Aspectos genéticos da curva de lactação em ovinos da raça Lacaune
Genetic analysis is a tool that can help in the search for better zootechnical indexes in dairy sheep breeding. For many years the lactation curves and the estimation of variance components of the parameters calculated from them have been used in management strategies in dairy farms since it is poss...
| Autor principal: | Negri, Renata |
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| Formato: | Dissertação |
| Idioma: | Português |
| Publicado em: |
Universidade Tecnológica Federal do Paraná
2017
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| Assuntos: | |
| Acesso em linha: |
http://repositorio.utfpr.edu.br/jspui/handle/1/2476 |
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| Resumo: |
Genetic analysis is a tool that can help in the search for better zootechnical indexes in dairy sheep breeding. For many years the lactation curves and the estimation of variance components of the parameters calculated from them have been used in management strategies in dairy farms since it is possible to change the shape of the lactation curve through selection. In Brazil, there is a large gap regarding technical knowledge related to dairy sheep in the country. The estimation of lactation curve parameters and subsequent estimation of the components of variance allow a better understanding of the genetic and environmental components that affect production, anticipating the information necessary for decision making on the direction of the genetic management of the herds. The aim of this work was to estimate the components of variance and the genetic parameters of the components of the Wood curve in a herd of Lacaune sheep. We used 3558 information from Lacaune sheep, and estimated the variance components and genetic parameters of the parameters for initial production (a), increase to peak (b), decrease after peak (c), peak day (d), peak production (p), persistence (ln (s)), and total production (y) of the Wood curve via Bayesian estimation using the Gibbs sampling method. The estimated mean for parameters a, b, c, d, p, ln (s) and y were 0.362, 0.135, 0.032, 3.911, 1.703, 4.049, 76.249, respectively. The estimated mean heritabilities were 0.41 (a), 0.47 (b), 0.50 (c), 0.11 (d), 0.30 (p), 0.36 (ln (s)) and 0.002 (y). The phenotypic and genetic correlations between parameter a and the others ranged from -0.13 to 0.39 and -0.06 to 0.24, respectively. In parameter b ranged from -0.002 to 0.17 and 0.04 to 0.15, parameter c of -0.01 to 0.11 and 0.04 to 0.10, parameter d of -0.13 to 0.39 and - 0.02 to 0.11, parameter p of -0.15 to 0.39 and -0.12 to 0.24, parameter ln (s) of -0.15 to 0.39 and -0.12 to 0.11, and for the parameter y ranged from -0.002 to 0.33 and 0.04 to 0.08. The repeatability identified were 0.81 (a), 0.94 (b), 0.98 (c), 0.22 (d), 0.60 (p), 0.71 (ln (s)) and 0.003 (y). It was concluded that the average estimates of heritability and correlations showed a strong environmental effect affecting the expression of the characteristic milk production and low genetic correlations between the parameters of the curve and the production, indicating that the selection by milk production will bring little genetic gain. On the other hand, the selection considering all parameters of the curve may be more convenient. In addition, the need for standardization of herd management is evidenced. More detailed studies should be developed to understand the relationship of the parameters. The database can be worked on in other lactation periods for a better understanding of the variance component estimates. It would be of great value studies on main components and track analysis for later use in the selection index method, to corroborate with the selection that considers all parameters of the curve. |
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