Time filter

Source Type

Urioste J.I.,Swedish University of Agricultural Sciences | Franzen J.,Swedish University of Agricultural Sciences | Windig J.J.,Animal Breeding and Genomics Center Livestock Research | Strandberg E.,Swedish University of Agricultural Sciences
Journal of Dairy Science | Year: 2012

The objectives of this study were to estimate heritabilities of, and genetic correlations among, clinical mastitis (CM), subclinical mastitis (SCM), and alternative somatic cell count (SCC) traits in the first 3 lactations of Swedish Holstein cows, and to estimate genetic correlations for the alternative traits across lactations. Data from cows having their first calving between 2002 and 2009 were used. The alternative SCC traits were based on information on CM and monthly test-day (TD) records of SCC traits of 178,613, 116,079, and 64,474 lactations in first, second, or third parity, respectively. Sires had an average of 230, 165, or 124 daughters in the data (parities 1, 2, or 3, respectively). Subclinical mastitis was defined as the number of periods with an SCC >150,000 cell/mL and without a treatment for CM. Average TD SCC between 5 and 150 d was used as a reference trait. The alternative SCC traits analyzed were 1) presence of at least 1 TD SCC between 41,000 and 80,000 cell/mL (TD41-80), 2) at least 1 TD SCC >500,000 cells/mL, 3) standard deviation of log SCC over the lactation, 4) number of infection peaks, and 5) average days diseased per peak. The same variables in different parities were treated as distinct traits. The statistical model considered the effects of herd-year, year, month, age at calving, animal, and residual. Heritability estimates were 0.07 to 0.08 for CM, 0.12 to 0.17 for SCM, and 0.14 for SCC150. For the alternative traits, heritability estimates were 0.12 to 0.17 for standard deviation of log SCC, TD SCC >500,000 cells/mL, and average days diseased per peak, and 0.06 to 0.10 for TD41-80 and number of infection peaks. Genetic correlations between CM with SCM were 0.62 to 0.74, and correlations for these traits with the alternative SCC traits were positive and very high (0.67 to 0.82 for CM, and 0.94 to 0.99 for SCM). Trait TD41-80 was the only alternative trait that showed negative, favorable, genetic correlations with CM (-0.22 to -0.50) and SCM (-0.48 to -0.85) because it is associated with healthy cows. Genetic correlations among the alternative traits in all 3 parities were high (0.93 to 0.99, 0.92 to 0.98, and 0.78 to 0.99, respectively). The only exception was TD41-80, which showed moderate to strong negative correlations with the rest of the traits. Genetic correlations of the same trait across parities were in general positive and very high (0.83 to 0.99). In conclusion, these alternative SCC traits could be used in practical breeding programs aiming to improve udder health in dairy cattle. © 2012 American Dairy Science Association.

Windig J.J.,Animal Breeding and Genomics Center Livestock Research | Ouweltjes W.,Animal Breeding and Genomics Center Livestock Research | ten Napel J.,Animal Breeding and Genomics Center Livestock Research | de Jong G.,Animal Evaluation Unit | And 3 more authors.
Journal of Dairy Science | Year: 2010

Test-day records of somatic cell counts (SCC) can be used to define alternative traits to decrease genetic susceptibility to clinical mastitis (CM) and subclinical mastitis (SCM). This paper examines which combination of alternative SCC traits can be used best to reduce both CM and SCM and whether direct information on CM is useful in this respect. Genetic correlations between 10 SCC traits and CM and SCM were estimated from 3 independent data sets. The SCC traits with the strongest correlations with CM differed from those with the strongest correlations with SCM. Selection index calculations were made for a breeding goal of 50% CM and 50% SCM resistance using these correlations. They indicated that a combination of 5 SCC traits (SCC early and late in lactation, suspicion of infection based on increased SCC, extent of increased SCC, and presence of a peak pattern in SCC) gave a high accuracy, almost without loss, compared with the full set of 10 SCC traits. The estimated accuracy of this index was 0.91, assuming that the correlations had been estimated without error. To take errors in estimation into account, correlations were resampled from a normal distribution with mean and standard errors as originally estimated. The accuracy of the index calculated with the original correlations was then recalculated using the resampled correlations. The average accuracy based on 50,000 resamplings decreased to 0.81. Use of direct information on CM improved the accuracy (uncorrected for errors in correlations) only slightly, to 0.92. © 2010 American Dairy Science Association.

Discover hidden collaborations