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Registro Completo |
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Biblioteca(s): |
Embrapa Florestas. |
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Data corrente: |
05/07/1993 |
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Data da última atualização: |
11/07/2012 |
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Autoria: |
MOURA, V. P. G. |
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Título: |
Efeito da temperatura na germinação de sementes de Eucalyptus urophylla S. T. Blake. |
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Ano de publicação: |
1983 |
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Fonte/Imprenta: |
Silvicultura, São Paulo, v. 8, n. 28, p. 376-381, 1983. |
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ISSN: |
0583-3132 |
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Idioma: |
Português |
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Notas: |
Edição dos anais do 4º Congresso Florestal Brasileiro, 1982, Belo Horizonte. |
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Thesagro: |
Eucalyptus Urophylla; Semente. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 00534naa a2200157 a 4500
001 1288283
005 2012-07-11
008 1983 bl uuuu u00u1 u #d
022 $a0583-3132
100 1 $aMOURA, V. P. G.
245 $aEfeito da temperatura na germinação de sementes de Eucalyptus urophylla S. T. Blake.
260 $c1983
500 $aEdição dos anais do 4º Congresso Florestal Brasileiro, 1982, Belo Horizonte.
650 $aEucalyptus Urophylla
650 $aSemente
773 $tSilvicultura, São Paulo$gv. 8, n. 28, p. 376-381, 1983.
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Registro original: |
Embrapa Florestas (CNPF) |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Semiárido. Para informações adicionais entre em contato com cpatsa.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Gado de Leite; Embrapa Semiárido. |
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Data corrente: |
06/02/2014 |
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Data da última atualização: |
05/02/2024 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
B - 1 |
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Autoria: |
VIEIRA, P. A. S.; PEREIRA, L. G. R.; AZEVÊDO, J. A. G.; NEVES, A. L. A.; CHIZZOTTI, M. L.; SANTOS, R. D. dos; ARAUJO, G. G. L. de; MISTURA, C.; CHAVES, A. V. |
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Afiliação: |
PABLO ALMEIDA SAMPAIO VIEIRA, Universidade Federal do Vale do São Francisco; LUIZ GUSTAVO RIBEIRO PEREIRA, CNPGL; JOSÉ AUGUSTO GOMES AZEVÊDO, UESC; ANDRE LUIS ALVES NEVES, CNPGL; MÁRIO LUIZ CHIZZOTTI, UFLA; RAFAEL DANTAS DOS SANTOS, CPATSA; GHERMAN GARCIA LEAL DE ARAUJO, CPATSA; CLAUDIO MISTURA, Universidade do Estado da Bahia; ALEXANDRE VIEIRA CHAVES, University of Sydney, Australia. |
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Título: |
Development of mathematical models to predict dry matter intake in feedlot Santa Ines rams. |
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Ano de publicação: |
2013 |
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Fonte/Imprenta: |
Small Ruminant Research, v. 112, n. 1/3, p. 78-84, 2013. |
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DOI: |
https://doi.org/10.1016/j.smallrumres.2012.10.007 |
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Idioma: |
Inglês |
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Conteúdo: |
Mathematical models to predict the dry matter intake (DMI) of feedlot Santa Ines rams were developed and evaluated in this study. The available database had 100 experimental units from 13 studies. Study effect was integrated and random effects of their interactions as components of a hybrid model. The independent variables were initially adjusted to a model which included fixed effects for y-intercept and slope and random effects in y-intercept and slope study, using unstructured covariance model (e.g.: UN-unstructured). Study effect on database was verified, and then a meta-analysis procedure to develop DMI prediction equations was performed. For validation and comparisons between existing prediction equations in the national and international literature, independent data from one survey with 21 animals were used. Validation methods of the observed and predicted DMI were based on linear regression model adjustment of the observed values over predicted values. The following variables: average live weight (ALW), metabolic live weight (MLW0.75), average daily gain (ADG) and average daily gain2 (ADGsq) presented positive correlation with DMI. In contrast diet concentrate level showed a negative correlation. Among eight models examined, the following resulting equation [DMI (g/day) = 238.74 ± 114.56 (0.0398) + 31.3574 ± 4.2737 (<0.0001) × MLW + 1.2623 ±0.2128 (<0.0001) × ADG − 5.1837 ± 0.7448 (<0.0001) × CON] has been found as the best fit model to predict DMI in feedlot Santa Ines ram MenosMathematical models to predict the dry matter intake (DMI) of feedlot Santa Ines rams were developed and evaluated in this study. The available database had 100 experimental units from 13 studies. Study effect was integrated and random effects of their interactions as components of a hybrid model. The independent variables were initially adjusted to a model which included fixed effects for y-intercept and slope and random effects in y-intercept and slope study, using unstructured covariance model (e.g.: UN-unstructured). Study effect on database was verified, and then a meta-analysis procedure to develop DMI prediction equations was performed. For validation and comparisons between existing prediction equations in the national and international literature, independent data from one survey with 21 animals were used. Validation methods of the observed and predicted DMI were based on linear regression model adjustment of the observed values over predicted values. The following variables: average live weight (ALW), metabolic live weight (MLW0.75), average daily gain (ADG) and average daily gain2 (ADGsq) presented positive correlation with DMI. In contrast diet concentrate level showed a negative correlation. Among eight models examined, the following resulting equation [DMI (g/day) = 238.74 ± 114.56 (0.0398) + 31.3574 ± 4.2737 (<0.0001) × MLW + 1.2623 ±0.2128 (<0.0001) × ADG − 5.1837 ± 0.7448 (<0.0001) × CON] has been found as the best fit model to predict DMI in feedlot S... Mostrar Tudo |
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Palavras-Chave: |
Modelling; Nutritional requirements; Raça Santa Ines; Santa Ines. |
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Thesagro: |
Carneiro; Matéria Seca. |
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Thesaurus NAL: |
Dry matter intake; Meta-analysis; Ruminants. |
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Categoria do assunto: |
L Ciência Animal e Produtos de Origem Animal |
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Marc: |
LEADER 02527naa a2200337 a 4500
001 1979019
005 2024-02-05
008 2013 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.smallrumres.2012.10.007$2DOI
100 1 $aVIEIRA, P. A. S.
245 $aDevelopment of mathematical models to predict dry matter intake in feedlot Santa Ines rams.$h[electronic resource]
260 $c2013
520 $aMathematical models to predict the dry matter intake (DMI) of feedlot Santa Ines rams were developed and evaluated in this study. The available database had 100 experimental units from 13 studies. Study effect was integrated and random effects of their interactions as components of a hybrid model. The independent variables were initially adjusted to a model which included fixed effects for y-intercept and slope and random effects in y-intercept and slope study, using unstructured covariance model (e.g.: UN-unstructured). Study effect on database was verified, and then a meta-analysis procedure to develop DMI prediction equations was performed. For validation and comparisons between existing prediction equations in the national and international literature, independent data from one survey with 21 animals were used. Validation methods of the observed and predicted DMI were based on linear regression model adjustment of the observed values over predicted values. The following variables: average live weight (ALW), metabolic live weight (MLW0.75), average daily gain (ADG) and average daily gain2 (ADGsq) presented positive correlation with DMI. In contrast diet concentrate level showed a negative correlation. Among eight models examined, the following resulting equation [DMI (g/day) = 238.74 ± 114.56 (0.0398) + 31.3574 ± 4.2737 (<0.0001) × MLW + 1.2623 ±0.2128 (<0.0001) × ADG − 5.1837 ± 0.7448 (<0.0001) × CON] has been found as the best fit model to predict DMI in feedlot Santa Ines ram
650 $aDry matter intake
650 $aMeta-analysis
650 $aRuminants
650 $aCarneiro
650 $aMatéria Seca
653 $aModelling
653 $aNutritional requirements
653 $aRaça Santa Ines
653 $aSanta Ines
700 1 $aPEREIRA, L. G. R.
700 1 $aAZEVÊDO, J. A. G.
700 1 $aNEVES, A. L. A.
700 1 $aCHIZZOTTI, M. L.
700 1 $aSANTOS, R. D. dos
700 1 $aARAUJO, G. G. L. de
700 1 $aMISTURA, C.
700 1 $aCHAVES, A. V.
773 $tSmall Ruminant Research$gv. 112, n. 1/3, p. 78-84, 2013.
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