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Associations between precision sensor data with productivity, health and welfare indicator traits in native black and white dual-purpose cattle under grazing conditions

By Maria Jaeger, Kerstin Brügemann, Horst Brandt, Sven König

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Abstract

The aim of the study was to analyse the relationships between conventional production as well as subjectively scored welfare assessment traits with longitudinal sensor measurements (i.e., behavioural activity traits) of dual-purpose cattle kept in grazing systems. Such aim implies getting knowledge into dual-purpose cow grazing behaviour, and inferring behaviour trait thresholds from a management perspective (e.g., development of an early-warning system for clinical mastitis). In this regard, 49 native black and white dual-purpose cows from the breed Deutsches Schwarzbuntes Niederungsrind (DSN) were equipped with electronic sensor ear tags (accelerometer attached to radio frequency identification tag). Over a period of twelve months including two grazing seasons, ear sensors recorded individual cow behaviour for rumination, feeding, lying, active, and highly active, as well as ear surface temperature. Data for all traits were transformed into the measurement unit “percent per day”. Additionally, a trained classifier subjectively scored welfare assessment traits (body condition score, locomotion score, udder/ leg hygiene score) and temperament traits (intra-herd rank order, aggressiveness and general temperament during milking). A third trait category included official test-day records for milk-kg, fat-kg and somatic cell count. Association analyses focussed on trait correlations, and on mixed model applications (i.e. defining fixed effect classes for explanatory sensor traits). Sensor ear temperature was significantly negatively correlated with feeding behaviour (r=−0.17, P 

Publication Title Applied Animal Behaviour Science
Volume 212
Pages 9-18
ISBN/ISSN 0168-1591
DOI https://doi.org/10.1016/j.applanim.2019.01.008
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Tags
  1. Behavior and behavior mechanisms
  2. Cattle
  3. Grazing
  4. sensors