Genetic analyses of novel temperament and milkability traits in Norwegian Red cattle based on data from automatic milking systems

Abstract

The number of dairy cows milked in automatic milking systems (AMS) is steadily increasing in Norway. Capacity and efficiency of AMS are highly dependent on the individual cow's milking efficiency, such as milking speed and occupation time in the milking robot. Cows meet new challenges in herds utilizing AMS. Consequently, new or revised traits may be needed for genetic evaluation of dairy cattle. The AMS records relevant information on an individual cow basis. The aims of this study were to estimate genetic parameters of new automatically recorded milkability and temperament traits. Data from 77 commercial herds with Norwegian Red dairy cattle were analyzed by mixed linear animal models. The final data set contained 1,012,912 daily records from 4,883 cows in first to ninth lactation. For variance component estimation, univariate and bivariate models were used. Daily records of box time (BT), average flow rate (FR), kilograms of milk per minute of box time (MEF), handling time (HT), log-transformed HT, milking frequency, and milking interval were analyzed with repeatability models. Among these traits, FR, BT, and MEF showed the highest heritabilities of 0.48, 0.27, and 0.22, respectively, whereas heritability of log-transformed HT, HT, milking frequency, and milking interval was low (0.02-0.07). Unsuccessful milkings expressed as rejected milkings, incomplete milkings (IM), milkings with kick-offs (KO), and teat not found also showed low heritabilities (0.002-0.06). Due to low frequency, KO, rejected milkings, IM, and teat not found were also analyzed as proportions per lactation, which resulted in slightly higher heritability estimates. Genetic correlations were favorable and intermediate to strong between BT, HT, MEF, and FR with absolute values above 0.50. Intermediate and favorable correlations were found for IM and KO with BT, HT, MEF, and FR. Cow milkability in AMS can be improved by selection for reduced number of unsuccessful milkings, faster FR, increased MEF, and shorter BT and HT. Our results confirm that automatically recorded data on milkability and temperament can be valuable sources of information for routine genetic evaluations and that milking efficiency in AMS can be genetically improved.

Large-Scale Phenotyping of Livestock Welfare in Commercial Production Systems: A New Frontier in Animal Breeding

“…Thus, genetically selecting cows that are easier to train (or other motivation traits to enter the milking robot, such as low neophobic cows) is highly desirable; (2) cow ability to stay calm during cleaning/disinfection and attachment of milking equipment, especially in the presence of sounds and mechanical movements. Cows with a proactive temperament kick-off the milking equipment and prolong preparation and teat attachment times (Wethal and Heringstad, 2019); (3) inter-milking interval; (4) udder and individual quarter milk production (as more heterogeneous production among quarters will result in longer retention in the milking box); (5) udder conformation and teat size/placement, which is associated with teat cup attachment success rate; (6) milking time and length of the milking procedure (milking box time), which is directly associated with milking speed; (7) milk flow rate (milking speed). It is worth noting that milking speed is unfavorably correlated with udder health, and consequently, both traits need to be considered simultaneously (Sewalen et al, 2011).…”

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

“…Information included in the current study came from 77 Norwegian herds equipped with AMS from DeLaval (Tumba, Sweden). Data were gathered from 2016 to 2017 using remote desktop connections to the same herds as used in Wethal and Heringstad (2019). Due to memory limits, records per milking were available only 1 yr back in time as data were deleted daily from the AMS.…”

“…Measurements of SCC are mainly based on monthly test-day records; thus, there may be time for an animal to get infected and recover from a mastitis case between test days, leading to undiscovered udder infections if information is based on test-day SCC. In AMS, repeated and objective records per milking are available and can be used for genetic evaluation purposes (Carlström et al, 2013;Wethal and Heringstad, 2019). In-line recording of online cell count (OCC; DeLaval, Tumba, Sweden) and electrical conductivity (EC) offers alternative phenotypes for continuous monitoring of udder health in AMS.…”

Genetic Parameters Estimation of Milking Traits in Polish Holstein-Friesians Based on Automatic Milking System Data

“…At the same time, the automation of milking allows for recording many parameters of the milking process, which are not commonly or directly measured in the conventional system. The extra information includes the interval from the previous milking, number of milkings and cluster attachment time, milking duration, milking speed, milking box time, milk efficiency (milk yield per minute in the milking box), electrical milk conductivity [21,[28][29][30][31][32][33][34][35]. It should be highlighted that there are relatively few studies addressing the estimation of genetic parameters for AMS recorded traits [20,32,36].…”