In vivo ultrasound and biometric measurements predict the empty body chemical composition in Nellore cattle

Detalhes bibliográficos
Autor(a) principal: Castilhos, A. M. [UNESP]
Data de Publicação: 2018
Outros Autores: Francisco, C. L. [UNESP], Branco, R. H., Bonilha, S. F.M., Mercadante, M. E.Z., Meirelles, P. R.L. [UNESP], Pariz, C. M. [UNESP], Jorge, A. M. [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1093/jas/sky081
http://hdl.handle.net/11449/176414
Resumo: Evaluation of the body chemical composition of beef cattle can only be measured postmortem and those data cannot be used in real production scenarios to adjust nutritional plans. The objective of this study was to develop multiple linear regression equations from in vivo measurements, such as ultrasound parameters [backfat thickness (uBFT, mm), rump fat thickness (uRF, mm), and ribeye area (uLMA, cm2)], shrunk body weight (SBW, kg), age (AG, d), hip height (HH, m), as well as from postmortem measurements (composition of the 9th to 11th rib section) to predict the empty body and carcass chemical composition for Nellore cattle. Thirty-three young bulls were used (339 ± 36.15 kg and 448 ± 17.78 d for initial weight and age, respectively). Empty body chemical composition (protein, fat, water, and ash in kg) was obtained by combining noncarcass and carcass components. Data were analyzed using the PROC REG procedure of SAS software. Mallows’ Cp values were close to the ideal value of number of independent variables in the prediction equations plus one. Equations to predict chemical components of both empty body and carcass using in vivo measurements presented higher R2 values than those determined by postmortem measurements. Chemical composition of the empty body using in vivo measurements was predicted with R2 > 0.73. Equations to predict chemical composition of the carcass from in vivo measurements showed R2 lower (R2 < 0.68) than observed for empty body, except for the water (R2 = 0.84). The independent variables SBW, uRF, and AG were sufficient to predict the fat, water, energy components of the empty body, whereas for estimation of protein content the uRF, HH, and SBW were satisfactory. For the calculation of the ash, the SBW variable in the equation was sufficient. Chemical compounds from components of the empty body of Nellore cattle can be calculated by the following equations: protein (kg) = 47.92 + 0.18 × SBW − 1.46 × uRF − 30.72 × HH (R2 = 0.94, RMSPE = 1.79); fat (kg) = 11.33 + 0.16 × SBW + 2.09 × uRF − 0.06 × AG (R2 = 0.74, RMSPE = 4.18); water (kg) = − 34.00 + 0.55 × SBW + 0.10 × AG − 2.34 × uRF (R2 = 0.96, RMSPE = 5.47). In conclusion, the coefficients of determination (for determining the chemical composition of the empty body) of the equations derived from in vivo measures were higher than those of the equations obtained from rib section measurements taken postmortem, and better than coefficients of determination of the equations to predict the chemical composition of the carcass.
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spelling In vivo ultrasound and biometric measurements predict the empty body chemical composition in Nellore cattleBeef cattleChemical compositionUltrasoundEvaluation of the body chemical composition of beef cattle can only be measured postmortem and those data cannot be used in real production scenarios to adjust nutritional plans. The objective of this study was to develop multiple linear regression equations from in vivo measurements, such as ultrasound parameters [backfat thickness (uBFT, mm), rump fat thickness (uRF, mm), and ribeye area (uLMA, cm2)], shrunk body weight (SBW, kg), age (AG, d), hip height (HH, m), as well as from postmortem measurements (composition of the 9th to 11th rib section) to predict the empty body and carcass chemical composition for Nellore cattle. Thirty-three young bulls were used (339 ± 36.15 kg and 448 ± 17.78 d for initial weight and age, respectively). Empty body chemical composition (protein, fat, water, and ash in kg) was obtained by combining noncarcass and carcass components. Data were analyzed using the PROC REG procedure of SAS software. Mallows’ Cp values were close to the ideal value of number of independent variables in the prediction equations plus one. Equations to predict chemical components of both empty body and carcass using in vivo measurements presented higher R2 values than those determined by postmortem measurements. Chemical composition of the empty body using in vivo measurements was predicted with R2 > 0.73. Equations to predict chemical composition of the carcass from in vivo measurements showed R2 lower (R2 < 0.68) than observed for empty body, except for the water (R2 = 0.84). The independent variables SBW, uRF, and AG were sufficient to predict the fat, water, energy components of the empty body, whereas for estimation of protein content the uRF, HH, and SBW were satisfactory. For the calculation of the ash, the SBW variable in the equation was sufficient. Chemical compounds from components of the empty body of Nellore cattle can be calculated by the following equations: protein (kg) = 47.92 + 0.18 × SBW − 1.46 × uRF − 30.72 × HH (R2 = 0.94, RMSPE = 1.79); fat (kg) = 11.33 + 0.16 × SBW + 2.09 × uRF − 0.06 × AG (R2 = 0.74, RMSPE = 4.18); water (kg) = − 34.00 + 0.55 × SBW + 0.10 × AG − 2.34 × uRF (R2 = 0.96, RMSPE = 5.47). In conclusion, the coefficients of determination (for determining the chemical composition of the empty body) of the equations derived from in vivo measures were higher than those of the equations obtained from rib section measurements taken postmortem, and better than coefficients of determination of the equations to predict the chemical composition of the carcass.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Department of Breeding and Animal Nutrition São Paulo State University (UNESP) School of Veterinary Medicine and Animal Science (FMVZ)Department of Animal Production São Paulo State University (UNESP) School of Veterinary Medicine and Animal Science (FMVZ)Centro APTA Bovinos de Corte-Instituto de Zootecnia-Secretaria de Agricultura e Abastecimento do Estado de São PauloDepartment of Breeding and Animal Nutrition São Paulo State University (UNESP) School of Veterinary Medicine and Animal Science (FMVZ)Department of Animal Production São Paulo State University (UNESP) School of Veterinary Medicine and Animal Science (FMVZ)FAPESP: 2005/60042-2Universidade Estadual Paulista (Unesp)Centro APTA Bovinos de Corte-Instituto de Zootecnia-Secretaria de Agricultura e Abastecimento do Estado de São PauloCastilhos, A. M. [UNESP]Francisco, C. L. [UNESP]Branco, R. H.Bonilha, S. F.M.Mercadante, M. E.Z.Meirelles, P. R.L. [UNESP]Pariz, C. M. [UNESP]Jorge, A. M. [UNESP]2018-12-11T17:20:42Z2018-12-11T17:20:42Z2018-05-04info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article1678-1687http://dx.doi.org/10.1093/jas/sky081Journal of Animal Science, v. 96, n. 5, p. 1678-1687, 2018.1525-31630021-8812http://hdl.handle.net/11449/17641410.1093/jas/sky0812-s2.0-8504817043781926198588684700000-0001-9168-5081Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengJournal of Animal Science0,848info:eu-repo/semantics/openAccess2024-09-09T13:01:11Zoai:repositorio.unesp.br:11449/176414Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestrepositoriounesp@unesp.bropendoar:29462024-09-09T13:01:11Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv In vivo ultrasound and biometric measurements predict the empty body chemical composition in Nellore cattle
title In vivo ultrasound and biometric measurements predict the empty body chemical composition in Nellore cattle
spellingShingle In vivo ultrasound and biometric measurements predict the empty body chemical composition in Nellore cattle
Castilhos, A. M. [UNESP]
Beef cattle
Chemical composition
Ultrasound
title_short In vivo ultrasound and biometric measurements predict the empty body chemical composition in Nellore cattle
title_full In vivo ultrasound and biometric measurements predict the empty body chemical composition in Nellore cattle
title_fullStr In vivo ultrasound and biometric measurements predict the empty body chemical composition in Nellore cattle
title_full_unstemmed In vivo ultrasound and biometric measurements predict the empty body chemical composition in Nellore cattle
title_sort In vivo ultrasound and biometric measurements predict the empty body chemical composition in Nellore cattle
author Castilhos, A. M. [UNESP]
author_facet Castilhos, A. M. [UNESP]
Francisco, C. L. [UNESP]
Branco, R. H.
Bonilha, S. F.M.
Mercadante, M. E.Z.
Meirelles, P. R.L. [UNESP]
Pariz, C. M. [UNESP]
Jorge, A. M. [UNESP]
author_role author
author2 Francisco, C. L. [UNESP]
Branco, R. H.
Bonilha, S. F.M.
Mercadante, M. E.Z.
Meirelles, P. R.L. [UNESP]
Pariz, C. M. [UNESP]
Jorge, A. M. [UNESP]
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
Centro APTA Bovinos de Corte-Instituto de Zootecnia-Secretaria de Agricultura e Abastecimento do Estado de São Paulo
dc.contributor.author.fl_str_mv Castilhos, A. M. [UNESP]
Francisco, C. L. [UNESP]
Branco, R. H.
Bonilha, S. F.M.
Mercadante, M. E.Z.
Meirelles, P. R.L. [UNESP]
Pariz, C. M. [UNESP]
Jorge, A. M. [UNESP]
dc.subject.por.fl_str_mv Beef cattle
Chemical composition
Ultrasound
topic Beef cattle
Chemical composition
Ultrasound
description Evaluation of the body chemical composition of beef cattle can only be measured postmortem and those data cannot be used in real production scenarios to adjust nutritional plans. The objective of this study was to develop multiple linear regression equations from in vivo measurements, such as ultrasound parameters [backfat thickness (uBFT, mm), rump fat thickness (uRF, mm), and ribeye area (uLMA, cm2)], shrunk body weight (SBW, kg), age (AG, d), hip height (HH, m), as well as from postmortem measurements (composition of the 9th to 11th rib section) to predict the empty body and carcass chemical composition for Nellore cattle. Thirty-three young bulls were used (339 ± 36.15 kg and 448 ± 17.78 d for initial weight and age, respectively). Empty body chemical composition (protein, fat, water, and ash in kg) was obtained by combining noncarcass and carcass components. Data were analyzed using the PROC REG procedure of SAS software. Mallows’ Cp values were close to the ideal value of number of independent variables in the prediction equations plus one. Equations to predict chemical components of both empty body and carcass using in vivo measurements presented higher R2 values than those determined by postmortem measurements. Chemical composition of the empty body using in vivo measurements was predicted with R2 > 0.73. Equations to predict chemical composition of the carcass from in vivo measurements showed R2 lower (R2 < 0.68) than observed for empty body, except for the water (R2 = 0.84). The independent variables SBW, uRF, and AG were sufficient to predict the fat, water, energy components of the empty body, whereas for estimation of protein content the uRF, HH, and SBW were satisfactory. For the calculation of the ash, the SBW variable in the equation was sufficient. Chemical compounds from components of the empty body of Nellore cattle can be calculated by the following equations: protein (kg) = 47.92 + 0.18 × SBW − 1.46 × uRF − 30.72 × HH (R2 = 0.94, RMSPE = 1.79); fat (kg) = 11.33 + 0.16 × SBW + 2.09 × uRF − 0.06 × AG (R2 = 0.74, RMSPE = 4.18); water (kg) = − 34.00 + 0.55 × SBW + 0.10 × AG − 2.34 × uRF (R2 = 0.96, RMSPE = 5.47). In conclusion, the coefficients of determination (for determining the chemical composition of the empty body) of the equations derived from in vivo measures were higher than those of the equations obtained from rib section measurements taken postmortem, and better than coefficients of determination of the equations to predict the chemical composition of the carcass.
publishDate 2018
dc.date.none.fl_str_mv 2018-12-11T17:20:42Z
2018-12-11T17:20:42Z
2018-05-04
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/sky081
Journal of Animal Science, v. 96, n. 5, p. 1678-1687, 2018.
1525-3163
0021-8812
http://hdl.handle.net/11449/176414
10.1093/jas/sky081
2-s2.0-85048170437
8192619858868470
0000-0001-9168-5081
url http://dx.doi.org/10.1093/jas/sky081
http://hdl.handle.net/11449/176414
identifier_str_mv Journal of Animal Science, v. 96, n. 5, p. 1678-1687, 2018.
1525-3163
0021-8812
10.1093/jas/sky081
2-s2.0-85048170437
8192619858868470
0000-0001-9168-5081
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Journal of Animal Science
0,848
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 1678-1687
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 repositoriounesp@unesp.br
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