Models of protein and amino acid requirements for cattle
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista Brasileira de Zootecnia (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982015000300109 |
Resumo: | 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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Models of protein and amino acid requirements for cattlemodelingnutritionpredictionruminantssimulationProtein 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.Sociedade Brasileira de Zootecnia2015-03-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982015000300109Revista Brasileira de Zootecnia v.44 n.3 2015reponame:Revista Brasileira de Zootecnia (Online)instname:Sociedade Brasileira de Zootecnia (SBZ)instacron:SBZ10.1590/S1806-92902015000300005info:eu-repo/semantics/openAccessTedeschi,Luis OrlindoFox,Danny GeneFonseca,Mozart AlvesCavalcanti,Luigi Francis Limaeng2015-09-15T00:00:00Zoai:scielo:S1516-35982015000300109Revistahttps://www.rbz.org.br/pt-br/https://old.scielo.br/oai/scielo-oai.php||bz@sbz.org.br|| secretariarbz@sbz.org.br1806-92901516-3598opendoar:2015-09-15T00:00Revista Brasileira de Zootecnia (Online) - Sociedade Brasileira de Zootecnia (SBZ)false |
dc.title.none.fl_str_mv |
Models of protein and amino acid requirements for cattle |
title |
Models of protein and amino acid requirements for cattle |
spellingShingle |
Models of protein and amino acid requirements for cattle Tedeschi,Luis Orlindo modeling nutrition prediction ruminants simulation |
title_short |
Models of protein and amino acid requirements for cattle |
title_full |
Models of protein and amino acid requirements for cattle |
title_fullStr |
Models of protein and amino acid requirements for cattle |
title_full_unstemmed |
Models of protein and amino acid requirements for cattle |
title_sort |
Models of protein and amino acid requirements for cattle |
author |
Tedeschi,Luis Orlindo |
author_facet |
Tedeschi,Luis Orlindo Fox,Danny Gene Fonseca,Mozart Alves Cavalcanti,Luigi Francis Lima |
author_role |
author |
author2 |
Fox,Danny Gene Fonseca,Mozart Alves Cavalcanti,Luigi Francis Lima |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Tedeschi,Luis Orlindo Fox,Danny Gene Fonseca,Mozart Alves Cavalcanti,Luigi Francis Lima |
dc.subject.por.fl_str_mv |
modeling nutrition prediction ruminants simulation |
topic |
modeling nutrition prediction ruminants simulation |
description |
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. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-03-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982015000300109 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982015000300109 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S1806-92902015000300005 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Zootecnia |
publisher.none.fl_str_mv |
Sociedade Brasileira de Zootecnia |
dc.source.none.fl_str_mv |
Revista Brasileira de Zootecnia v.44 n.3 2015 reponame:Revista Brasileira de Zootecnia (Online) instname:Sociedade Brasileira de Zootecnia (SBZ) instacron:SBZ |
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Sociedade Brasileira de Zootecnia (SBZ) |
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SBZ |
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SBZ |
reponame_str |
Revista Brasileira de Zootecnia (Online) |
collection |
Revista Brasileira de Zootecnia (Online) |
repository.name.fl_str_mv |
Revista Brasileira de Zootecnia (Online) - Sociedade Brasileira de Zootecnia (SBZ) |
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||bz@sbz.org.br|| secretariarbz@sbz.org.br |
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1750318151411695616 |