The objective of this study was to investigate how useful data from automatic milking systems used in commercial herds are for genetic analysis of milkability traits. Data were available from 4,968 Swedish Holstein and Swedish Red cows over a span of 5 yr (2004-2009) from 19 herds. The analyzed milkability traits were average flow rate, box time, milking interval, and number of milkings per day. Variance components were estimated for genetic, permanent environmental, and residual effects in first and later (second and third) lactations, and were used for estimation of heritabilities and repeatablilites. The experiences of the data quality and editing procedures showed that almost half of the data and about a quarter of the cows had to be excluded from the analyses due to incomplete or inconsistent information. However, much more data are available than is needed for accurate genetic parameter estimations. For the genetic analysis, a repeatability animal model was used that included the fixed effects of herd, year and season, lactation month, and milk yield. The repeatability coefficients were at a high level: highest for average flow rate, with estimates between 0.8 and 0.9. The estimated heritability coefficients were in the range of 0.37 to 0.48, 0.21 to 0.44, 0.09 to 0.26, and 0.02 to 0.07 for average flow rate, box time, milking interval, and number of milkings, respectively. The results from the present study unraveled large genetic variation in milkability traits. The genetic parameter estimates were well in agreement with previous studies of milkability, which proves the feasibility of using data from automatic milking systems for genetic analysis.

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The overall objective of this study was to assess the use of in-line recorded milkability information from dairy herds with conventional milking parlors (CMP) and from herds with automatic milking systems (AMS) for genetic evaluation. Some genetic parameters were previously studied on AMS data for 2,053 Swedish Holstein (SH) and 1,749 Swedish Red (SR) cows in 19 herds. These data were combined in the present paper with milkability information from 74 herds with CMP, including 11,123 SH cows and 7,554 SR cows. Genetic parameters were estimated for the CMP data and genetic correlations were estimated between milkability traits measured in the 2 systems. Average flow rate and milking time were derived and used as similar milkability traits for both systems, whereas box time was used only for AMS herds. Estimated heritabilities were in the range from 0.24 to 0.49. Even though the traits were differently defined in the 2 milking systems, the corresponding traits recorded in AMS and CMP were genetically closely related (0.93-1.00). Similarly, close genetic relationships were shown between milkability traits in different lactations in both breeds (0.93-0.99). Thus, it should be possible to treat milkability traits in different lactations and from different milking systems as the same traits in genetic evaluations. The various milkability traits were also highly genetically correlated, indicating that the inclusion of just one trait in the genetic selection program would efficiently select for milkability without the need to consider all measures. Comparisons of repeatability and random regression models, combining all information from the 2 systems for genetic evaluation, were done to find the most suitable model for genetic evaluation purposes. Even though the random regression models were favored in the formal model tests to evaluate suitability, correlation coefficients between test-days within lactation were high (0.7-0.8) and small differences in breeding values resulted among different models. That would indicate that a few test-days per cow would produce accurate breeding values for milkability.

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