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| Registros recuperados : 7 | |
| 1. |  | OLIVEIRA, V. F. de; VENSKE, E.; STAFEN, C. F.; PANIZ, F. P.; PEDRON, T.; PEREIRA, R. M.; MAGALHAES JUNIOR, A. M. de; MAIA, L. C. da; OLIVEIRA, A. C. de; BATISTA, B. L.; PEGORARO, C. Genome-wide association of iron content in rice grains grown in Southern Brazil. Pesquisa Agropecuária Brasileira, Brasília, v. 58, e03203, 2023. Título em português: Associação genômica ampla para teor de ferro em grãos de arroz na região Sul do Brasil.| Biblioteca(s): Embrapa Clima Temperado; Embrapa Unidades Centrais. |
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| 2. | | OLIVEIRA, V. F. de; BUSANELLO, C.; VIANA, V. E.; STAFEN, C. F.; PEDROLO, A. M.; PANIZ, F. P.; PEDRON, T.; PEREIRA, R. M.; ROSA, S. A.; MAGALHAES JUNIOR, A. M. de; OLIVEIRA, A. C. de; BATISTA, B. L.; PEGORARO, C. Assessing mineral and toxic elements content in rice grains grown in southern Brazil. Journal of Food Composition and Analysis, v. 100, 103914, July 2021.| Biblioteca(s): Embrapa Clima Temperado. |
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| 3. | | BUSANELLO, C.; VENSKE, E.; STAFEN, C. F.; PEDROLO, A. M.; LUZ, V. K. da; PEDRON, T.; PANIZ, F. P.; BATISTA, B. L.; MAGALHAES JUNIOR, A. M. de; OLIVEIRA, A. C. DE; PEGORARO, C. Is the genetic variability of elite rice in southern Brazil really disappearing? Crop Breeding and Applied Biotechnology, v. 20, n. 2, e262620214, July 2020.| Biblioteca(s): Embrapa Clima Temperado. |
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| 4. | | STAFEN, C. F.; PEDROLO, A. M.; PANIZ, F. P.; PEDRON, T.; BUSANELLO, C.; VENSKE, E.; MAGALHAES JUNIOR, A. M. de; BATISTA, B. L.; OLIVEIRA, A. C.; PEGORARO, C. Iron biofortification in rice: in search of morphological traits for indirect selection in breeding programs. Científica, Jaboticabal, v.47, n.2, p.199-209, 2019.| Biblioteca(s): Embrapa Clima Temperado. |
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| 5. | | VENSKE, E.; STAFEN, C. F.; OLIVEIRA, V. F. de; MAIA, L. C. da; MAGALHAES JUNIOR, A. M. de; MCNALLY, K. L.; OLIVEIRA, A. C. de; PEGORARO, C. Genetic diversity, linkage disequilibrium, and population structure in a panel of Brazilian rice accessions. Journal of Applied Genetics, v. 60, p. 27?31, 2019.| Biblioteca(s): Embrapa Clima Temperado. |
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| 6. | | STAFEN, C.; PEDROLO, A. M.; SCHROEDER, L. D.; VIANA, V. E.; BUSANELLO, C.; ROSA, M. P. da; TOMM, G. O.; OLIVEIRA, A. C. de; PEGORARO, C. Seed germination and seedling growth of canola treated with abiotic factors that can affect growth and development. International Journal of Vegetable Science, mar. 2018. 9 p.| Biblioteca(s): Embrapa Trigo. |
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| 7. | | PEDROLO, A. M.; PELEGRIN, A. J. de; STAFEN, C. F.; CORTÉS, D. C. L.; SILVEIRA, T.; PEGORARO, C.; DA MAIA, L. C.; ANTONIO COSTA DE OLIVEIRA; TOMM, G. O.; FIALHO, G. S. Influência da temperatura na germinação de Brassica napus L. var. oleífera. In: ENCONTRO LATINO AMERICANO DE INICIAÇÃO CIENTÍFICA, 20.; ENCONTRO LATINO AMERICANO DE PÓS-GRADUAÇÃO, 16.; ENCONTRO LATINO AMERICANO DE INICIAÇÃO CIENTÍFICA JÚNIOR, 10.; ENCONTRO DE INICIAÇÃO À DOCÊNCIA, 6., 2016, São José dos Campos. Educação e ciência para a cidadania global: [anais]. São José dos Campos: Universidade do Vale do Paraíba, 2016. 7 p.| Biblioteca(s): Embrapa Trigo. |
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| Registros recuperados : 7 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Gado de Leite. |
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Data corrente: |
05/02/2013 |
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Data da última atualização: |
23/01/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 2 |
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Autoria: |
COBUCI, J. A.; COSTA, C. N. |
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Afiliação: |
JAIME ARAUJO COBUCI, UFRS; CLAUDIO NAPOLIS COSTA, CNPGL. |
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Título: |
Persistency of lactation using random regression models and different fixed regression modeling approaches. |
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Ano de publicação: |
2012 |
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Fonte/Imprenta: |
Revista Brasileira de Zootecnia, v. 41, n. 9, p. 1996-2004, 2012. |
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DOI: |
https://doi.org/10.1590/S1516-35982012000900005 |
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Idioma: |
Inglês |
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Conteúdo: |
Milk yield test-day records on the first three lactations of 25,500 Holstein cows were used to estimate genetic parameters and predict breeding values for nine measures of persistency and 305-d milk yield in a random regression animal model using two criteria to define the fixed regression. Legendre polynomials of fourth and fifth orders were used to model the fixed and random regressions of lactation curves. The fixed regressions were adjusted for average milk yield on populations (single) or subpopulations (multiple) formed by cows that calved at the same age and in the same season. Akaike Information (AIC) and Bayesian Information (BIC) criteria indicated that models with multiple regression lactation curves had the best fit to test-day milk records of first lactations, while models with a single regression curve had the best fit for the second and third lactations. Heritability and genetic correlation estimates between persistency and milk yield differed significantly depending on the lactation order and the measures of persistency used. These parameters did not differ significantly depending on the criteria used for defining the fixed regressions for lactation curves. In general, the heritability estimates were higher for first (0.07 to 0.43), followed by the second (0.08 to 0.21) and third (0.04 to 0.10) lactation. The rank of sires resulting from the processes of genetic evaluation for milk yield or persistency using random regression models differed according to the criteria used for determining the fixed regression of lactation curve. MenosMilk yield test-day records on the first three lactations of 25,500 Holstein cows were used to estimate genetic parameters and predict breeding values for nine measures of persistency and 305-d milk yield in a random regression animal model using two criteria to define the fixed regression. Legendre polynomials of fourth and fifth orders were used to model the fixed and random regressions of lactation curves. The fixed regressions were adjusted for average milk yield on populations (single) or subpopulations (multiple) formed by cows that calved at the same age and in the same season. Akaike Information (AIC) and Bayesian Information (BIC) criteria indicated that models with multiple regression lactation curves had the best fit to test-day milk records of first lactations, while models with a single regression curve had the best fit for the second and third lactations. Heritability and genetic correlation estimates between persistency and milk yield differed significantly depending on the lactation order and the measures of persistency used. These parameters did not differ significantly depending on the criteria used for defining the fixed regressions for lactation curves. In general, the heritability estimates were higher for first (0.07 to 0.43), followed by the second (0.08 to 0.21) and third (0.04 to 0.10) lactation. The rank of sires resulting from the processes of genetic evaluation for milk yield or persistency using random regression models differed according to the ... Mostrar Tudo |
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Palavras-Chave: |
Legendre polynomial; Teste de produção de leite; Valor de criação. |
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Thesagro: |
Seleção. |
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Categoria do assunto: |
L Ciência Animal e Produtos de Origem Animal |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/948345/1/Persistency-of-lactation-using-random-regression-models-and-different-fixed-regression-modeling-approaches.pdf
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Marc: |
LEADER 02228naa a2200193 a 4500
001 1948345
005 2023-01-23
008 2012 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1590/S1516-35982012000900005$2DOI
100 1 $aCOBUCI, J. A.
245 $aPersistency of lactation using random regression models and different fixed regression modeling approaches.$h[electronic resource]
260 $c2012
520 $aMilk yield test-day records on the first three lactations of 25,500 Holstein cows were used to estimate genetic parameters and predict breeding values for nine measures of persistency and 305-d milk yield in a random regression animal model using two criteria to define the fixed regression. Legendre polynomials of fourth and fifth orders were used to model the fixed and random regressions of lactation curves. The fixed regressions were adjusted for average milk yield on populations (single) or subpopulations (multiple) formed by cows that calved at the same age and in the same season. Akaike Information (AIC) and Bayesian Information (BIC) criteria indicated that models with multiple regression lactation curves had the best fit to test-day milk records of first lactations, while models with a single regression curve had the best fit for the second and third lactations. Heritability and genetic correlation estimates between persistency and milk yield differed significantly depending on the lactation order and the measures of persistency used. These parameters did not differ significantly depending on the criteria used for defining the fixed regressions for lactation curves. In general, the heritability estimates were higher for first (0.07 to 0.43), followed by the second (0.08 to 0.21) and third (0.04 to 0.10) lactation. The rank of sires resulting from the processes of genetic evaluation for milk yield or persistency using random regression models differed according to the criteria used for determining the fixed regression of lactation curve.
650 $aSeleção
653 $aLegendre polynomial
653 $aTeste de produção de leite
653 $aValor de criação
700 1 $aCOSTA, C. N.
773 $tRevista Brasileira de Zootecnia$gv. 41, n. 9, p. 1996-2004, 2012.
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Registro original: |
Embrapa Gado de Leite (CNPGL) |
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