A genetic study of new udder health indicator traits with data from automatic milking systems

The current study aimed to investigate new udder health traits based on data from automatic milking systems (AMS) for use in routine genetic evaluations. Data were from 77 commercial herds; out of these, 24 had equipment for measuring online cell count (OCC), whereas all had data on electrical conductivity (EC). A total of 4,714 Norwegian Red dairy cows and 2,363,928 milkings were included in the genetic analyses. Electrical conductivity was available on quarter level for each milking, whereas OCC was measured per milking. The AMS traits analyzed were log-transformed online cell count (lnOCC), maximum conductivity (ECmax), mean conductivity (ECmean), elevated mastitis risk (EMR), and log-transformed EMR (lnEMR). In addition, lactation mean somatic cell score (LSCS) was collected from the Norwegian dairy herd recording system. Elevated mastitis risk expresses the probability of a cow having mastitis and was calculated from smoothed lnOCC values according to individual trend and level of the OCC curve. The udder health traits from AMS were analyzed as repeated milkings from 30 to 320 DIM, and LSCS as repeated parities. In addition, both ECmax and lnOCC were analyzed as multiple traits by splitting the lactation into 5 periods. (Co)variance components were estimated from bivariate mixed linear animal models, and investigated traits showed genetic variation. Estimated heritabilities of ECmean, ECmax, and lnEMR were 0.35, 0.23, and 0.12, respectively, whereas EMR and lnOCC both showed heritabilities of 0.09. Heritability varied between periods of lactation, from 0.04 to 0.13 for lnOCC and from 0.12 to 0.27 for ECmax, although standard errors of certain periods were large. Genetic correlations among the AMS traits ranged from 0 to 0.99. The genetic correlations between EC-based traits and OCC-based traits in AMS were 0. Genetic correlations with LSCS were favorable, ranging from 0.37 to 0.80 (±0.11-0.22). The strongest correlation (0.80 ± 0.13) was found between LSCS and lnEMR. Results question the value of ECmax and ECmean as indicators of udder health in genetic evaluations and suggest OCC to be more valuable in this manner. This study demonstrates a potential of using AMS data as additional information on udder health for genetic evaluations, although further investigation is recommended before these traits can be implemented.