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Journal ArticleDOI

A net carbohydrate and protein system for evaluating cattle diets: II. Carbohydrate and protein availability.

TLDR
The Cornell Net Carbohydrate and Protein System has a submodel that predicts rates of feedstuff degradation in the rumen, the passage of undegraded feed to the lower gut, and the amount of ME and protein that is available to the animal.
Abstract
The Cornell Net Carbohydrate and Protein System (CNCPS) has a submodel that predicts rates of feedstuff degradation in the rumen, the passage of undegraded feed to the lower gut, and the amount of ME and protein that is available to the animal. In the CNCPS, structural carbohydrate (SC) and nonstructural carbohydrate (NSC) are estimated from sequential NDF analyses of the feed. Data from the literature are used to predict fractional rates of SC and NSC degradation. Crude protein is partitioned into five fractions. Fraction A is NPN, which is trichloroacetic (TCA) acid-soluble N. Unavailable or protein bound to cell wall (Fraction C) is derived from acid detergent insoluble nitrogen (ADIP), and slowly degraded true protein (Fraction B3) is neutral detergent insoluble nitrogen (NDIP) minus Fraction C. Rapidly degraded true protein (Fraction B1) is TCA-precipitable protein from the buffer-soluble protein minus NPN. True protein with an intermediate degradation rate (Fraction B2) is the remaining N. Protein degradation rates are estimated by an in vitro procedure that uses Streptomyces griseus protease, and a curve-peeling technique is used to identify rates for each fraction. The amount of carbohydrate or N that is digested in the rumen is determined by the relative rates of degradation and passage. Ruminal passage rates are a function of DMI, particle size, bulk density, and the type of feed that is consumed (e.g., forage vs cereal grain).

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Citations
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Journal ArticleDOI

Effect of total mixed ration composition on amino acid profiles of different fractions of ruminal microbes in vitro.

TL;DR: Multiple linear regression analysis did not show that the content of a certain nutrient or the inclusion rate of single feedstuffs could be used to predict the amino acid profile of microbial protein with an adequate level of accuracy.
Journal ArticleDOI

Níveis de proteína bruta em dietas para bovinos de corte: parâmetros ruminais, balanço de compostos nitrogenados e produção de proteína microbiana

TL;DR: Ruminal passage rate, abomasal flow of N compounds as well as microbial efficiency were not affected by different dietary crude protein levels while nitrogen balance expressed in g/day increased linearly when the crude protein content increased from 10.5% to 15% in the diet.
Journal ArticleDOI

Composição bromatológica da silagem de capim-elefante com diferentes proporções de casca desidratada de maracujá (Passiflora edulis Sims f. flavicarpa)

TL;DR: The chemical composition of elephant grass silages containing different inclusion levels (0, 10, 20 and 30%) of dried passion fruit peel -CMD - in elephant grass is described in this article.
Journal ArticleDOI

Review: Nutritive evaluation of forages by near infrared reflectance spectroscopy

TL;DR: In this paper, the main reference methods that have been used in order to achieve proper calibration of NIR spectroscopy are reviewed with the intention of increasing the potential of the NIR Spectroscopy potential in this area.
References
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Journal ArticleDOI

Methods for dietary fiber, neutral detergent fiber, and nonstarch polysaccharides in relation to animal nutrition.

TL;DR: In addition to NDF, new improved methods for total dietary fiber and nonstarch polysaccharides including pectin and beta-glucans now are available and are also of interest in rumen fermentation.
Journal ArticleDOI

A net carbohydrate and protein system for evaluating cattle diets: I. Ruminal fermentation.

TL;DR: The Cornell Net Carbohydrate and Protein System (CNCPS) has a kinetic submodel that predicts ruminal fermentation and the protein-sparing effect of ionophores is accommodated by decreasing the rate of peptide uptake by 34%.
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