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Registro Completo |
Biblioteca(s): |
Embrapa Pantanal. |
Data corrente: |
22/01/2015 |
Data da última atualização: |
24/03/2016 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
BAILEY, J. C.; TEDESCHI, L. O.; MENDES, E. D. M.; SAWYER, J. E.; CARSTENS, G. E. |
Afiliação: |
J. C. BAILEY, Department of Animal Science, Texas A&M University, College Station; L.O.TEDESCHI, Department of Animal Science, Texas A&M University, College Station; EGLEU DIOMEDES MARINHO MENDES, CPAP; J. E. SAWYER, Department of Animal Science, Texas A&M University, College Station; G. E. CARSTENS, Department of Animal Science, Texas A&M University, College Station. |
Título: |
Technical note: evaluation of bimodal distribution models to determine meal criterion in heifers fed a high-grain diet. |
Ano de publicação: |
2012 |
Fonte/Imprenta: |
Journal of Animal Science, v. 90, n. 8, p. 2750-2753, aug. 2012. |
DOI: |
10.2527/jas2011-4634 |
Idioma: |
Inglês |
Conteúdo: |
Meals are clusters of feedbunk visit (BV) events that are differentiated from the next meal by a nonfeeding interval that is longer compared with the nonfeeding intervals within a meal. The longest nonfeeding interval considered to be part of a meal is defi ned as the meal criterion. The objective of this study was to determine which combination of 2 probability density functions [(PDF): Gaussian normal (G), Weibull (W), Log-Normal, Gamma, and Gumbel] used in a bimodal distribution model had the best fit of nonfeeding interval data collected in beef heifers. Feeding behavior traits (572,627 total BV events) were measured in 119 heifers fed a high-grain diet (3.08 Mcal ME/kg DM), using a GrowSafe system for 66 d. The frequency and duration of BV events averaged 75 ± 15 events/d and 73.0 ± 22.3 min/d, respectively. The bimodal PDF combinations were fi tted to the log10-transformed interval lengths between BV events for each animal, using R mixdist package (2.13). The Akaike Information Criterion (AIC) was used to assess goodness of fi t of the 25 bimodal PDF combinations. The PDF model with the least AIC value was selected as the best fi t for each individual. A x2 analysis of the selected best PDF distribution across individuals revealed that 78.2% of the heifers best fi t were G-W or W-W PDF models. The likelihood probability estimates were calculated from the average AIC deviation of each model from the standard G-G model. The G-W likelihood probability estimate was greater (P = 0.001) than the W-W combination (0.997 vs. 0.727). Our analysis indicated the G-W model had a statistically better fi t and is most likely the best approach to defi ne meal criterion in beef heifers fed high-grain diets. MenosMeals are clusters of feedbunk visit (BV) events that are differentiated from the next meal by a nonfeeding interval that is longer compared with the nonfeeding intervals within a meal. The longest nonfeeding interval considered to be part of a meal is defi ned as the meal criterion. The objective of this study was to determine which combination of 2 probability density functions [(PDF): Gaussian normal (G), Weibull (W), Log-Normal, Gamma, and Gumbel] used in a bimodal distribution model had the best fit of nonfeeding interval data collected in beef heifers. Feeding behavior traits (572,627 total BV events) were measured in 119 heifers fed a high-grain diet (3.08 Mcal ME/kg DM), using a GrowSafe system for 66 d. The frequency and duration of BV events averaged 75 ± 15 events/d and 73.0 ± 22.3 min/d, respectively. The bimodal PDF combinations were fi tted to the log10-transformed interval lengths between BV events for each animal, using R mixdist package (2.13). The Akaike Information Criterion (AIC) was used to assess goodness of fi t of the 25 bimodal PDF combinations. The PDF model with the least AIC value was selected as the best fi t for each individual. A x2 analysis of the selected best PDF distribution across individuals revealed that 78.2% of the heifers best fi t were G-W or W-W PDF models. The likelihood probability estimates were calculated from the average AIC deviation of each model from the standard G-G model. The G-W likelihood probability estimate was greater... Mostrar Tudo |
Palavras-Chave: |
Meal criterion. |
Thesagro: |
Bovino; Gado; Nutrição animal. |
Thesaurus Nal: |
beef cattle; feeding behavior. |
Categoria do assunto: |
-- |
Marc: |
LEADER 02473naa a2200253 a 4500 001 2006379 005 2016-03-24 008 2012 bl uuuu u00u1 u #d 024 7 $a10.2527/jas2011-4634$2DOI 100 1 $aBAILEY, J. C. 245 $aTechnical note$bevaluation of bimodal distribution models to determine meal criterion in heifers fed a high-grain diet. 260 $c2012 520 $aMeals are clusters of feedbunk visit (BV) events that are differentiated from the next meal by a nonfeeding interval that is longer compared with the nonfeeding intervals within a meal. The longest nonfeeding interval considered to be part of a meal is defi ned as the meal criterion. The objective of this study was to determine which combination of 2 probability density functions [(PDF): Gaussian normal (G), Weibull (W), Log-Normal, Gamma, and Gumbel] used in a bimodal distribution model had the best fit of nonfeeding interval data collected in beef heifers. Feeding behavior traits (572,627 total BV events) were measured in 119 heifers fed a high-grain diet (3.08 Mcal ME/kg DM), using a GrowSafe system for 66 d. The frequency and duration of BV events averaged 75 ± 15 events/d and 73.0 ± 22.3 min/d, respectively. The bimodal PDF combinations were fi tted to the log10-transformed interval lengths between BV events for each animal, using R mixdist package (2.13). The Akaike Information Criterion (AIC) was used to assess goodness of fi t of the 25 bimodal PDF combinations. The PDF model with the least AIC value was selected as the best fi t for each individual. A x2 analysis of the selected best PDF distribution across individuals revealed that 78.2% of the heifers best fi t were G-W or W-W PDF models. The likelihood probability estimates were calculated from the average AIC deviation of each model from the standard G-G model. The G-W likelihood probability estimate was greater (P = 0.001) than the W-W combination (0.997 vs. 0.727). Our analysis indicated the G-W model had a statistically better fi t and is most likely the best approach to defi ne meal criterion in beef heifers fed high-grain diets. 650 $abeef cattle 650 $afeeding behavior 650 $aBovino 650 $aGado 650 $aNutrição animal 653 $aMeal criterion 700 1 $aTEDESCHI, L. O. 700 1 $aMENDES, E. D. M. 700 1 $aSAWYER, J. E. 700 1 $aCARSTENS, G. E. 773 $tJournal of Animal Science$gv. 90, n. 8, p. 2750-2753, aug. 2012.
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Embrapa Pantanal (CPAP) |
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Registro Completo
Biblioteca(s): |
Embrapa Amapá; Embrapa Amazônia Oriental; Embrapa Rondônia. |
Data corrente: |
17/04/2008 |
Data da última atualização: |
14/11/2018 |
Tipo da produção científica: |
Folder/Folheto/Cartilha |
Autoria: |
FREIRE FILHO, F. R.; CRAVO, M. da S.; VILARINHO, A. A.; CAVALCANTE, E. da S.; FERNANDES, J. B.; SAGRILO, E.; RIBEIRO, V. Q.; ROCHA, M. de M.; SITTOLIN, I. M.; SOUZA, F. de F.; LOPES, A. de M.; ROCHA NETO, O. G. da; CELESTINO FILHO, P.; GONCALVES, J. R. P.; CARVALHO, H. W. L. de; RAPOSO, J. A. A.; SAMPAIO, L. S. |
Afiliação: |
FRANCISCO RODRIGUES FREIRE FILHO, CPAMN; MANOEL DA SILVA CRAVO, CPATU; ALUÍSIO ALCÂNTARA VILARINHO, CPAF-RR; EMANUEL DA SILVA CAVALCANTE, CPAF-Amapá; JOÃO BATISTA FERNANDES, EMPARN; EDVALDO SAGRILO, CPAO; VALDENIR QUEIROZ RIBEIRO, CPAMN; MAURISRAEL DE MOURA ROCHA, CPAMN; ILZA MARIA SITTOLIN, CPAMN; FLAVIO DE FRANCA SOUZA, CPAF-RO; ALTEVIR DE MATOS LOPES, CPATU; OLINTO GOMES DA ROCHA NETO, CPATU; PEDRO CELESTINO FILHO, CPATU; JOSE RICARDO PUPO GONCALVES, CPAA; HELIO WILSON LEMOS DE CARVALHO, CPATC; JOÃO ANTÔNIO ARRUDA RAPOSO, IPA; LEILA SOBRAL SAMPAIO, UFRA. |
Título: |
BRS NOVAERA: cultivar de feijão-caupi de porte semi-ereto. |
Ano de publicação: |
2007 |
Fonte/Imprenta: |
Belém, PA: Embrapa Amazônia Oriental; Teresina: Embrapa Meio-Norte, 2007. |
Descrição Física: |
Não paginado, il. |
Idioma: |
Português |
Notas: |
1 folder. Equipe Técnica: Francisco Rodrigues Freire Filho, Manoel da Silva Cravo, Aluísio Alcântara Vilarinho, Emanuel da Silva Cavalcante, João Batista Fernandes, Edvaldo Sagrilo, Valdenir Queiroz Ribeiro, Maurisrael de Moura Rocha, Ilza Maria Sittolin, Flávio de França Souza, Altevir de Matos Lopes, Olinto Gomes da Rocha Neto, Pedro Celestino Filho, José Ricardo P. Gonçalves, Hélio Wilson Lemos de Carvalho, João Antônio Arruda Raposo e Leila Sobral Sampaio. |
Thesagro: |
Agricultura; Agricultura Familiar; Características Agronômicas; Feijão de Corda; Mercado; Rendimento; Tecnologia; Variedade; Vigna Unguiculata. |
Categoria do assunto: |
-- F Plantas e Produtos de Origem Vegetal |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/91229/1/FD170.pdf
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Marc: |
LEADER 01690nam a2200421 a 4500 001 1402169 005 2018-11-14 008 2007 bl uuuu u0uu1 u #d 100 1 $aFREIRE FILHO, F. R. 245 $aBRS NOVAERA$bcultivar de feijão-caupi de porte semi-ereto.$h[electronic resource] 260 $aBelém, PA: Embrapa Amazônia Oriental; Teresina: Embrapa Meio-Norte$c2007 300 $cNão paginado, il. 500 $a1 folder. Equipe Técnica: Francisco Rodrigues Freire Filho, Manoel da Silva Cravo, Aluísio Alcântara Vilarinho, Emanuel da Silva Cavalcante, João Batista Fernandes, Edvaldo Sagrilo, Valdenir Queiroz Ribeiro, Maurisrael de Moura Rocha, Ilza Maria Sittolin, Flávio de França Souza, Altevir de Matos Lopes, Olinto Gomes da Rocha Neto, Pedro Celestino Filho, José Ricardo P. Gonçalves, Hélio Wilson Lemos de Carvalho, João Antônio Arruda Raposo e Leila Sobral Sampaio. 650 $aAgricultura 650 $aAgricultura Familiar 650 $aCaracterísticas Agronômicas 650 $aFeijão de Corda 650 $aMercado 650 $aRendimento 650 $aTecnologia 650 $aVariedade 650 $aVigna Unguiculata 700 1 $aCRAVO, M. da S. 700 1 $aVILARINHO, A. A. 700 1 $aCAVALCANTE, E. da S. 700 1 $aFERNANDES, J. B. 700 1 $aSAGRILO, E. 700 1 $aRIBEIRO, V. Q. 700 1 $aROCHA, M. de M. 700 1 $aSITTOLIN, I. M. 700 1 $aSOUZA, F. de F. 700 1 $aLOPES, A. de M. 700 1 $aROCHA NETO, O. G. da 700 1 $aCELESTINO FILHO, P. 700 1 $aGONCALVES, J. R. P. 700 1 $aCARVALHO, H. W. L. de 700 1 $aRAPOSO, J. A. A. 700 1 $aSAMPAIO, L. S.
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