Dairy cattle

Genetic Selection for Improved Milking Efficiency and Adaptability in Automatic Milking Systems

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Abstract

The widespread adoption of automatic milking systems (AMS) has resulted in an array of detailed milking-related data being recorded on an individual cow basis. New opportunities for genetic selection have been explored, particularly by identifying traits that can improve cow adaptability and milking efficiency in AMS. In this study, we introduced and evaluated a set of novel sensor-based traits derived from AMS data. These traits, which capture aspects of milking efficiency and cow behavior, have not previously been considered in the development of a robot efficiency index and were assessed for their potential inclusion. The data consisted of 9,997 Holstein cows from 39 commercial farms across North America with records for each AMS unit visit from 2022 to 2024. Variance components and genomic breeding values were estimated for each trait. Heritability estimates ranged from 0.07 to 0.43, and the lowest values were observed for behavioral traits. Genetic and phenotypic correlations among the traits studied were estimated. The combination of these traits into an index can help dairy farmers improve their herds by selecting animals that are genetically better for AMS.

Keywords: 2026

How to Cite:

Campos, I., Hidding, S., Carson, M., Shannon, J., Roelofs, R., Mazeris, F., Lohuis, M. & Malchiodi, F., (2026) “Genetic Selection for Improved Milking Efficiency and Adaptability in Automatic Milking Systems”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2286666. doi: https://doi.org/10.31274/wcgalp.24087

Rights: 1