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| Acesso ao texto completo restrito à biblioteca da Embrapa Pecuária Sudeste. Para informações adicionais entre em contato com cppse.biblioteca@embrapa.br. |
Registro Completo |
Biblioteca(s): |
Embrapa Pecuária Sudeste. |
Data corrente: |
10/01/2023 |
Data da última atualização: |
16/02/2024 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
LOBO, A. A. G.; CÔNSOLO, N. R. B.; DIAS, J.; MENEZES, A. C. B.; MARTINS, T. DA S.; SILVA, J.; MACHADO, F. S.; MARCONDES, M. I.; PFLANZER JR, S. B.; NASSU, R. T.; SCHEFFLER, T. L.; CHIZZOTTI, M. L. |
Afiliação: |
ANNELISE AILA GOMES LOBO, University of Sao Paulo; NARA REGINA BRANDÃO CÔNSOLO, University of Sao Paulo; JULIANA DIAS, Federal University of Viçosa; ANA CLARA BAIÃO MENEZES, Federal University of Viçosa; TAIANE DA SILVA MARTINS, University of Sao Paulo; JULIANA SILVA, University of Sao Paulo; FERNANDA SAMARINI MACHADO, CNPGL; MARCOS INACIO MARCONDES, Federal University of Viçosa; SÉRGIO BERTELLI PFLANZER JR, UNICAMP; RENATA TIEKO NASSU, CPPSE; TRACY L. SCHEFFLER, University of Florida; MARIO LUIZ CHIZZOTTI, Federal University of Viçosa. |
Título: |
The use of dual energy x-ray absorptiometry (DXA) to predict the veal carcass composition. |
Ano de publicação: |
2023 |
Fonte/Imprenta: |
Journal of Food Composition and Analysis, v. 117, apr. 2023, 105104. |
DOI: |
https://doi.org/10.1016/j.jfca.2022.105104 |
Idioma: |
Inglês |
Conteúdo: |
The objective of this study was to evaluate the potential of dual energy X-ray absorptiometry (DXA) to estimate the carcass composition of veal calves. A total of 15 newborn Holstein × Gyr male calves were randomly assigned to two dietary treatments: calves fed exclusively milk or fed milk + concentrate ad libitum. Calves were assigned to four slaughter groups (7, 28, 49 and 63 days of age) and after 24 h of chilling carcasses were analyzed by DXA using the enCORE software to obtain fat, lean tissue, and bone mineral content and density. Afterward, carcasses were dissected into lean, fat, and bone tissues that were ground and lyophilized to determine the carcasses chemical composition. The DXA predicted the protein (P < 0.0001, R2 = 0.7290), mineral (P = 0.002, R2 = 0.6119) contents, proportions of muscle (P < 0.001, R2 = 0.6986) and bone of veal carcasses (P < 0.0001, R2 = 0.6982), but not fat (P = 0.9557, R2 = 0.002). In conclusion, the DXA measured values were able to predict veal carcass protein, mineral contents, lean and bones amount but was not precise enough to detect the fat tissue on lean carcasses such as those from veal calves. |
Palavras-Chave: |
Ash; Ether extract; Lean tissue; Protein. |
Thesaurus Nal: |
Body composition; Calves. |
Categoria do assunto: |
Q Alimentos e Nutrição Humana |
Marc: |
LEADER 02140naa a2200337 a 4500 001 2150856 005 2024-02-16 008 2023 bl uuuu u00u1 u #d 024 7 $ahttps://doi.org/10.1016/j.jfca.2022.105104$2DOI 100 1 $aLOBO, A. A. G. 245 $aThe use of dual energy x-ray absorptiometry (DXA) to predict the veal carcass composition.$h[electronic resource] 260 $c2023 520 $aThe objective of this study was to evaluate the potential of dual energy X-ray absorptiometry (DXA) to estimate the carcass composition of veal calves. A total of 15 newborn Holstein × Gyr male calves were randomly assigned to two dietary treatments: calves fed exclusively milk or fed milk + concentrate ad libitum. Calves were assigned to four slaughter groups (7, 28, 49 and 63 days of age) and after 24 h of chilling carcasses were analyzed by DXA using the enCORE software to obtain fat, lean tissue, and bone mineral content and density. Afterward, carcasses were dissected into lean, fat, and bone tissues that were ground and lyophilized to determine the carcasses chemical composition. The DXA predicted the protein (P < 0.0001, R2 = 0.7290), mineral (P = 0.002, R2 = 0.6119) contents, proportions of muscle (P < 0.001, R2 = 0.6986) and bone of veal carcasses (P < 0.0001, R2 = 0.6982), but not fat (P = 0.9557, R2 = 0.002). In conclusion, the DXA measured values were able to predict veal carcass protein, mineral contents, lean and bones amount but was not precise enough to detect the fat tissue on lean carcasses such as those from veal calves. 650 $aBody composition 650 $aCalves 653 $aAsh 653 $aEther extract 653 $aLean tissue 653 $aProtein 700 1 $aCÔNSOLO, N. R. B. 700 1 $aDIAS, J. 700 1 $aMENEZES, A. C. B. 700 1 $aMARTINS, T. DA S. 700 1 $aSILVA, J. 700 1 $aMACHADO, F. S. 700 1 $aMARCONDES, M. I. 700 1 $aPFLANZER JR, S. B. 700 1 $aNASSU, R. T. 700 1 $aSCHEFFLER, T. L. 700 1 $aCHIZZOTTI, M. L. 773 $tJournal of Food Composition and Analysis$gv. 117, apr. 2023, 105104.
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Embrapa Pecuária Sudeste (CPPSE) |
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| Acesso ao texto completo restrito à biblioteca da Embrapa Agroindústria Tropical. Para informações adicionais entre em contato com cnpat.biblioteca@embrapa.br. |
Registro Completo
Biblioteca(s): |
Embrapa Agroindústria Tropical. |
Data corrente: |
16/12/2016 |
Data da última atualização: |
23/05/2018 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
VASCONCELOS, E. A. F.; LEITAO, R. C.; SANTAELLA, S. T. |
Afiliação: |
EDUARDO AUGUSTO FELIPE DE VASCONCELOS, Doutorando em Ecologia e Recursos Naturais, Universidade Federal do Ceará; RENATO CARRHA LEITAO, CNPAT; SANDRA TEDDE SANTAELLA, Instituto de Ciências do Mar (LABOMAR), Universidade Federal do Ceará. |
Título: |
Factors that affect bacterial ecology in hydrogen-producing anaerobic reactors. |
Ano de publicação: |
2016 |
Fonte/Imprenta: |
BioEnergy Research, v. 9, n. 4, p. 1260-1271, 2016. |
Idioma: |
Inglês |
Palavras-Chave: |
Bacterial diversity; Bactérias; Dark fermentation; Diversidade bacterial; Energia renovável; Fermentação escura; Renewable energy. |
Thesagro: |
Bactéria. |
Categoria do assunto: |
-- |
Marc: |
LEADER 00697naa a2200229 a 4500 001 2058812 005 2018-05-23 008 2016 bl uuuu u00u1 u #d 100 1 $aVASCONCELOS, E. A. F. 245 $aFactors that affect bacterial ecology in hydrogen-producing anaerobic reactors.$h[electronic resource] 260 $c2016 650 $aBactéria 653 $aBacterial diversity 653 $aBactérias 653 $aDark fermentation 653 $aDiversidade bacterial 653 $aEnergia renovável 653 $aFermentação escura 653 $aRenewable energy 700 1 $aLEITAO, R. C. 700 1 $aSANTAELLA, S. T. 773 $tBioEnergy Research$gv. 9, n. 4, p. 1260-1271, 2016.
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