In vivo ultrasound and biometric measurements predict the empty body chemical composition in Nellore cattle
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , , , , |
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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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 |
_version_ |
1813546586350813184 |