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 | Acesso ao texto completo restrito à biblioteca da Embrapa Pantanal. Para informações adicionais entre em contato com cpap.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Pantanal. |
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Data corrente: |
22/01/2015 |
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Data da última atualização: |
24/03/2016 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
BAILEY, J. C.; TEDESCHI, L. O.; MENDES, E. D. M.; SAWYER, J. E.; CARSTENS, G. E. |
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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. |
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Título: |
Technical note: evaluation of bimodal distribution models to determine meal criterion in heifers fed a high-grain diet. |
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Ano de publicação: |
2012 |
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Fonte/Imprenta: |
Journal of Animal Science, v. 90, n. 8, p. 2750-2753, aug. 2012. |
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DOI: |
10.2527/jas2011-4634 |
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Idioma: |
Inglês |
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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 |
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Palavras-Chave: |
Meal criterion. |
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Thesagro: |
Bovino; Gado; Nutrição animal. |
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Thesaurus Nal: |
beef cattle; feeding behavior. |
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Categoria do assunto: |
-- |
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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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| 1. |  | PECH, J. C.; PURGATTO, E.; GIRARDI, C. L.; ROMBALDI, C. V.; LATCHÉ, A. Current challenges in postharvest biology of fruit ripening. Current Agricultural Science and Technology, Pelotas, v. 19, n. 1, p. 1-18, 2013.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: C - 0 |
| Biblioteca(s): Embrapa Uva e Vinho. |
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| 3. |  | GIRARDI, C. L.; BERMUDEZ, K; BERNADAC, A.; CHAVEZ, A.; ZOUINE, M.; MIRANDA, F. J.; BOUZAYEN, M.; PECH, J.-C.; LATCH, A. The mitochondrial elongation factor LeEF-Tsmt is regulated during tomato fruit ripening and upon wounding and ethylene treatment. Postharvest Biology and Technology, Amsterdam, v. 42, n. 1, p. 1-7, 2006.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: Internacional - A |
| Biblioteca(s): Embrapa Uva e Vinho. |
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| 4. |  | GIRARDI, C. L.; BERMUDEZ, K.; BERNADAC, A.; CHAVEZ, A.; ZOUINE, M.; MIRANDA, F. J.; BOUZAYEN, M.; PECH, J.-C.; LATCHÉ, A. The mitochondrial elongation factor LeEF-TSmt is regulated during tomato fruit ripening and upon wounding and ethylene treatment. In: GIRARDI, C. L. Biotechnologie de la maturation des fruits: caracterisation fonctionelle d'un facteur d'elongation mitochondrial leEF-Tsmt chez la tomate: approaches par transgenese et proteomique. Sarrebruck: Éditions Universitaires Européennes, 2010. p. 25-42.| Tipo: Capítulo em Livro Técnico-Científico |
| Biblioteca(s): Embrapa Uva e Vinho. |
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| Registros recuperados : 4 | |
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