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| 11. |  | FIALHO, J. de F.; VIEIRA, E. A. (ed.). Mandioca no cerrado: orientações técnicas. 2. ed. rev. e ampl. Brasília, DF: Embrapa, 2013. 203 p. Autores: Camila Ferreira Lobo, CNPq; Charles Martins de Oliveira, CPAC; Eduardo Alano Vieira, CPAC; Francisco Duarte Fernandes, CPAC; José de Ribamar Nazareno dos Anjos, CPAC; Josefino de Freitas Fialho, CPAC; Jozeneida Lúcia Pimenta de...| Biblioteca(s): Embrapa Amazônia Ocidental; Embrapa Cerrados; Embrapa Meio-Norte; Embrapa Unidades Centrais. |
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| 12. | | VIEIRA, E. A.; FIALHO, J. de F.; SILVA, M. S. Estado da arte e estratégias do melhoramento participativo: o exemplo da mandioca no Cerrado. In: FALEIRO, F. G.; FARIAS NETO, A. L. de; RIBEIRO JÚNIOR, W. Q. (Ed.). Pré-melhoramento, melhoramento e pós-melhoramento: estratégias e desafios. Planaltina, DF: Embrapa Cerrados, 2008. cap. 7, p. 107-124.| Biblioteca(s): Embrapa Cerrados. |
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| 13. | | CHAIB-FERREIRA, A.; VIEIRA, E. A.; FIALHO, J. de F. Estratégia para a geração de uma coleção nuclear do banco regional de germoplasma de mandioca do Cerrado In: ENCONTRO DE JOVENS TALENTOS DA EMBRAPA CERRADOS, 4., 2009, Planaltina, DF. Resumos apresentados... Planaltina, DF: Embrapa Cerrados, 2009. p. 25-26. (Embrapa Cerrados. Documentos, 243).| Biblioteca(s): Embrapa Cerrados. |
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| Registros recuperados : 294 | |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Gado de Leite. Para informações adicionais entre em contato com cnpgl.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Gado de Leite. |
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Data corrente: |
23/09/2021 |
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Data da última atualização: |
23/09/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 2 |
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Autoria: |
VIEIRA, E. A.; BELLI, A. L.; CAMPOLIA, J. P.; RODRIGUES, J. P. P.; COELHO, S. G.; CAMPOS, M. M.; TOMICH, T. R.; PEREIRA, L. G. R. |
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Afiliação: |
EDVALDO ALVES VIEIRA, Universidade Estadual do Sudoeste da Bahia; ANNA LUIZA BELLI, Universidade Federal de Minas Gerais; JOANA PALHARES CAMPOLINA, Universidade Federal de Minas Gerais; JOAO PAULO PACHECO RODRIGUES, Universidade Federal do Sul e Sudeste do Pará; SANDRA GESTEIRA COELHO, Universidade Federal de Minas Gerais; MARIANA MAGALHAES CAMPOS, CNPGL; THIERRY RIBEIRO TOMICH, CNPGL; LUIZ GUSTAVO RIBEIRO PEREIRA, CNPGL. |
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Título: |
Screening microchip sites to predict body temperature in young calves. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Journal of Thermal Biology, v. 100, 103052, 2021. |
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DOI: |
https://doi.org/10.1016/j.jtherbio.2021.103052 |
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Idioma: |
Inglês |
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Conteúdo: |
Thermal microchip sensors can automate body temperature measurements. The best site of implantation is still unknown, and the accuracy and precision of body temperature predictions based on microchip data need to be investigated. The aim of this study was to investigate the best site for microchip implant for monitoring body temperature in dairy calves. Seventeen calves were used (32.2 ± 5.2 kg of body weight) and the microchips were implanted four days after birth. The microchips were implanted at navel, ear and tail base (subcutaneous), neck (cleidocephalicus) and internal face of leg (gracilis) (intramuscular). Rectal temperature (RT, ◦C), obtained with a clinical thermometer, was considered as core temperature. Air temperature (AT), relative humidity (RH) and the temperature and humidity index (THI) were evaluated at the same time of rectal and microchip temperature measurements over 56 days. The range of AT, RH and THI was 7.6?34.4 ◦C, 17.5?99.0% and 50.6 to 91.5. The average for rectum, ear, neck, tail, leg, and navel were 38.7; 36.9; 38.0; 37.0, 37.8 and 37.0 ◦C. The intramuscular implantations had closest values to RT. The correlations between RT and ear, neck, tail, leg, and navel temperatures were 0.56, 0.60, 0.60, 0.53 e 0.48. The RT prediction based on microchip data had precision (rc) ranged between 0.49 and 0.60 and accuracy (Cb) between 0.79 and 0.88. The inclusion of AT, RH and THI as predictive variables in models decrease the mean absolute error (23%) and increase the precision (21.3%) and accuracy (10.2%). The Concordance Correlation Coefficient and root-mean-square error for equations using tail or neck microchips were 0.68 and 0.67, and 0.29 and 0.28 ◦C, respectively. The tail base is a promising site for microchip implantation to predict rectal temperature. The inclusion of air temperature as a predictive variable in the models is recommended. MenosThermal microchip sensors can automate body temperature measurements. The best site of implantation is still unknown, and the accuracy and precision of body temperature predictions based on microchip data need to be investigated. The aim of this study was to investigate the best site for microchip implant for monitoring body temperature in dairy calves. Seventeen calves were used (32.2 ± 5.2 kg of body weight) and the microchips were implanted four days after birth. The microchips were implanted at navel, ear and tail base (subcutaneous), neck (cleidocephalicus) and internal face of leg (gracilis) (intramuscular). Rectal temperature (RT, ◦C), obtained with a clinical thermometer, was considered as core temperature. Air temperature (AT), relative humidity (RH) and the temperature and humidity index (THI) were evaluated at the same time of rectal and microchip temperature measurements over 56 days. The range of AT, RH and THI was 7.6?34.4 ◦C, 17.5?99.0% and 50.6 to 91.5. The average for rectum, ear, neck, tail, leg, and navel were 38.7; 36.9; 38.0; 37.0, 37.8 and 37.0 ◦C. The intramuscular implantations had closest values to RT. The correlations between RT and ear, neck, tail, leg, and navel temperatures were 0.56, 0.60, 0.60, 0.53 e 0.48. The RT prediction based on microchip data had precision (rc) ranged between 0.49 and 0.60 and accuracy (Cb) between 0.79 and 0.88. The inclusion of AT, RH and THI as predictive variables in models decrease the mean absolute... Mostrar Tudo |
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Palavras-Chave: |
Core temperature; Precision livestock; Sensors. |
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Thesagro: |
Bovino; Sanidade Animal. |
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Thesaurus NAL: |
Animal health. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02755naa a2200289 a 4500
001 2134743
005 2021-09-23
008 2021 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.jtherbio.2021.103052$2DOI
100 1 $aVIEIRA, E. A.
245 $aScreening microchip sites to predict body temperature in young calves.$h[electronic resource]
260 $c2021
520 $aThermal microchip sensors can automate body temperature measurements. The best site of implantation is still unknown, and the accuracy and precision of body temperature predictions based on microchip data need to be investigated. The aim of this study was to investigate the best site for microchip implant for monitoring body temperature in dairy calves. Seventeen calves were used (32.2 ± 5.2 kg of body weight) and the microchips were implanted four days after birth. The microchips were implanted at navel, ear and tail base (subcutaneous), neck (cleidocephalicus) and internal face of leg (gracilis) (intramuscular). Rectal temperature (RT, ◦C), obtained with a clinical thermometer, was considered as core temperature. Air temperature (AT), relative humidity (RH) and the temperature and humidity index (THI) were evaluated at the same time of rectal and microchip temperature measurements over 56 days. The range of AT, RH and THI was 7.6?34.4 ◦C, 17.5?99.0% and 50.6 to 91.5. The average for rectum, ear, neck, tail, leg, and navel were 38.7; 36.9; 38.0; 37.0, 37.8 and 37.0 ◦C. The intramuscular implantations had closest values to RT. The correlations between RT and ear, neck, tail, leg, and navel temperatures were 0.56, 0.60, 0.60, 0.53 e 0.48. The RT prediction based on microchip data had precision (rc) ranged between 0.49 and 0.60 and accuracy (Cb) between 0.79 and 0.88. The inclusion of AT, RH and THI as predictive variables in models decrease the mean absolute error (23%) and increase the precision (21.3%) and accuracy (10.2%). The Concordance Correlation Coefficient and root-mean-square error for equations using tail or neck microchips were 0.68 and 0.67, and 0.29 and 0.28 ◦C, respectively. The tail base is a promising site for microchip implantation to predict rectal temperature. The inclusion of air temperature as a predictive variable in the models is recommended.
650 $aAnimal health
650 $aBovino
650 $aSanidade Animal
653 $aCore temperature
653 $aPrecision livestock
653 $aSensors
700 1 $aBELLI, A. L.
700 1 $aCAMPOLIA, J. P.
700 1 $aRODRIGUES, J. P. P.
700 1 $aCOELHO, S. G.
700 1 $aCAMPOS, M. M.
700 1 $aTOMICH, T. R.
700 1 $aPEREIRA, L. G. R.
773 $tJournal of Thermal Biology$gv. 100, 103052, 2021.
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