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Registro Completo |
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Biblioteca(s): |
Embrapa Semiárido. |
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Data corrente: |
03/12/2013 |
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Data da última atualização: |
03/12/2013 |
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Tipo da produção científica: |
Resumo em Anais de Congresso |
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Autoria: |
MENEZES, K. A. S.; SILVA, A. F.; NUNES, G. F. de O.; SAMPAIO, A. A.; VIEIRA, L. M. V.; FERNANDES JUNIOR, P. I. |
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Afiliação: |
KELLY ALEXSANDRA SOUZA MENEZES, Mestranda UNES-DTCS; ALEKSANDRO FERREIRA DA SILVA, UNEB-DTCS; GERSIKA FAKIRRA DE OLIVEIRA NUNES, Mestranda UNEB-DTCS; ALINE ARAÚJO SAMPAIO, Mestranda UNEB-DTCS; LINDETE MÍRIA VIEIRA MARTINS, UNEB-DTCS; PAULO IVAN FERNANDES JUNIOR, CPATSA. |
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Título: |
Nodulação e desenvolvimento vegetativo de leucena (Leucaena leucocephala) (lam.) de wit) em diferentes solos do Semiárido. |
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Ano de publicação: |
2013 |
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Fonte/Imprenta: |
In: REUNIÃO ANUAL DA SOCIEDADE BRASILEIRA PARA O PROGRESSO DA CIÊNCIA, 65., 2013, Recife. Ciência para um novo Brasil. Recife: UFPE: SBPC, 2013. |
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Páginas: |
2 p. |
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Idioma: |
Português |
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Conteúdo: |
Avaliar a capacidade de nodulação de leucena (Leucaena leucocephala (Lam.) de Wit) cultivada em diferentes amostras de solos do Semiárido. |
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Palavras-Chave: |
Bioma Caatinga; Fixação biológica de nitrogênio; Leucena. |
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Thesagro: |
Leucaena Leucocephala; Nodulação; Solo. |
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Thesaurus Nal: |
Fabaceae; Soil. |
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Categoria do assunto: |
S Ciências Biológicas |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/93472/1/Paulo-Ivan-4.pdf
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Marc: |
LEADER 01071nam a2200277 a 4500
001 1972821
005 2013-12-03
008 2013 bl uuuu u00u1 u #d
100 1 $aMENEZES, K. A. S.
245 $aNodulação e desenvolvimento vegetativo de leucena (Leucaena leucocephala) (lam.) de wit) em diferentes solos do Semiárido.$h[electronic resource]
260 $aIn: REUNIÃO ANUAL DA SOCIEDADE BRASILEIRA PARA O PROGRESSO DA CIÊNCIA, 65., 2013, Recife. Ciência para um novo Brasil. Recife: UFPE: SBPC$c2013
300 $a2 p.
520 $aAvaliar a capacidade de nodulação de leucena (Leucaena leucocephala (Lam.) de Wit) cultivada em diferentes amostras de solos do Semiárido.
650 $aFabaceae
650 $aSoil
650 $aLeucaena Leucocephala
650 $aNodulação
650 $aSolo
653 $aBioma Caatinga
653 $aFixação biológica de nitrogênio
653 $aLeucena
700 1 $aSILVA, A. F.
700 1 $aNUNES, G. F. de O.
700 1 $aSAMPAIO, A. A.
700 1 $aVIEIRA, L. M. V.
700 1 $aFERNANDES JUNIOR, P. I.
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Registro original: |
Embrapa Semiárido (CPATSA) |
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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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Embrapa Gado de Leite (CNPGL) |
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