Metabolizable Protein: 1. Predicting Equations to Estimate Microbial Crude Protein Synthesis in Small Ruminants

Detalhes bibliográficos
Autor(a) principal: Santos, Stefanie Alvarenga
Data de Publicação: 2021
Outros Autores: de Carvalho, Gleidson Giordano Pinto, Azevêdo, José Augusto Gomes, Zanetti, Diego, Santos, Edson Mauro, Pereira, Mara Lucia Albuquerque, Pereira, Elzania Sales, Pires, Aureliano José Vieira, Valadares Filho, Sebastião de Campos, Teixeira, Izabelle Auxiliadora Molina de Almeida [UNESP], Tosto, Manuela Silva Libânio, Leite, Laudi Cunha, Mariz, Lays Débora Silva
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.3389/fvets.2021.650248
http://hdl.handle.net/11449/221819
Resumo: Microbial crude protein (MCP) produced in rumen could be estimated by a variety of protocols of experimental sampling and analysis. However, a model to estimate this value is necessary when protein requirements are calculated for small ruminants. This model could be useful to calculate rumen degradable protein (RDP) requirements from metabolizable protein (MP). Then, our objective was to investigate if there is a difference in MCP efficiency between sheep and goats, and to fit equations to predict ruminal MCP production from dietary energy intake. The database consisted of 19 studies with goats (n = 176) and sheep (n = 316), and the variables MCP synthesis (g/day), total digestible nutrients (TDN), and organic matter (OM) intakes (g/day), and OM digestibility (g/kg DM) were registered for both species. The database was used for two different purposes, where 70% of the values were sorted to fit equations, and 30% for validation. A meta-analytical procedure was carried out using the MIXED procedure of SAS, specie was considered as the fixed dummy effect, and the intercept and slope nested in the study were considered random effects. No effect of specie was observed for the estimation of MCP from TDN, digestible Organic Matter (dOM), or metabolizable energy (ME) intakes (P > 0.05), considering an equation with or without an intercept. Therefore, single models including both species at the same fitting were validated. The following equations MCP (g/day) = 12.7311 + 59.2956 × TDN intake (AIC = 3,004.6); MCP (g/day) = 15.7764 + 62.2612 × dOM intake (AIC = 2,755.1); and MCP (g/day) = 12.7311 + 15.3000 × ME intake (AIC = 3,007.3) presented lower values for the mean square error of prediction (MSEP) and its decomposition, and similar values for the concordance correlation coefficient (CCC) and for the residual mean square error (RMSE) when compared with equations fitted without an intercept. The intercept and slope pooled test was significant for equations without an intercept (P < 0.05), indicating that observed and predicted data differed. In contrast, predicted and observed data for complete equations were similar (P > 0.05).
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spelling Metabolizable Protein: 1. Predicting Equations to Estimate Microbial Crude Protein Synthesis in Small RuminantsbacteriagoatmicroorganismsrumensheepyieldMicrobial crude protein (MCP) produced in rumen could be estimated by a variety of protocols of experimental sampling and analysis. However, a model to estimate this value is necessary when protein requirements are calculated for small ruminants. This model could be useful to calculate rumen degradable protein (RDP) requirements from metabolizable protein (MP). Then, our objective was to investigate if there is a difference in MCP efficiency between sheep and goats, and to fit equations to predict ruminal MCP production from dietary energy intake. The database consisted of 19 studies with goats (n = 176) and sheep (n = 316), and the variables MCP synthesis (g/day), total digestible nutrients (TDN), and organic matter (OM) intakes (g/day), and OM digestibility (g/kg DM) were registered for both species. The database was used for two different purposes, where 70% of the values were sorted to fit equations, and 30% for validation. A meta-analytical procedure was carried out using the MIXED procedure of SAS, specie was considered as the fixed dummy effect, and the intercept and slope nested in the study were considered random effects. No effect of specie was observed for the estimation of MCP from TDN, digestible Organic Matter (dOM), or metabolizable energy (ME) intakes (P > 0.05), considering an equation with or without an intercept. Therefore, single models including both species at the same fitting were validated. The following equations MCP (g/day) = 12.7311 + 59.2956 × TDN intake (AIC = 3,004.6); MCP (g/day) = 15.7764 + 62.2612 × dOM intake (AIC = 2,755.1); and MCP (g/day) = 12.7311 + 15.3000 × ME intake (AIC = 3,007.3) presented lower values for the mean square error of prediction (MSEP) and its decomposition, and similar values for the concordance correlation coefficient (CCC) and for the residual mean square error (RMSE) when compared with equations fitted without an intercept. The intercept and slope pooled test was significant for equations without an intercept (P < 0.05), indicating that observed and predicted data differed. In contrast, predicted and observed data for complete equations were similar (P > 0.05).Instituto Nacional de Ciência e Tecnologia de Ciência AnimalSchool of Veterinary Medicine and Animal Science Universidade Federal da BahiaDepartment of Agricultural and Environmental Sciences Universidade Estadual de Santa CruzDepartment of Animal Science Instituto Federal de Educação Ciência e Tecnologia do Sul de Minas GeraisCenter of Agrarian Sciences Universidade Federal da ParaíbaDepartment of Plant and Animal Sciences Universidade Estadual do Sudoeste da BahiaDepartment of Animal Science Universidade Federal do CearáDepartment of Animal Science Universidade Federal de ViçosaDepartment of Animal Science Universidade Estadual PaulistaDepartment of Agricultural and Environmental Sciences Universidade Federal do Recôncavo da BahiaDepartment of Animal Science Universidade Estadual PaulistaUniversidade Federal da Bahia (UFBA)Universidade Estadual de Santa CruzCiência e Tecnologia do Sul de Minas GeraisUniversidade Federal da Paraíba (UFPB)Universidade Estadual do Sudoeste da BahiaUniversidade Federal do CearáUniversidade Federal de Viçosa (UFV)Universidade Estadual Paulista (UNESP)Universidade Federal do Recôncavo da BahiaSantos, Stefanie Alvarengade Carvalho, Gleidson Giordano PintoAzevêdo, José Augusto GomesZanetti, DiegoSantos, Edson MauroPereira, Mara Lucia AlbuquerquePereira, Elzania SalesPires, Aureliano José VieiraValadares Filho, Sebastião de CamposTeixeira, Izabelle Auxiliadora Molina de Almeida [UNESP]Tosto, Manuela Silva LibânioLeite, Laudi CunhaMariz, Lays Débora Silva2022-04-28T19:40:49Z2022-04-28T19:40:49Z2021-06-10info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.3389/fvets.2021.650248Frontiers in Veterinary Science, v. 8.2297-1769http://hdl.handle.net/11449/22181910.3389/fvets.2021.6502482-s2.0-85108368655Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengFrontiers in Veterinary Scienceinfo:eu-repo/semantics/openAccess2022-04-28T19:40:49Zoai:repositorio.unesp.br:11449/221819Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T15:52:49.221374Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Metabolizable Protein: 1. Predicting Equations to Estimate Microbial Crude Protein Synthesis in Small Ruminants
title Metabolizable Protein: 1. Predicting Equations to Estimate Microbial Crude Protein Synthesis in Small Ruminants
spellingShingle Metabolizable Protein: 1. Predicting Equations to Estimate Microbial Crude Protein Synthesis in Small Ruminants
Santos, Stefanie Alvarenga
bacteria
goat
microorganisms
rumen
sheep
yield
title_short Metabolizable Protein: 1. Predicting Equations to Estimate Microbial Crude Protein Synthesis in Small Ruminants
title_full Metabolizable Protein: 1. Predicting Equations to Estimate Microbial Crude Protein Synthesis in Small Ruminants
title_fullStr Metabolizable Protein: 1. Predicting Equations to Estimate Microbial Crude Protein Synthesis in Small Ruminants
title_full_unstemmed Metabolizable Protein: 1. Predicting Equations to Estimate Microbial Crude Protein Synthesis in Small Ruminants
title_sort Metabolizable Protein: 1. Predicting Equations to Estimate Microbial Crude Protein Synthesis in Small Ruminants
author Santos, Stefanie Alvarenga
author_facet Santos, Stefanie Alvarenga
de Carvalho, Gleidson Giordano Pinto
Azevêdo, José Augusto Gomes
Zanetti, Diego
Santos, Edson Mauro
Pereira, Mara Lucia Albuquerque
Pereira, Elzania Sales
Pires, Aureliano José Vieira
Valadares Filho, Sebastião de Campos
Teixeira, Izabelle Auxiliadora Molina de Almeida [UNESP]
Tosto, Manuela Silva Libânio
Leite, Laudi Cunha
Mariz, Lays Débora Silva
author_role author
author2 de Carvalho, Gleidson Giordano Pinto
Azevêdo, José Augusto Gomes
Zanetti, Diego
Santos, Edson Mauro
Pereira, Mara Lucia Albuquerque
Pereira, Elzania Sales
Pires, Aureliano José Vieira
Valadares Filho, Sebastião de Campos
Teixeira, Izabelle Auxiliadora Molina de Almeida [UNESP]
Tosto, Manuela Silva Libânio
Leite, Laudi Cunha
Mariz, Lays Débora Silva
author2_role author
author
author
author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade Federal da Bahia (UFBA)
Universidade Estadual de Santa Cruz
Ciência e Tecnologia do Sul de Minas Gerais
Universidade Federal da Paraíba (UFPB)
Universidade Estadual do Sudoeste da Bahia
Universidade Federal do Ceará
Universidade Federal de Viçosa (UFV)
Universidade Estadual Paulista (UNESP)
Universidade Federal do Recôncavo da Bahia
dc.contributor.author.fl_str_mv Santos, Stefanie Alvarenga
de Carvalho, Gleidson Giordano Pinto
Azevêdo, José Augusto Gomes
Zanetti, Diego
Santos, Edson Mauro
Pereira, Mara Lucia Albuquerque
Pereira, Elzania Sales
Pires, Aureliano José Vieira
Valadares Filho, Sebastião de Campos
Teixeira, Izabelle Auxiliadora Molina de Almeida [UNESP]
Tosto, Manuela Silva Libânio
Leite, Laudi Cunha
Mariz, Lays Débora Silva
dc.subject.por.fl_str_mv bacteria
goat
microorganisms
rumen
sheep
yield
topic bacteria
goat
microorganisms
rumen
sheep
yield
description Microbial crude protein (MCP) produced in rumen could be estimated by a variety of protocols of experimental sampling and analysis. However, a model to estimate this value is necessary when protein requirements are calculated for small ruminants. This model could be useful to calculate rumen degradable protein (RDP) requirements from metabolizable protein (MP). Then, our objective was to investigate if there is a difference in MCP efficiency between sheep and goats, and to fit equations to predict ruminal MCP production from dietary energy intake. The database consisted of 19 studies with goats (n = 176) and sheep (n = 316), and the variables MCP synthesis (g/day), total digestible nutrients (TDN), and organic matter (OM) intakes (g/day), and OM digestibility (g/kg DM) were registered for both species. The database was used for two different purposes, where 70% of the values were sorted to fit equations, and 30% for validation. A meta-analytical procedure was carried out using the MIXED procedure of SAS, specie was considered as the fixed dummy effect, and the intercept and slope nested in the study were considered random effects. No effect of specie was observed for the estimation of MCP from TDN, digestible Organic Matter (dOM), or metabolizable energy (ME) intakes (P > 0.05), considering an equation with or without an intercept. Therefore, single models including both species at the same fitting were validated. The following equations MCP (g/day) = 12.7311 + 59.2956 × TDN intake (AIC = 3,004.6); MCP (g/day) = 15.7764 + 62.2612 × dOM intake (AIC = 2,755.1); and MCP (g/day) = 12.7311 + 15.3000 × ME intake (AIC = 3,007.3) presented lower values for the mean square error of prediction (MSEP) and its decomposition, and similar values for the concordance correlation coefficient (CCC) and for the residual mean square error (RMSE) when compared with equations fitted without an intercept. The intercept and slope pooled test was significant for equations without an intercept (P < 0.05), indicating that observed and predicted data differed. In contrast, predicted and observed data for complete equations were similar (P > 0.05).
publishDate 2021
dc.date.none.fl_str_mv 2021-06-10
2022-04-28T19:40:49Z
2022-04-28T19:40:49Z
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/10.3389/fvets.2021.650248
Frontiers in Veterinary Science, v. 8.
2297-1769
http://hdl.handle.net/11449/221819
10.3389/fvets.2021.650248
2-s2.0-85108368655
url http://dx.doi.org/10.3389/fvets.2021.650248
http://hdl.handle.net/11449/221819
identifier_str_mv Frontiers in Veterinary Science, v. 8.
2297-1769
10.3389/fvets.2021.650248
2-s2.0-85108368655
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Frontiers in Veterinary 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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