The Cornell Net Carbohydrate and Protein System model for evaluating herd nutrition and nutrient excretion

Fox, D. G.; Tedeschi, L. O.; Tylutki, T. P.; Russell, James B.; Amburgh, M.E. Van; Chase, L.E.; Pell, Alice N.; Overton, T.R.

doi:10.1016/j.anifeedsci.2003.10.006

Cited by 600 publications

(742 citation statements)

References 102 publications

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“…The most recent complete CNCPS version published is that described by and Fox et al (2004), which includes both beef and dairy cattle with two levels of solution (L1 and L2). Modifications have been made to L2 for CPM Dairy as described by Tedeschi et al (2008), CNCPS version 6.0 as described by Tylutki et al (2008), and CNCPS v. 6.1 as described by Van Amburgh et al (2010), and to both levels for the Large Ruminant Nutrition System (LRNS) as described by Tedeschi and Fox at http://nutritionmodels.tamu.edu/lrns.html.…”

Section: Cornell Net Carbohydrate and Protein System (Cncps)mentioning

confidence: 99%

Models of protein and amino acid requirements for cattle

et al. 2015

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-Protein supply and requirements by ruminants have been studied for more than a century. These studies led to the accumulation of lots of scientific information about digestion and metabolism of protein by ruminants as well as the characterization of the dietary protein in order to maximize animal performance. During the 1980s and 1990s, when computers became more accessible and powerful, scientists began to conceptualize and develop mathematical nutrition models, and to program them into computers to assist with ration balancing and formulation for domesticated ruminants, specifically dairy and beef cattle. The most commonly known nutrition models developed during this period were the National Research Council (NRC) in the United States, Agricultural Research Council (ARC) in the United Kingdom, Institut National de la Recherche Agronomique (INRA) in France, and the Commonwealth Scientific and Industrial Research Organization (CSIRO) in Australia. Others were derivative works from these models with different degrees of modifications in the supply or requirement calculations, and the modeling nature (e.g., static or dynamic, mechanistic, or deterministic). Circa 1990s, most models adopted the metabolizable protein (MP) system over the crude protein (CP) and digestible CP systems to estimate supply of MP and the factorial system to calculate MP required by the animal. The MP system included two portions of protein (i.e., the rumen-undegraded dietary CP -RUP -and the contributions of microbial CP -MCP) as the main sources of MP for the animal. Some models would explicitly account for the impact of dry matter intake (DMI) on the MP required for maintenance (MPm; e.g., Cornell Net Carbohydrate and Protein System -CNCPS, the Dutch system -DVE/OEB), while others would simply account for scurf, urinary, metabolic fecal, and endogenous contributions independently of DMI. All models included milk yield and its components in estimating MP required for lactation (MPl) and calf birth weight and some form of an empirical, exponential equation to compute MP for pregnancy (MPp). The MP required for growth (MPg) varied tremendously among the original models and their derivative works mainly due to the differences in computing growth pattern and the composition of the gain. The calculation of MCP differs among models; some rely on the total digestible nutrient (TDN; e.g., NRC, CNCPS level 1) intake to estimate MCP, while others use fermentable organic matter (FOM; e.g., INRA, DVE/OEB), fermentable carbohydrate (e.g., CNCPS level 2, NorFor), or metabolizable energy (ME; e.g., ARC, CSIRO, Rostock). Most models acknowledged the importance of ruminal recycled N, but not all accounted for it. Our Monte Carlo simulation indicated the prediction of most models for required MPl overlapped, confirming uniformity among models when predicting requirements for lactating animals, but a large variation in required MPg for growing animals exists.

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Section: Cornell Net Carbohydrate and Protein System (Cncps)mentioning

confidence: 99%

Models of protein and amino acid requirements for cattle

et al. 2015

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“…Accordingly, pectin would also be placed in fraction A and not in fraction B 1 . The CNCPS model puts pectin in carbohydrate fraction B 1 Fox et al, 2004).…”

Section: Resultsmentioning

confidence: 99%

Substitution of crude cell wall for neutral detergent fibre in the equations of the Cornell Net Carbohydrate and Protein System that predict carbohydrate fractions: application to sunflower (Helianthus annuus L.)

Queiróz

Fukushima

Gomide

et al. 2008

Animal

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Prediction of carbohydrate fractions using equations from the Cornell Net Carbohydrate and Protein System (CNCPS) is a valuable tool to assess the nutritional value of forages. In this paper, these carbohydrate fractions were predicted using data from three sunflower (Helianthus annuus L.) cultivars, fresh or as silage. The CNCPS equations for fractions B 2 and C include measurement of ash and protein-free neutral detergent fibre (NDF) as one of their components. However, NDF lacks pectin and other non-starch polysaccharides that are found in the cell wall (CW) matrix, so this work compared the use of a crude CW preparation instead of NDF in the CNCPS equations. There were no differences in the estimates of fractions B 1 and C when CW replaced NDF; however, there were differences in fractions A and B 2 . Some of the CNCPS equations could be simplified when using CW instead of NDF. Notably, lignin could be expressed as a proportion of DM, rather than on the basis of ash and protein-free NDF, when predicting CNCPS fraction C. The CNCPS fraction B 1 (starch 1 pectin) values were lower than pectin determined through wet chemistry. This finding, along with the results obtained by the substitution of CW for NDF in the CNCPS equations, suggests that pectin was not part of fraction B 1 but present in fraction A. We suggest that pectin and other non-starch polysaccharides that are dissolved by the neutral detergent solution be allocated to a specific fraction (B 2 ) and that another fraction (B 3 ) be adopted for the digestible cell wall carbohydrates.

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“…The WFBS is constructed by merging different functions or parts of the existing biophysical models of the literature (e.g. Jarrige (1988);Fox et al (2004) for the milk production sub-model). The WFDS is relevant to the current article while WFBS is beyond the scope of this paper.…”

Section: Study Area Descriptionmentioning

confidence: 99%

Modelling farmers' action: decision rules capture methodology and formalisation structure: a case of biomass flow operations in dairy farms of a tropical island

Vayssières

Lecomte

Guerrin

et al. 2007

Animal

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Studies on decision-making processes are generally aimed at identifying farmers' needs and predicting farmers' reactions to technical innovations. In the present paper we study these decision-making processes, with reference to dairy farms, to build a whole-farm computer model (WFM) which simulates farmers' actions. In this study, (i) a multi-tool and multi-step methodology is proposed, which can also be qualified as an iterative and interactive methodology to reveal decision rules and (ii) a generic structure to formalise how action is conducted, termed 'structure for action modelling' (SAM). In the case of forage crop-dairy cattle systems, we have tested the current methodology to capture the decision rules and the SAM to represent action concerning farm management. An 'immersion' approach, inspired by the ethnographic approach has been adapted to access operational technical decisions (taken on a daily basis). This study helped in understanding how detailed and large approaches can be complementary and can facilitate identification of what can be generalised in a conceptual model. To define the generic structure (SAM), a set of descriptive variables concerning technical operations has been selected. The conceptual model generated is composed of decision rules reconstructed by researchers with farmers' committed participation. The validation method is based on participatory approaches and on comparing of actions simulated by the model with practices on the ground. Not contesting the fact that farmers plan their action, this study also revealed the importance of adjustments in action. For example, 20 to 55% of the time the planned food ration is not distributed to the milking cows because of forage unavailability. We also discuss how this structure can facilitate integration of decision mechanisms in biophysical models and how such an integration of adjustment decision rules can produce more realistic simulations of technical actions. Error of biotechnical evaluations done by the WFM is reduced from about 25% to about 10% with the application of the proposed method.

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The Cornell Net Carbohydrate and Protein System model for evaluating herd nutrition and nutrient excretion

Cited by 600 publications

References 102 publications

Models of protein and amino acid requirements for cattle

Models of protein and amino acid requirements for cattle

Substitution of crude cell wall for neutral detergent fibre in the equations of the Cornell Net Carbohydrate and Protein System that predict carbohydrate fractions: application to sunflower (Helianthus annuus L.)

Modelling farmers' action: decision rules capture methodology and formalisation structure: a case of biomass flow operations in dairy farms of a tropical island

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