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Cited by 329Ruminant Nutrition and Digestive PhysiologyAnimal Nutrition and PhysiologyAnimal Nutrition and Health

The cornell net carbohydrate and protein system: updates to the model and evaluation of version 6.5

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Van Amburgh, M.E., Collao-Saenz, E.A., Higgs, R.J., Ross, D.A., Recktenwald, E.B., Raffrenato, E., Chase, L.E., Overton, T.R. +2 more·2015·Journal of Dairy Science
DOI 10.3168/jds.2015-9378
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Abstract

New laboratory and animal sampling methods and data have been generated over the last 10 yr that had the potential to improve the predictions for energy, protein, and AA supply and requirements in the Cornell Net Carbohydrate and Protein System (CNCPS). The objectives of this study were to describe updates to the CNCPS and evaluate model performance against both literature and on-farm data. The changes to the feed library were significant and are reported in a separate manuscript. Degradation rates of protein and carbohydrate fractions were adjusted according to new fractionation schemes, and corresponding changes to equations used to calculate rumen outflows and postrumen digestion were presented. In response to the feed-library changes and an increased supply of essential AA because of updated contents of AA, a combined efficiency of use was adopted in place of separate calculations for maintenance and lactation to better represent the biology of the cow. Four different data sets were developed to evaluate Lys and Met requirements, rumen N balance, and milk yield predictions. In total 99 peer-reviewed studies with 389 treatments and 15 regional farms with 50 different diets were included. The broken-line model with plateau was used to identify the concentration of Lys and Met that maximizes milk protein yield and content. Results suggested concentrations of 7.00 and 2.60% of metabolizable protein (MP) for Lys and Met, respectively, for maximal protein yield and 6.77 and 2.85% of MP for Lys and Met, respectively, for maximal protein content. Updated AA concentrations were numerically higher for Lys and 11 to 18% higher for Met compared with CNCPS v6.0, and this is attributed to the increased content of Met and Lys in feeds that were previously incorrectly analyzed and described. The prediction of postruminal flows of N and milk yield were evaluated using the correlation coefficient from the BLUP (R(2)BLUP) procedure or model predictions (R(2)MDP) and the concordance correlation coefficient. The accuracy and precision of rumen-degradable N and undegradable N and bacterial N flows were improved with reduced bias. The CNCPS v6.5 predicted accurate and precise milk yield according to the first-limiting nutrient (MP or metabolizable energy) with a R(2)BLUP=0.97, R(2)MDP=0.78, and concordance correlation coefficient=0.83. Furthermore, MP-allowable milk was predicted with greater precision than metabolizable energy-allowable milk (R(2)MDP=0.82 and 0.76, respectively, for MP and metabolizable energy). Results suggest a significant improvement of the model, especially under conditions of MP limitation.

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  • The development of rumen models has been deployed mainly via consolidation of four model structures (Molly, Karoline, Cornell, and Dijkstra) that have been improved over the years to enhance understanding of rumen function.

    “The development of rumen models has been deployed mainly via the consolidation of four model structures (Molly, Karoline, Cornell, and Dijkstra models) that have been improved over the years to enhance the understanding of rumen function (Mills et al., 2014; Huhtanen et al., 2015; Van Amburgh et al., 2015; Gregorini et al., 2016).”

    From Addressing global ruminant agricultural challenges through understanding the rumen microbiome: past, present, and future (2018) · cites this paper as Van Amburgh et al., 2015

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Research works printed but not linked: 6

  1. Comparison of model-predicted and measured CO 2 and CH 4 emissions in dairy cattle using the equations of Casper and Mertens (2010; A) and Mills et al. (2003; B) using data from studies by van Dorland et al. (2007), Moate et al. (2011), Liu et al. (2012), Hammond et al. (2014), and Reynolds et al. (2014). Predictions were not significantly different from published values. Journal of Dairy Science Vol. 98 No. 9, 2015
  2. Lock, A. L., K. J. Harvatine, J. K. Drackley, and D. E. Bauman. 2006. Concepts in fat and fatty acid digestion in ruminants. Pages 85-100 in Proc. Intermountain Nutr. Conf., Utah State University, Logan, UT.
  3. Lock, A. L., K. J. Harvatine, I. R. Ipharraguerre, M. E. Van Amburgh, J. K. Drackley, and D. E. Bauman. 2005. The dynamics of fat digestion in lactating dairy cows: What does the literature tell us? Pages 83-106 in Proc. Cornell Nutr. Conf., Dept. Anim. Sci., Cornell Univ., Ithaca, NY.
  4. Mitchell, H. H. 1928. Check formulas for surface area of sheep. Pages 155-158 in A Year's Progress in Solving Problems in Illinois. Il- linois Agric. Stn. Annu. Rep., Urbana, IL.
  5. NRC. 2001. Nutrient Requirements of Dairy Cattle. 7th rev. ed. Natl. Acad. Press, Washington, DC.
  6. Ranathunga, S. D., K. F. Kalscheur, A. R. Hippen, and D. J. Sch- ingoethe. 2010. Replacement of starch from corn with nonforage Journal of Dairy Science Vol. 98 No. 9, 2015 fiber from distillers grains and soyhulls in diets of lactating dairy cows. J. Dairy Sci. 93:1086-1097.

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Authors
Van Amburgh, M. E., Collao-Saenz, E. A., Higgs, R. J., Ross, D. A., Recktenwald, E. B., Raffrenato, E., Chase, L. E., Overton, T. R., Mills, J. K., & Foskolos, A.
Affiliations
  • Universidade Federal de Jataí (BR)
  • Cornell University (US)
  • Stellenbosch University (ZA)
ORCID
Venue
Journal of Dairy Science
Publisher
American Dairy Science Association
Published
2015-09
Volume
98
Issue
9
Pages
6361-6380
ISSN
0022-0302 (ISSN-L)
DOI
10.3168/jds.2015-9378
OpenAlex
W1535695796
Cited by
329
References
172
Citations by year
2026: 25 · 2025: 33 · 2024: 29 · 2023: 36 · 2022: 35 · 2021: 34 · 2020: 37 · 2019: 39 · 2018: 24 · 2017: 22 · 2016: 13 · 2015: 2
FWCI
43.96
Type
journal article
Language
en
Open access
Licence
Locations
  • Journal of Dairy Science (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • Padua Research Archive (University of Padova) (submittedVersion)
Topics
  • Life Sciences › Agricultural and Biological Sciences › Agronomy and Crop Science › Ruminant Nutrition and Digestive Physiology
  • Life Sciences › Agricultural and Biological Sciences › Animal Science and Zoology › Animal Nutrition and Physiology
  • Life Sciences › Agricultural and Biological Sciences › Plant Science › Animal Nutrition and Health
Keywords
Cornell Net Carbohydrate and Protein System, dairy cattle nutrition, model updating, protein degradation rate, amino acid requirements, lysine, methionine, milk protein yield, milk protein content, metabolizable protein, metabolizable energy, bacterial nitrogen, milk yield prediction, broken-line model
MeSH terms
Animals, Animal Feed, Carbon Dioxide, Cattle, Diet, Dietary Carbohydrates, Dietary Proteins, Digestion, Energy Metabolism, Fatty Acids, Feces, Female, Lactation, Methane, Milk, Milk Proteins, Models, Biological, Nitrogen, Rumen

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