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Registro Completo |
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Biblioteca(s): |
Embrapa Pecuária Sul. |
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Data corrente: |
28/11/2011 |
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Data da última atualização: |
15/02/2012 |
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Tipo da produção científica: |
Resumo em Anais de Congresso |
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Autoria: |
LACA, E. A.; GENRO, T. C. M.; GENRO NETO, J. S. |
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Afiliação: |
EMILIO ANDRÉS LACA, University of California Davis, CA, USA; TERESA CRISTINA MORAES GENRO, CPPSUL; JAIRO SILVEIRA GENRO NETO, Universidade Federal de Santa Maria, RS, Brasil. |
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Título: |
Bayesian hierarchical models to improve estimation of diet composition by alkane profiles. |
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Ano de publicação: |
2011 |
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Fonte/Imprenta: |
In: REUNIÓN DE LA ASOCIACIÓN LATINOAMERICANA DE PRODUCCIÓN ANIMAL, 22., 2011, Montevideo, Uruguay. Memorias... Montevideo: Asociación Uruguaya de Producción Animal, 2011. |
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Descrição Física: |
1 CD-ROM. |
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Idioma: |
Inglês |
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Conteúdo: |
Alkane profiles in forage and feces are used to determine diet composition, essentially by inverting a linear mixing equation. Depending on the number of dietary components, number of alkanes and difference in forage profiles, the linear equations can be over or underdetermined. We compared the typical non-negative least squares (NNLS) method against a novel Bayesian hierarchical model (BHM) where diet composition is represented as latent variables modeled with parameters shared by the models for fecal and forage profiles. Forage and fecal profiles were obtained from steers grazing either Brachiaria brizantha cv Marandu, Panicum maximum cv. Mombaça, or Pennisetum purpureum cv. Cameroon at Embrapa Beef Cattle, Campo Grande, MS, Brazil. Herbage and fecal samples were collected in the dry and early wet seasons. Herbage was sampled by 20-cm horizons sorted into stem/sheath and leaf blade as dietary components. Feces were collected from 6 animals in the morning and afternoon. Fecal profiles were corrected by faecal recoveries using mean values from the literature. Distributions of diets estimated by NNLS were obtained by Monte Carlo simulation of profiles using parameters and covariance matrices estimated from data. The BHM yielded posterior distributions directly by using Monte Carlo Markov Chains. NNLS resulted in highly variables diets with distributions that were clearly non-normal. BHM resulted in quasi-normal posterior distributions. We conclude that both approaches are better than the normal approach where diet covariances are calculated ad-hoc. The BHM method has the potential to be vastly superior because it allows the simultaneous integration in a formally correct manner, however, convergence can be difficult. MenosAlkane profiles in forage and feces are used to determine diet composition, essentially by inverting a linear mixing equation. Depending on the number of dietary components, number of alkanes and difference in forage profiles, the linear equations can be over or underdetermined. We compared the typical non-negative least squares (NNLS) method against a novel Bayesian hierarchical model (BHM) where diet composition is represented as latent variables modeled with parameters shared by the models for fecal and forage profiles. Forage and fecal profiles were obtained from steers grazing either Brachiaria brizantha cv Marandu, Panicum maximum cv. Mombaça, or Pennisetum purpureum cv. Cameroon at Embrapa Beef Cattle, Campo Grande, MS, Brazil. Herbage and fecal samples were collected in the dry and early wet seasons. Herbage was sampled by 20-cm horizons sorted into stem/sheath and leaf blade as dietary components. Feces were collected from 6 animals in the morning and afternoon. Fecal profiles were corrected by faecal recoveries using mean values from the literature. Distributions of diets estimated by NNLS were obtained by Monte Carlo simulation of profiles using parameters and covariance matrices estimated from data. The BHM yielded posterior distributions directly by using Monte Carlo Markov Chains. NNLS resulted in highly variables diets with distributions that were clearly non-normal. BHM resulted in quasi-normal posterior distributions. We conclude that both approaches are bet... Mostrar Tudo |
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Palavras-Chave: |
Melhoramento forrageira; Modelo bayesiano; Perfil alcalino. |
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Categoria do assunto: |
K Ciência Florestal e Produtos de Origem Vegetal |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/48108/1/G158-pagina173poster.pdf
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Marc: |
LEADER 02430nam a2200181 a 4500
001 1907473
005 2012-02-15
008 2011 bl uuuu u00u1 u #d
100 1 $aLACA, E. A.
245 $aBayesian hierarchical models to improve estimation of diet composition by alkane profiles.$h[electronic resource]
260 $aIn: REUNIÓN DE LA ASOCIACIÓN LATINOAMERICANA DE PRODUCCIÓN ANIMAL, 22., 2011, Montevideo, Uruguay. Memorias... Montevideo: Asociación Uruguaya de Producción Animal$c2011
300 $c1 CD-ROM.
520 $aAlkane profiles in forage and feces are used to determine diet composition, essentially by inverting a linear mixing equation. Depending on the number of dietary components, number of alkanes and difference in forage profiles, the linear equations can be over or underdetermined. We compared the typical non-negative least squares (NNLS) method against a novel Bayesian hierarchical model (BHM) where diet composition is represented as latent variables modeled with parameters shared by the models for fecal and forage profiles. Forage and fecal profiles were obtained from steers grazing either Brachiaria brizantha cv Marandu, Panicum maximum cv. Mombaça, or Pennisetum purpureum cv. Cameroon at Embrapa Beef Cattle, Campo Grande, MS, Brazil. Herbage and fecal samples were collected in the dry and early wet seasons. Herbage was sampled by 20-cm horizons sorted into stem/sheath and leaf blade as dietary components. Feces were collected from 6 animals in the morning and afternoon. Fecal profiles were corrected by faecal recoveries using mean values from the literature. Distributions of diets estimated by NNLS were obtained by Monte Carlo simulation of profiles using parameters and covariance matrices estimated from data. The BHM yielded posterior distributions directly by using Monte Carlo Markov Chains. NNLS resulted in highly variables diets with distributions that were clearly non-normal. BHM resulted in quasi-normal posterior distributions. We conclude that both approaches are better than the normal approach where diet covariances are calculated ad-hoc. The BHM method has the potential to be vastly superior because it allows the simultaneous integration in a formally correct manner, however, convergence can be difficult.
653 $aMelhoramento forrageira
653 $aModelo bayesiano
653 $aPerfil alcalino
700 1 $aGENRO, T. C. M.
700 1 $aGENRO NETO, J. S.
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Registro original: |
Embrapa Pecuária Sul (CPPSUL) |
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| Registros recuperados : 2 | |
| 1. |  | MAESTRI, R.; GRACA, L. R.; SIMOES, J. W.; FREITAS, A. J. P. Análise de adubação fosfatada na produção física e econômica da acácia-negra (Acacia mearnsii de Wild). Silvicultura, São Paulo, v. 11, n. 41, p. 74, 1986. Resumo. Edição dos anais do 5º Congresso Florestal Brasileiro, 1986, Olinda. Usos múltiplos da floresta: uma necessidade.| Biblioteca(s): Embrapa Florestas. |
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| Registros recuperados : 2 | |
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