Nitrogen excretion from beef cattle fed a wide range of diets compiled in an intercontinental dataset: a meta-analysis
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , , , , , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1093/jas/skac150 http://hdl.handle.net/11449/248659 |
Resumo: | Manure N from cattle contributes to nitrate leaching, nitrous oxide, and ammonia emissions. Measurement of manure N outputs on commercial beef cattle operations is laborious, expensive, and impractical; therefore, models are needed to predict N excreted in urine and feces. Building robust prediction models requires extensive data from animals under different management systems worldwide. Thus, the study objectives were to 1) collate an international dataset of N excretion in feces and urine based on individual observations from beef cattle; 2) determine the suitability of key variables for predicting fecal, urinary, and total manure N excretion; and 3) develop robust and reliable N excretion prediction models based on individual observation from beef cattle consuming various diets. A meta-analysis based on individual beef data from different experiments was carried out from a raw dataset including 1,004 observations from 33 experiments collected from 5 research institutes in Europe (n = 3), North America (n = 1), and South America (n = 1). A sequential approach was taken in developing models of increasing complexity by incrementally adding significant variables that affected fecal, urinary, or total manure N excretion. Nitrogen excretion was predicted by fitting linear mixed models with experiment as a random effect. Simple models including dry matter intake (DMI) were better at predicting fecal N excretion than those using only dietary nutrient composition or body weight (BW). Simple models based on N intake performed better for urinary and total manure N excretion than those based on DMI. A model including DMI and dietary component concentrations led to the most robust prediction of fecal and urinary N excretion, generating root mean square prediction errors as a percentage of the observed mean values of 25.0% for feces and 25.6% for urine. Complex total manure N excretion models based on BW and dietary component concentrations led to the lowest prediction errors of about 14.6%. In conclusion, several models to predict N excretion already exist, but the ones developed in this study are based on individual observations encompassing larger variability than the previous developed models. In addition, models that include information on DMI or N intake are required for accurate prediction of fecal, urinary, and total manure N excretion. In the absence of intake data, equations have poor performance as compared with equations based on intake and dietary component concentrations. |
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Nitrogen excretion from beef cattle fed a wide range of diets compiled in an intercontinental dataset: a meta-analysisbeef cattlenitrogen excretionprediction modelsManure N from cattle contributes to nitrate leaching, nitrous oxide, and ammonia emissions. Measurement of manure N outputs on commercial beef cattle operations is laborious, expensive, and impractical; therefore, models are needed to predict N excreted in urine and feces. Building robust prediction models requires extensive data from animals under different management systems worldwide. Thus, the study objectives were to 1) collate an international dataset of N excretion in feces and urine based on individual observations from beef cattle; 2) determine the suitability of key variables for predicting fecal, urinary, and total manure N excretion; and 3) develop robust and reliable N excretion prediction models based on individual observation from beef cattle consuming various diets. A meta-analysis based on individual beef data from different experiments was carried out from a raw dataset including 1,004 observations from 33 experiments collected from 5 research institutes in Europe (n = 3), North America (n = 1), and South America (n = 1). A sequential approach was taken in developing models of increasing complexity by incrementally adding significant variables that affected fecal, urinary, or total manure N excretion. Nitrogen excretion was predicted by fitting linear mixed models with experiment as a random effect. Simple models including dry matter intake (DMI) were better at predicting fecal N excretion than those using only dietary nutrient composition or body weight (BW). Simple models based on N intake performed better for urinary and total manure N excretion than those based on DMI. A model including DMI and dietary component concentrations led to the most robust prediction of fecal and urinary N excretion, generating root mean square prediction errors as a percentage of the observed mean values of 25.0% for feces and 25.6% for urine. Complex total manure N excretion models based on BW and dietary component concentrations led to the lowest prediction errors of about 14.6%. In conclusion, several models to predict N excretion already exist, but the ones developed in this study are based on individual observations encompassing larger variability than the previous developed models. In addition, models that include information on DMI or N intake are required for accurate prediction of fecal, urinary, and total manure N excretion. In the absence of intake data, equations have poor performance as compared with equations based on intake and dietary component concentrations.U.S. Department of AgricultureNational Institute of Food and AgricultureFondo Nacional de Desarrollo Científico, Tecnológico y de Innovación TecnológicaDepartment of Animal Science University of CaliforniaDepartment of Animal Science The Pennsylvania State UniversityDepartment of Animal Sciences Universidade Federal de Viçosa, Minas GeraisDepartment of Animal Science Universidade Estadual Paulista (UNESP), JaboticabalAgriculture and Agri-Food Canada Lethbridge Research and Development CentreAnimal Sciences Unit Flanders Research Institute for Agriculture Fisheries and Food (ILVO), ScheldewegSustainable Agri-Food Sciences Division Agri-Food and Biosciences Institute, County DownINRAE Université Clermont Auvergne - VetAgroSup UMR 1213 Unité Mixte de Recherche sur les Herbivores Centre de recherche Auvergne Rhône-Alpes TheixAgResearch Grasslands Research CentreDepartment of Animal Science Universidade Estadual Paulista (UNESP), JaboticabalNational Institute of Food and Agriculture: 1000803Fondo Nacional de Desarrollo Científico, Tecnológico y de Innovación Tecnológica: 1191476National Institute of Food and Agriculture: 2014-67003-21979National Institute of Food and Agriculture: 2019-67019-29400University of CaliforniaThe Pennsylvania State UniversityUniversidade Federal de Viçosa (UFV)Universidade Estadual Paulista (UNESP)Lethbridge Research and Development CentreFisheries and Food (ILVO)Agri-Food and Biosciences InstituteTheixGrasslands Research CentreBougouin, AdelineHristov, AlexanderZanetti, DiegoFilho, Sebastiao C.V.Rennó, Lucianna N.Menezes, Ana C.B.Silva, Jarbas M.Alhadas, Herlon M.Mariz, Lays D.S.Prados, Laura F. [UNESP]Beauchemin, Karen A.McAllister, TimYang, WenZhu Z.Koenig, Karen M.Goossens, KarenYan, TianhaiNoziere, PierreJonker, ArjanKebreab, Ermias2023-07-29T13:50:08Z2023-07-29T13:50:08Z2022-09-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1093/jas/skac150Journal of Animal Science, v. 100, n. 9, 2022.1525-31630021-8812http://hdl.handle.net/11449/24865910.1093/jas/skac1502-s2.0-85151990202Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengJournal of Animal Scienceinfo:eu-repo/semantics/openAccess2024-06-07T18:42:07Zoai:repositorio.unesp.br:11449/248659Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T18:34:10.400003Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Nitrogen excretion from beef cattle fed a wide range of diets compiled in an intercontinental dataset: a meta-analysis |
title |
Nitrogen excretion from beef cattle fed a wide range of diets compiled in an intercontinental dataset: a meta-analysis |
spellingShingle |
Nitrogen excretion from beef cattle fed a wide range of diets compiled in an intercontinental dataset: a meta-analysis Bougouin, Adeline beef cattle nitrogen excretion prediction models |
title_short |
Nitrogen excretion from beef cattle fed a wide range of diets compiled in an intercontinental dataset: a meta-analysis |
title_full |
Nitrogen excretion from beef cattle fed a wide range of diets compiled in an intercontinental dataset: a meta-analysis |
title_fullStr |
Nitrogen excretion from beef cattle fed a wide range of diets compiled in an intercontinental dataset: a meta-analysis |
title_full_unstemmed |
Nitrogen excretion from beef cattle fed a wide range of diets compiled in an intercontinental dataset: a meta-analysis |
title_sort |
Nitrogen excretion from beef cattle fed a wide range of diets compiled in an intercontinental dataset: a meta-analysis |
author |
Bougouin, Adeline |
author_facet |
Bougouin, Adeline Hristov, Alexander Zanetti, Diego Filho, Sebastiao C.V. Rennó, Lucianna N. Menezes, Ana C.B. Silva, Jarbas M. Alhadas, Herlon M. Mariz, Lays D.S. Prados, Laura F. [UNESP] Beauchemin, Karen A. McAllister, Tim Yang, WenZhu Z. Koenig, Karen M. Goossens, Karen Yan, Tianhai Noziere, Pierre Jonker, Arjan Kebreab, Ermias |
author_role |
author |
author2 |
Hristov, Alexander Zanetti, Diego Filho, Sebastiao C.V. Rennó, Lucianna N. Menezes, Ana C.B. Silva, Jarbas M. Alhadas, Herlon M. Mariz, Lays D.S. Prados, Laura F. [UNESP] Beauchemin, Karen A. McAllister, Tim Yang, WenZhu Z. Koenig, Karen M. Goossens, Karen Yan, Tianhai Noziere, Pierre Jonker, Arjan Kebreab, Ermias |
author2_role |
author author author author author author author author author author author author author author author author author author |
dc.contributor.none.fl_str_mv |
University of California The Pennsylvania State University Universidade Federal de Viçosa (UFV) Universidade Estadual Paulista (UNESP) Lethbridge Research and Development Centre Fisheries and Food (ILVO) Agri-Food and Biosciences Institute Theix Grasslands Research Centre |
dc.contributor.author.fl_str_mv |
Bougouin, Adeline Hristov, Alexander Zanetti, Diego Filho, Sebastiao C.V. Rennó, Lucianna N. Menezes, Ana C.B. Silva, Jarbas M. Alhadas, Herlon M. Mariz, Lays D.S. Prados, Laura F. [UNESP] Beauchemin, Karen A. McAllister, Tim Yang, WenZhu Z. Koenig, Karen M. Goossens, Karen Yan, Tianhai Noziere, Pierre Jonker, Arjan Kebreab, Ermias |
dc.subject.por.fl_str_mv |
beef cattle nitrogen excretion prediction models |
topic |
beef cattle nitrogen excretion prediction models |
description |
Manure N from cattle contributes to nitrate leaching, nitrous oxide, and ammonia emissions. Measurement of manure N outputs on commercial beef cattle operations is laborious, expensive, and impractical; therefore, models are needed to predict N excreted in urine and feces. Building robust prediction models requires extensive data from animals under different management systems worldwide. Thus, the study objectives were to 1) collate an international dataset of N excretion in feces and urine based on individual observations from beef cattle; 2) determine the suitability of key variables for predicting fecal, urinary, and total manure N excretion; and 3) develop robust and reliable N excretion prediction models based on individual observation from beef cattle consuming various diets. A meta-analysis based on individual beef data from different experiments was carried out from a raw dataset including 1,004 observations from 33 experiments collected from 5 research institutes in Europe (n = 3), North America (n = 1), and South America (n = 1). A sequential approach was taken in developing models of increasing complexity by incrementally adding significant variables that affected fecal, urinary, or total manure N excretion. Nitrogen excretion was predicted by fitting linear mixed models with experiment as a random effect. Simple models including dry matter intake (DMI) were better at predicting fecal N excretion than those using only dietary nutrient composition or body weight (BW). Simple models based on N intake performed better for urinary and total manure N excretion than those based on DMI. A model including DMI and dietary component concentrations led to the most robust prediction of fecal and urinary N excretion, generating root mean square prediction errors as a percentage of the observed mean values of 25.0% for feces and 25.6% for urine. Complex total manure N excretion models based on BW and dietary component concentrations led to the lowest prediction errors of about 14.6%. In conclusion, several models to predict N excretion already exist, but the ones developed in this study are based on individual observations encompassing larger variability than the previous developed models. In addition, models that include information on DMI or N intake are required for accurate prediction of fecal, urinary, and total manure N excretion. In the absence of intake data, equations have poor performance as compared with equations based on intake and dietary component concentrations. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-09-01 2023-07-29T13:50:08Z 2023-07-29T13:50:08Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1093/jas/skac150 Journal of Animal Science, v. 100, n. 9, 2022. 1525-3163 0021-8812 http://hdl.handle.net/11449/248659 10.1093/jas/skac150 2-s2.0-85151990202 |
url |
http://dx.doi.org/10.1093/jas/skac150 http://hdl.handle.net/11449/248659 |
identifier_str_mv |
Journal of Animal Science, v. 100, n. 9, 2022. 1525-3163 0021-8812 10.1093/jas/skac150 2-s2.0-85151990202 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Journal of Animal Science |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
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1808128949454110720 |