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Volume 61, issue 2 | Copyright
Arch. Anim. Breed., 61, 161-171, 2018
https://doi.org/10.5194/aab-61-161-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Original study 13 Apr 2018

Original study | 13 Apr 2018

Genetic parameters for longitudinal behavior and health indicator traits generated in automatic milking systems

Laura Viviana Santos1, Kerstin Brügemann1, Asja Ebinghaus2, and Sven König1 Laura Viviana Santos et al.
  • 1Institute of Animal Breeding and Genetics, University of Gießen, Ludwigstraße 21b, 35390 Gießen, Germany
  • 2Department of Farm Animal Behavior and Husbandry, University of Kassel, Nordbahnhofstraße 1a, 37213 Witzenhausen, Germany

Abstract. Genetic (co)variance components were estimated for alternative functional traits generated by automatic milking systems (AMSs), and reflecting dairy cow behavior and health. Data recording spanned a period of 30 days and included 70700 observations (visits to the AMS) from 922 Holstein cows kept in three German farms. The three selected farms used the same type of AMS and specific selection gates allowing natural cow behavior on a voluntary basis. AMS traits used as behavior indicator traits were AMS visits per cow and day as binary traits, with a threshold for equal to or greater than three visits (VIS3) and equal to or greater than four visits (VIS4), knocking off the milking device with a threshold of at least one udder quarter, also as a binary trait (KO), milking duration of each AMS visit in minutes (DUR), average milk flow in kgmin−1 (AMF), and the interval between two consecutive milkings (INT). Electrical conductivity (EC) of milk from each udder quarter and in total was used as a health indicator trait. For genetic analyses, in univariate and bivariate models, linear and generalized linear mixed models (GLMMs) with a logit link function were applied to Gaussian distributed and binary traits, respectively. The heritability was 0.08±0.03 for VIS3, 0.05±0.05 for VIS4, 0.03±0.03 for KO, 0.19±0.07 for DUR, 0.25±0.07 for AMF, and 0.07±0.03 for INT. Heritabilities for EC varied between 0.37±0.08 and 0.46±0.09, depending on the udder quarter. On the genetic scale, an increased number of AMS visits (VIS3 and VIS4) were associated with an increase of KO (rg = 0.24 and rg = 0.55, respectively). From a genetic perspective, high-milk-yielding cows visited the AMS more often (rg = 0.49 for VIS3 and rg = 0.80 for VIS4), had a faster AMF (rg = 0.40), and shorter INT (rg = −0.51). When considering these traits as behavior indicator traits, selection of cows with desired temperament simultaneously increases milk yield. An increase of automatically and objectively recorded AMS traits with moderate heritabilities justifies modifications of dairy cattle breeding goals towards higher emphasis on behavioral traits, especially when developing specific robot indices. Nevertheless, ongoing research in this regard with a larger data is suggested in order to validate the results from the present pilot study.

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The impact of the milking technique on the individual animal and the reaction of the animal on the technique were investigated. With the use of objectively recorded data from automatic milking systems (AMSs), auxiliary traits that reflect animal behavior in the milking system were defined, free from subjective impressions of classifiers. There is an apparent possibility to breed cows for AMS systems based on AMS data, though it is imperative to have further validation based on larger datasets.
The impact of the milking technique on the individual animal and the reaction of the animal on...
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