Updating the Cornell Net Carbohydrate and Protein System feed library and analyzing model sensitivity to feed inputs

Abstract

The Cornell Net Carbohydrate and Protein System (CNCPS) is a nutritional model that evaluates the environmental and nutritional resources available in an animal production system and enables the formulation of diets that closely match the predicted animal requirements. The model includes a library of approximately 800 different ingredients that provide the platform for describing the chemical composition of the diet to be formulated. Each feed in the feed library was evaluated against data from 2 commercial laboratories and updated when required to enable more precise predictions of dietary energy and protein supply. A multistep approach was developed to predict uncertain values using linear regression, matrix regression, and optimization. The approach provided an efficient and repeatable way of evaluating and refining the composition of a large number of different feeds against commercially generated data similar to that used by CNCPS users on a daily basis. The protein A fraction in the CNCPS, formerly classified as nonprotein nitrogen, was reclassified to ammonia for ease and availability of analysis and to provide a better prediction of the contribution of metabolizable protein from free AA and small peptides. Amino acid profiles were updated using contemporary data sets and now represent the profile of AA in the whole feed rather than the insoluble residue. Model sensitivity to variation in feed library inputs was investigated using Monte Carlo simulation. Results showed the prediction of metabolizable energy was most sensitive to variation in feed chemistry and fractionation, whereas predictions of metabolizable protein were most sensitive to variation in digestion rates. Regular laboratory analysis of samples taken on-farm remains the recommended approach to characterizing the chemical components of feeds in a ration. However, updates to the CNCPS feed library provide a database of ingredients that are consistent with current feed chemistry information and laboratory methods and can be used as a platform to formulate rations and improve the description of biology within the model.

Kinetics of digestion of low-quality forage grazed by beef cattle fed supplements containing increasing levels of rumen undegradable protein

“…The separation of the rumen-fill effect of each fraction (D and I) according to Waldo et al (1972), allows for a combined evaluation of the interaction effects of the passage and digestion kinetics on the fiber filling effect at the rumen compartment (Van Soest, 1994;Vieira et al, 2000a,b). Besides, other important quantitative variables in the feeds can be estimated, such as the energy availability and daily amount of metabolizable protein, which enables the prediction of animal performance based on known dietary inputs (Vieira et al, 2000c;Jardim et al, 2013;Jardim et al, 2015;Higgs et al, 2015). In the present study (Table 4), the average RF(I) was approximately 32% greater than RF(D), a situation that was also observed by Vieira et al (2000b) based on extrusa samples taken from a tropical grassland.…”

“…Therefore, the variability of this fraction in the pasture is difficult to predict, e.g., Vieira et al (2000a) analyzed esophageal extrusa samples collected from a natural grassland containing U. decumbens and found 11 g kg −1 DM in the dry season and 40 g kg −1 DM in the rainy season. That variability led Higgs et al (2015) to state that in loco evaluation of the protein fractions of the forage resources is the first strategy to predict animal performance more accurately if the feed library does not contain robust estimates of the feed resources available.…”

“…Besides, the prediction of metabolizable protein is most sensitive to digestion rates of protein fractions, and the laboratory analysis of the available forages and feeds used in the production system is the recommended approach to characterize feed resources. In the CNCPS, the metabolizable protein depends on digestion and passage rates and fractions such as soluble protein, ammonia, neutral detergent insoluble protein, and acid detergent insoluble protein (Higgs et al, 2015). Highly degradable true protein sources improve energy and amino acid supplies for ruminants grazing tropical forages, but their presence in the diet increases N excretion (Hentz et al, 2012).…”

In Vitro Yield of Microbial-N from Fermentation of Glucogenic and Lipogenic Diets Provided by Different Sources of Rumen Degradable Amino Acids

“…In addition, microbial-N production was also determined. In order to evaluate the degradation potential of the amino acid sources, nitrogen fractionation [14] was used. The results indicated that F was more rumen degradable than SB as fraction A 2 in this amino acid provider was higher than that in SB.…”

“…Sodium sulfite and heat stable alpha amylase were not used in the NDF and ADF assays, and were expressed without residual ash. Nitrogen fractionation was carried out as described by Higgs et al [14]. Briefly, the proteins of SBM and Fortid ® were divided into five fractions, namely A 1 , A 2 B 1 , B 2 and C. The A 1 fraction is made up of ammonia, and calculated by: Ammonia × (SP/100) × (CP/100) (% of CP); where SP is the soluble protein and CP is the crude protein.…”