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).

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

https://www.webpages.uidaho.edu/ruminant_nutrition/Reading%20materials%20411/dietary%20factors%20affecting%20feed%20intake-Allen2000.pdf

Effects of Diet on Short-Term Regulation of Feed Intake by Lactating Dairy Cattle

Creating a System for Meeting the Fiber Requirements of Dairy Cows

Dietary fibre is that part of plant material in the diet which is resistant to enzymatic digestion which includes cellulose, noncellulosic polysaccharides such as hemicellulose, pectic substances, gums, mucilages and a non-carbohydrate component lignin. The diets rich in fibre such as cereals, nuts, fruits and vegetables have a positive effect on health since their consumption has been related to decreased incidence of several diseases. Dietary fibre can be used in various functional foods like bakery, drinks, beverages and meat products. Influence of different processing treatments (like extrusion-cooking, canning, grinding, boiling, frying) alters the physico- chemical properties of dietary fibre and improves their functionality. Dietary fibre can be determined by different methods, mainly by: enzymic gravimetric and enzymic—chemical methods. This paper presents the recent developments in the extraction, applications and functions of dietary fibre in different food products.

/pdf/dietary-fibre-in-foods-a-review-2da00vg1js.pdf

Dietary fibre in foods: a review

Bovine Acidosis: Implications on Laminitis

As an important constituent of animal feeds, fiber represents the portion of feeds that is bulky and difficult to digest. The neutral detergent fiber (NDF) method, developed over 30 years ago, is the method of choice for measuring total fiber in forages and other feeds. Several modifications that were made to improve its general applicability to all feeds and others developed in individual laboratories often resulted in variability among laboratories in measuring NDF. The amylase-treated NDF (aNDF) method, therefore, was developed as an accurate and precise method of measuring total insoluble fiber in feeds. A collaborative study was conducted to evaluate the repeatability and reproducibility of the aNDF method over the full range of animal feed materials. Twelve laboratories representing research, feed company, regulatory, and commercial feed testing laboratories analyzed 11 materials as blind duplicates. The materials represented feed matrixes, including animal products; high-protein, high-fat, and high-pectin feeds; oil seeds; grains; heated by-product feeds; and legume and grass hays and silages. Materials selected varied in chemical composition and contained 0-90% aNDF, 1-16% ash, 1-20% crude fat, 1-40% crude protein, and 0-50% starch. Correcting results for changes in blanks and reporting results as ash-free aNDF organic matter (aNDFom) improved the repeatability and reproducibility of results when aNDF was 10% fat. However, standard deviations of repeatability and reproducibility for feeds with >10% fat were similar to those of other materials. It is recommended that the aNDF method be accepted for Official First Action status.

Gravimetric Determination of Amylase-Treated Neutral Detergent Fiber in Feeds with Refluxing in Beakers or Crucibles: Collaborative Study

Forage quality can be assessed in terms of the animal performance that is elicited when the forage is offered to the animal. Animal performance is the product of supply, nutrient and energy concentration, intake, digestibility, and metabolism. Typically, forage quality is measured assuming that the forage is freely available and that deficient nutrients other than protein and energy are provided in a supplement. Of the remaining factors affecting forage quality, intake is the most important one affecting animal performance. Reid (1961) listed the amount of forage eaten as the first factor limiting the usefulness of forage-testing schemes. His list also included the effect of concentrates on the amount of forage eaten, degree of selective feeding, and effect of physical form as important information not provided by the forage testing systems used at that time. Unfortunately, intake, substitution rates, selection, and physical form still are not a part of routine forage evaluation systems in the 1990's. Animal performance depends on the intake of digestible and metabolizable nutrients. Of the variation in digestible dry matter (DDM) or digestible energy (DE) intake among animals and feeds, 60 to 90% is related to differences in intake, whereas only 10 to 40% is related to differences in digestibility (Crampton et al., 1960; Reid, 1961). Intake generally accounts for twice as much variability in DDM intake as does digestibility (Milford, 1960; Ingalls et al., 1965). Milford and Minson (1966) observed that DDM intake is more closely correlated with dry matter intake (DMI) than any other feed or animal characteristic. Similarly, high correlations would occur between DMI and metabolizable (ME) or net energy (NE) intake, and between DMI and overall animal performance when forages are fed. The primary importance of intake in assessing forage quality does not mean that digestibility or metabolizability of nutrients are invariant or unimportant. Metabolizability can vary depending on the amounts and ratios of absorbed nutrients, the individual and interacting biochemical pathways of nutrient conversion and the type of animal production (MacRae et al., 1985; Blaxter, 1989). However, differences in the efficiency of converting DE to ME are small compared to differences in intake and digestibility, and the metabolic conversion of DE to ME or NE is typically considered to be relatively constant within type of production, such as maintenance, growth, pregnancy, or lactation (Moe and Tyrrell, 1976; NRC, 1989). Digestibility of forages is more variable than metabolizability, and feces typically are the greatest loss of ingested nutrients and energy. Extensive research has been devoted to measuring digestibility and relating it to feed characteristics because digestibility can be accurately measured with relative ease compared to DMI. Although intake is more important than digestibility in assessing forage quality, progress in understanding the basic factors that affect intake has been hampered by our inability to measure it accurately and to separate the influences of animal and diet on intake. Thus, we routinely use availability information (DE, ME, andNE)

Regulation of Forage Intake

Forage ouality, evaluation and Utilization , Forage ouality, evaluation and Utilization , مرکز فناوری اطلاعات و اطلاع رسانی کشاورزی

Forage Quality, Evaluation, and Utilization

Intake and digestibility of feeds by ruminants are influenced by characteristics of the feed, animal and feeding situation. Integration of these characteristics in mathematical models is critical to future progress in forage evaluation and optimal formulation of diets for ruminants. The physiological and physical theories of intake regulation can be described by simple mathematical equations. These equations indicate that intake is a linear function of animal characteristics, such as body weight and production level, and a reciprocal function of feed characteristics, such as fill effect and energy content. Theoretical equations were developed to predict intake when the neutral detergent fiber and energy content of the diet and the energy requirements of the animal are known. The theoretical model also can be used to predict the maximum intake that will maintain a given level of animal production by solving the physiological and physical intake equations at their intersection. Psychogenic intake regulation, which is related to the animal's behavioral response to factors not related to physiological or physical characteristics, can be described mathematically as a multiplier. Digestibility can be predicted by summing the contents of ideal nutritive entities in feeds, which have true digestibilities near 100%, subtracting their associated endogenous losses and adding the variable digestible fiber content. Steady-state models indicate fractional rates of digestion and passage can be used to define ideal nutritive entities and predict digestibility over a range of kinetic characteristics. The steady-state solutions are particularly useful in understanding and predicting the depression in digestibility associated with changes in rates of passage at high levels of feed intake.

David R. Mertens

Papers

Gravimetric Determination of Amylase-Treated Neutral Detergent Fiber in Feeds with Refluxing in Beakers or Crucibles: Collaborative Study

Creating a System for Meeting the Fiber Requirements of Dairy Cows

Regulation of Forage Intake

Forage Quality, Evaluation, and Utilization

Predicting intake and digestibility using mathematical models of ruminal function.