Alternative use of somatic cells count in genetic selection for clinical mastitis

Three sets of somatic cell count (SCC) traits were defined in this study: (1) lactation-averages of SCC, (2) traits derived from the proportion of test-day SCC above 150,000 cells/ml, (3) patterns of peaks in SCC. Genetic parameters were estimated for these SCC-traits, as well as their genetic correlation with mastitistraits. Mastitis-traits were clinical and subclinical mastitis (CM and SCM, respectively) and were both scored as binary traits. Data was available from farms with a PC Management Information System, and the dataset contained 56,726 lactations of 30,145 cows on 272 herds. Variance components for sire and permanent animal effects were estimated using ASREML. The estimated heritabilities for CM and SCM were both low at 3%. Heritabilities for SCC-traits ranged from 1 to 13%; lowest for the patterns of peaks in SCC, and highest for lactation-average SCC. A range of genetic correlations was estimated between SCCtraits and CM or SCM, varying from 0.55 to 0.93 for CM, and from 0.68 to 0.98 for SCM. Strongest genetic correlation was estimated between CM and the pattern of peak that describes a quick recovery in SCC (0.93), and between SCM and SCC averaged between 151 and 400 days (0.95). Therefore, to improve the overall udder health, information from a combination of SCC-traits is expected to be most successful. Introduction Current selection indices realize an increase in milk yield and simultaneously monitor udder health by selecting for lower lactation-average somatic cell count (SCC). However, the estimated moderate genetic correlation of ≈ 0.7 between lactation-average SCC and udder health indicates that, genetically, they are not identical traits (Mrode and Swanson, 1996). Therefore, it could be worthwhile to establish if other SCCtraits provide additional information for selection that aims to decrease genetic susceptibility to clinical and subclinical mastitis (CM and SCM, respectively), in comparison to the information provided by one lactation-average SCC. The objective of this study was, therefore, to develop alternative measures from SCC, and to estimate their genetic relationship with CM and SCM. These alternative measures take into account the length of the observed lactationperiod, patterns of peaks in SCC, and indicators of excessive SCC. Materials and Methods To analyze alternative SCC-traits as mastitisindicators for genetic selection, three sets of SCC-traits were defined. The first set of SCCtraits consisted of SCC averaged over different lengths of observation. The second set of SCCtraits was derived from the proportion of excessive test-day SCC-recordings. The third set of SCC-traits corresponded to patterns of peaks in SCC (De Haas et al., 2004). Trait definitions Somatic cell counts were averaged over shorter lactation-lengths, because it is known that most first cases of CM occur in the first weeks of lactation. To be able to find an optimum, SCC were averaged per lactation over the test-day records up to 400, 300 and 150 days in milk (DIM). This average SCC was transformed to SCS=1000+100*(2log(SCC/1,000,000) resulting in SCS400, SCS300 and SCS150, respectively. To be able to compare the first versus second part of the lactation, SCC was averaged over day 151 to 400 and this average was log-transformed (SCS151-400). Excessive test-day SCC indicated the suspicion of a SCC to originate from an intramammary infection (IMI). Each test-day SCC was classed individually as a binary trait; when the test-day SCC was above 150,000 cells/ml it was registered as 1, otherwise it was scored as 0. Based on these classifications, two SCC-traits were defined to describe the dynamics of SCC during lactation. The hypothesis is that these