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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

Nutrient variation and availability of wheat DDGS, corn DDGS and blend DDGS from bioethanol plants

TL;DR: In this article, the authors compared different types of DDGS and different bioethanol plants in terms of: (1) chemical profiles; (2) mineral concentrations of sulfur (S), calcium (Ca), and phosphorus (P); (3) protein and carbohydrate subfractions associated with different degradation rates; (4) digestible component nutrients and energy values; and (5) in situ rumen availability of each DDGS component.
Journal ArticleDOI

High-throughput Methods Redefine the Rumen Microbiome and Its Relationship with Nutrition and Metabolism:

TL;DR: This review highlights recent studies of the rumen microbiome in the context of cattle production focusing on nutrition, rumen development, animal efficiency, and microbial function.
Journal ArticleDOI

Milk protein synthesis as a function of amino acid supply.

TL;DR: Estimations of the ideal profile of AA for lactating dairy cows were similar between models, with requirements for Lys and Met in line with 2001 National Research Council recommendations.
Journal ArticleDOI

Effects of barley grain processing on extent of digestion and milk production of lactating cows.

TL;DR: The results indicate that the optimal extent of barley processing for dairy cows fed diets supplying adequate fiber was medium-flat, corresponding to a processing index of about 64%.
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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