Phenotypic correlations of productive and reproductive traits of Simmental cows

Pantelic, V.; Skalicki, Z.; Petrović, M.M.; Aleksić, S.; Miscevic, B.; Ostojić-Andrić, D.

doi:10.2298/bah0704011p

Cited by 2 publications

(9 citation statements)

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“…Other genetic correlations were lower (less than 0.1) and with a higher standard error, which coincides with the majority of the results presented in literature (24,25). However, it is important to mention that genetic correlations are estimated parameters for a specific population under particular environmental and genetic conditions, and can therefore present variations between populations (18).…”

Section: Discussionsupporting

confidence: 87%

“…Las demás correlaciones genéticas fueron muy bajas (menores de 0.1) y con alto error estándar, lo que coincide con la mayoría de resultados presentes en la literatura (24,25). Sin embargo, es importante mencionar que las correlaciones genéticas son parámetros estimados de una población específica bajo condiciones ambientales y genéticas particulares, y por tanto puede presentar variaciones entre poblaciones (18).…”

Section: Discussionunclassified

“…Adicionalmente, algunos estudios han encontrado correlaciones similares a las reportadas en este trabajo, fortaleciendo la idea que se pueden obtener animales altamente productivos y resistentes a mastitis por medio de mejoramiento genético (19,25).…”

Section: Discussionunclassified

“…Finalmente, las correlaciones fenotípicas estimadas entre las diferentes características evaluadas por lo general fueron débiles, lo cual coincide con algunos reportes de la literatura (22,25). Sin embargo, los valores de éstas correlaciones son muy variables de acuerdo al ambiente donde son estimadas, por lo que es común obtener valores más altos en condiciones de producción altamente controladas (17).…”

Section: Discussionunclassified

“…Los mayores valores fueron obtenidos para la asociación entre el porcentaje de grasa (PG) y el porcentaje de proteína (PP) (0.48 y 0.25) para Holstein y Jersey, respectivamente, lo cual refleja la importancia ambiental sobre la expresión fenotípica de una característica, debido a que la correlación genética siendo alta, es diluida por el ambiente. Los resultados obtenidos en esta investigación concuerdan con los reportes encontrados por otros autores en ganado lechero (19,25). Es importante resaltar que las correlaciones fenotípicas por lo general son bajas, debido a la influencia de múltiples factores ambientales y en la mayoría de los casos las correlaciones genéticas son superiores a las correlaciones fenotípicas.…”

Section: Discussionunclassified

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Estimation of genetic and phenotypic parameters for production traits in Holstein and Jersey from Colombia

Echeverri

2015

Rev MVZ Córdoba

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Objective. Determine the genetic and phenotypic parameters for milk yield, fat percentage, protein percentage and somatic cell score. Materials and methods. 18134 lactation records were used to Holstein and 1377 lactations for Jersey in different herds. The (co) variance components and genetic parameters were estimated using the software Multiple Trait Derivative-Free Restricted Maximum Likelihood MTDFREML. Results. The Holstein and Jersey heritability’s (and standard error) for milk yield were: 0.16 (0.082) and 0.15 (0.306), 0.30 (0.079) and 0.37 (0.319) for protein percentage, 0.32 (0.076) and 0.46 (0.313) for fat percentage and for somatic cell score were: 0.01 (0.054) and 0.01 (0.233), respectively. The largest genetic correlations were found between the percentage of fat and percentage of protein, with values of 0.82 (0.126) and 0.98 (0.852) for Holstein and Jersey respectively. The lowest correlations were between fat percentage and somatic cell score with -0.01 (1.147) and -0.01 (1. 734). Phenotypic correlations were generally found low and repeatability showed a significant effect of permanent environment on milk production per lactation. Conclusions. It is important to emphasize the development of research to help guide breeding programs in the tropics, using selection indices of multi-traits.

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Section: Discussionsupporting

confidence: 87%

Section: Discussionunclassified

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Estimation of genetic and phenotypic parameters for production traits in Holstein and Jersey from Colombia

Echeverri

2015

Rev MVZ Córdoba

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Deriving estimates of individual variability in genetic potentials of performance traits for 3 dairy breeds, using a model of lifetime nutrient partitioning

Phuong¹,

Martin²,

Boer³

et al. 2015

Journal of Dairy Science

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This study explored the ability of an existing lifetime nutrient partitioning model for simulating individual variability in genetic potentials of dairy cows. Generally, the model assumes a universal trajectory of dynamic partitioning of priority between life functions and genetic scaling parameters are then incorporated to simulate individual difference in performance. Data of 102 cows including 180 lactations of 3 breeds: Danish Red, Danish Holstein, and Jersey, which were completely independent from those used previously for model development, were used. Individual cow performance records through sequential lactations were used to derive genetic scaling parameters for each animal by calibrating the model to achieve best fit, cow by cow. The model was able to fit individual curves of body weight, and milk fat, milk protein, and milk lactose concentrations with a high degree of accuracy. Daily milk yield and dry matter intake were satisfactorily predicted in early and mid lactation, but underpredictions were found in late lactation. Breeds and parities did not significantly affect the prediction accuracy. The means of genetic scaling parameters between Danish Red and Danish Holstein were similar but significantly different from those of Jersey. The extent of correlations between the genetic scaling parameters was consistent with that reported in the literature. In conclusion, this model is of value as a tool to derive estimates of genetic potentials of milk yield, milk composition, body reserve usage, and growth for different genotypes of cow. Moreover, it can be used to separate genetic variability in performance between individual cows from environmental noise. The model enables simulation of the effects of a genetic selection strategy on lifetime efficiency of individual cows, which has a main advantage of including the rearing costs, and thus, can be used to explore the impact of future selection on animal performance and efficiency.

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Phenotypic correlations of productive and reproductive traits of Simmental cows

Cited by 2 publications

References 0 publications

Estimation of genetic and phenotypic parameters for production traits in Holstein and Jersey from Colombia

Estimation of genetic and phenotypic parameters for production traits in Holstein and Jersey from Colombia

Deriving estimates of individual variability in genetic potentials of performance traits for 3 dairy breeds, using a model of lifetime nutrient partitioning

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