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Details for article 5 of 6 found articles
| Title: |
Genetic parameters and single versus multi-trait evaluation of udder health traits |
| Author: |
Negussie, Enyew Koivula, Minna Mantysaari, Esa A. |
| Appeared in: |
Acta agriculturae Scandinavica. Section A, Animal science |
| Paging: | Volume 56 (2006) nr. 2 pages 73-82 |
| Year: |
2006-06-01 |
| Contents: |
Genetic parameters were estimated for lactation average somatic cell score (SCS) and clinical mastitis (CM) for the first three lactations of multiparous Finnish Ayrshire cows. A multi-trait linear sire model was used for estimation of covariance components, and the efficiencies of single- versus multi-trait multi-lactation (MT) sire evaluations were compared. Heritability of SCS and CM in the first three lactations ranged from 0.11 to 0.13 and 0.02 to 0.03, respectively. Within lactation, genetic correlations between SCS and CM ranged from 0.68 to 0.72. Within both traits, across-lactation genetic correlations were lowest between 1 and 3, and highest between 2 and 3, with estimates ranging from 0.75 to 0.86 and from 0.81 to 0.98 for CM and SCS, respectively. Residual and phenotypic correlations were low and ranged from 0.09 to 0.13 and from 0.10 to 0.13, respectively. The absolute difference between genetic and residual correlations was from 0.5 to 0.6. Within-lactation genetic correlations between traits that are much less than unity suggest a multi-trait model for genetic evaluation of mastitis resistance. Comparison of model prediction performance between single-trait (ST) and MT models using a data splitting method showed that the MT model was more stable in predicting breeding values in future records of animals. Especially, for young sires and CM, the SD of EBVs from the MT model was 14 to 23% higher than the ST model, indicating more effective use of information in terms of revealing more genetic variation. |
| Publisher: |
Taylor & Francis |
| Source file: |
Elektronische Wetenschappelijke Tijdschriften |
Details for article 5 of 6 found articles
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