recent NRC model (2001) and work on the Molly model of Baldwin and colleagues (1987). These models have different objectives but share many properties. The level of aggregation of the NRC model (2001) does not allow detailed analyses of specific metabolic reactions that affect nutritional efficiency. The Baldwin model is aggregated at the pathway level and is therefore amenable to assessment with a broad range of biological measurements. Recent improvements to that model include the addition of an ingredient based input scheme, use of in situ data to set ruminal protein degradation rates, and refinement of the representation of mammary cell numbers and activity. Although the Baldwin model appears to be appropriate structurally, several parameters are known to be inadequate. Predictions of ruminal N metabolism and total-tract starch digestions have similar accuracy as the NRC model. However, the NRC more accurately predicts total-tract fiber digestion and both models significantly overpredict total-tract lipid digestion. These errors contribute to overpredictions of weight retention when simulating full lactations with the Baldwin model and may result in performance prediction errors with the NRC model. Limitations remain in the descriptions of metabolism and metabolic regulation of the splanchnic, viscera, adipose tissue, body muscle, and mammary tissue. Integration of genetic control mechanisms can expand these efforts to assist genetic selection as well as feeding management decisions.

Development of a System to Predict Feed Protein Flow to the Small Intestine of Cattle

A data set constructed from research trials published between 1979 and 1998 was used to derive equations to adjust published tabular values for the rumen-undegradable protein (RUP) content of feeds to better predict the passage of nonammonia nonmicrobial N (NANMN) to the small intestine of lactating dairy cows. Both linear and nonlinear forms of equations were considered for making adjustments. Iterative processes were used to estimate equation parameters. A logistic equation was developed and considered to be the most optimal for adjustment of published tabular RUP contents of feeds. The equation is a function of dietary dry matter intake (DMI) and includes terms for tabular RUP and nonprotein N contents of individual feeds. The equation has a standard error of prediction of 69.29 g of NANMN/ d per cow and a root mean square prediction error of 104.63 g of NANMN/d per cow. Independent evaluation of the equation indicated that the concept of variable RUP content for feeds based on DMI is correct. Further refinements may be needed as other data become available to quantify the effects of additional factors on the RUP value of feeds.

Adaptations in Body Muscle and Fat in Transition Dairy Cattle Fed Differing Amounts of Protein and Methionine Hydroxy Analog

The objectives were to determine effects of prepartum protein intake and dietary amino acid balance on production, adaptations in body fat and protein, amino acid concentrations, and, indirectly, body protein breakdown in early lactation. Multiparous Holstein cows (n = 42) were fed diets containing 11 or 14% crude protein with or without 20 g/d of methionine hydroxy analog for 21 d prepartum and then fed a common diet of 17% crude protein for 120 d postpartum, with or without 50 g/d of methionine hydroxy analog. Dry matter intake postpartum averaged 25.4 kg and milk production 41.6 kg. Cows fed the 14% CP diet ate 0.7 kg more dry matter and gave 1.7 kg more milk than those fed the 11% diet postpartum, but this difference was not significant. Cows fed methionine hydroxy analog prepartum lost less body protein from -14 to 60 d in milk. From d 60 to 120, body fat increased 8.5 and 11.5 kg for low and high protein groups and body protein increased 0.5 and 1.0 kg. Serum concentrations of branched chain amino acids fell 17% in the first few weeks postpartum, lysine fell 15%, histidine fell 16%, methionine increased 20%, and cysteine increased 30%. The ratio of serum 3-methylhistidine to creatinine was determined to indicate muscle protein degradation. An increase in this ratio at 7 d postpartum indicated increased body protein breakdown, there was no effect of prepartum ration. Increased protein intake prepartum may allow more feed intake and milk production postpartum, and supplementing a methionine analog on a ration already balanced in methionine by contemporary models may spare body protein.