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

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 < 0.01), but significantly positively correlated with walking activity (r = 0.20, P < 0.001). Regarding subjectively cow welfare and temperament scoring, we found positive correlations between the level of aggressiveness towards other herd mates and the intra herd rank order (r = 0.36, P < 0.001), indicating that cows with a higher intra-herd rank showed increased aggressive behaviour. Mixed model analysis revealed that DSN cows spending more time lying down (>7 h/d) had reduced daily milk and fat yields. Oppositely, high yielding cows showed intensive feeding and rumination behaviour. A substantial decrease in rumination and feeding time was observed for cows with elevated somatic cells (>700,000 cells/mL), suggesting utilisation of sensor behaviour as an indicator for udder health. We identified significantly higher body condition scores for cows with increased lying times, whereas active cows with high daily feeding and rumination times had quite low body conditions scores. Hence, optimal health and behaviour monitoring for cows in grazing systems implies consideration of both trait components objectively recorded longitudinal sensor traits and subjectively scored behaviour and health indicators. Overall, individual behaviour pattern variation was detected, via sensor technology for dual-purpose cows kept in grazing systems. Hence, automatically recorded longitudinal sensor data is a proper alternative for cow phenotyping in extensive grassland systems, aiming on an accurate data basis for genetic evaluations.