A net carbohydrate and protein system for evaluating cattle diets: III. Cattle requirements and diet adequacy

Fox, D. G.; Sniffen, C.J.; O’Connor, John D.; Russell, James B.; Soest, P.J. Van

doi:10.2527/1992.70113578x

Cited by 412 publications

(239 citation statements)

References 11 publications

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“…The UIP is a user input value while the MCP is computed as 13% of TDN and corrected for the effect of rumen pH, using physically effective neutral detergent fiber (peNDF) as described by Russell et al (1992). The solution level 2 uses the Cornell Net Carbohydrate and Protein System (CNCPS) as described by Fox et al (1992), Sniffen et al (1992), Russell et al (1992), andO'Connor et al (1993).…”

Section: Description Of Major Feeding Systemsmentioning

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: Description Of Major Feeding Systemsmentioning

confidence: 99%

Models of protein and amino acid requirements for cattle

et al. 2015

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“…The A and B 1 equations include measurements of NDF, as a component of B 2 and C. In the B 2 and C equations the Queiroz, Fukushima, Gomide and Braga indigestible pool is calculated using lignin as a proportion of ash and protein-free NDF Van Soest et al, 2000;Fox and Tedeschi, 2002). This ratio is then multiplied by 2.4, as proposed by Chandler et al (1980), which represents the material remaining after an extended period of in vitro fermentation, likely containing significant unfermented available substrate depending on the duration of incubation (Van Soest et al, 2000).…”

Section: Methodsmentioning

confidence: 99%

“…The 'Cornell Net Carbohydrate and Protein System' (CNCPS; Fox et al, 1992;Russell et al, 1992;Sniffen et al, 1992) is a mathematical model linking feed analysis and estimates of nutrient requirements for cattle. In order to predict the supply of metabolisable energy and protein, the CNCPS uses equations to estimate digestion and passage of several feed carbohydrate and protein fractions, each of which is assumed to have a constant rate of ruminal -E-mail: rsfukush@usp.br digestion.…”

Section: Introductionmentioning

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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“…Over the last few decades, several nutrition models (Institute National de la Recherche Agronomique, 1989;Commonwealth Scientific and Industrial Research Organisation, 1990;Fox et al, 1992;Agricultural and Food Research Council (AFRC), 1993;National Research Council (NRC), 2001;Tylutki et al, 2008) were developed, evaluated or updated, and used to estimate requirements and performance of animals. However, some groups such as dairy calves less than 2 months of age are overlooked on the farms.…”

Section: Introductionmentioning

confidence: 99%

“…The development of models is based on known facts and logical assumptions, and then the predictions from the model are compared with independent real data (Vanden Berg, 1980). The evaluation of different models is important to verify the accuracy and precision of the estimated values in different environmental conditions, genotypes and managements.Over the last few decades, several nutrition models (Institute National de la Recherche Agronomique, 1989; Commonwealth Scientific and Industrial Research Organisation, 1990; † E-mail: veridianalsousa@yahoo.com.br Animal (2016), 10:12, pp 1965-1974 Fox et al, 1992; Agricultural and Food Research Council (AFRC), 1993; National Research Council (NRC), 2001;Tylutki et al, 2008) were developed, evaluated or updated, and used to estimate requirements and performance of animals. However, some groups such as dairy calves less than 2 months of age are overlooked on the farms.…”

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confidence: 99%

Evaluation of nutrition models to estimate performance of young dairy calves: a meta-analytical study under tropical conditions

Souza

Drackley

Almeida

et al. 2016

animal

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Mathematical models are important tools to estimate nutritional requirements and animal growth. Very few calf models generated from other countries with different feeding programs, environment and production systems have been evaluated. The objective of this paper is to evaluate two calf models: (i) the National Research Council (NRC) in 2001 and (ii) the updates published by Van Amburgh and Drackley in 2005 and inputted into Agricultural Modeling and Training Systems (AMTS, version 3.5.8). Data from 16 previous studies involving 51 diets for dairy calves under tropical conditions (n = 485 calves, initial BW 37.5 ± 4.35 kg and weaning weight of 62.0 ± 10.16 kg) were used. The calves were fed with whole milk, milk replacer or fermented colostrum, plus starter (20.9 ± 1.78% of CP). The accuracy of the average daily gain (ADG) prediction was evaluated by mean bias, mean square prediction error (MSPE), concordance correlation coefficient, bias correction factor (Cb), and regression between the observed and predicted values. The ADG observed from birth to weaning was 0.452 ± 0.121 kg/day. Calves fed with whole milk had greater ADG compared with calves fed milk replacer (0.477 v. 0.379 kg/day) during the milk-feeding period. When all data were pooled (n = 51 diets), predictions had a mean bias of −0.019 and 0.068 kg/day for energy-allowable gain using NRC and AMTS models, respectively. The regression equation between observed and predicted values obtained from energy of diets showed an intercept different from zero ( P < 0.0001) and slope that differed from unity ( P < 0.0001). In a second evaluation, when calves were fed only milk replacer, the energy-allowable gain from AMTS showed the lowest mean bias (0.008 kg/day) and 82.1% of the MSPE value originated from random errors. The lowest MSPE, the higher Cb value and no significant slope bias ( P > 0.05) indicate that the AMTS growth model resulted in accurate predictions for calves fed with milk replacer. However, within these latter two approaches, the goodness of fit ( R 2 ) was low, representing low precision. The weight gain estimated by the energy available from the diet was overestimated by 19 g/day when calculated by the NRC and underestimated by 68 g/day when calculated by AMTS. The reasons for this discrepancy need to be understood, for only then new models could be developed and parameterized to estimate animal performance in tropical conditions more accurately and precisely.Keywords: calf models, cross-bred calves, growth, meta-analysis, prediction ImplicationsThe development of an accurate calf model has been challenging because several factors affect growth such as breed, colostrum and feeding programs, facilities and environmental conditions. Because of the conventional feeding system (e.g. 4 l/calf at each of two daily feedings) and tropical conditions, the animals evaluated in this study showed poor weight gains. The low energy to protein ratio likely reduced calf growth rates. Currently available calf models can be used to predict calf growth during ...

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A net carbohydrate and protein system for evaluating cattle diets: III. Cattle requirements and diet adequacy

Cited by 412 publications

References 11 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.)

Evaluation of nutrition models to estimate performance of young dairy calves: a meta-analytical study under tropical conditions

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