Evaluation of the RumiWatchSystem for measuring grazing behaviour of cows

J Werner,L Leso,C Umstatter,J Niederhauser,E Kennedy,A Geoghegan,L Shalloo,M Schick,B O’Brien

doi:10.1016/j.jneumeth.2017.08.022

Abstract

Feeding behaviour is an important parameter of animal performance, health and welfare, as well as reflecting levels and quality of feed available. Previously, sensors were only used for measuring animal feeding behaviour in indoor housing systems. However, sensors such as the RumiWatchSystem can also monitor such behaviour continuously in pasture-based environments. Therefore, the aim of this study was to validate the RumiWatchSystem to record cow activity and feeding behaviour in a pasture-based system. The RumiWatchSystem was evaluated against visual observation across two different experiments. The time duration per hour at grazing, rumination, walking, standing and lying recorded by the RumiWatchSystem was compared to the visual observation data in Experiment 1. Concordance Correlation Coefficient (CCC) values of CCC=0.96 for grazing, CCC=0.99 for rumination, CCC=1.00 for standing and lying and CCC=0.92 for walking were obtained. The number of grazing and rumination bouts within one hour were also analysed resulting in Cohen‘s Kappa (κ)=0.62 and κ=0.86 for grazing and rumination bouts, respectively. Experiment 2 focused on the validation of grazing bites and rumination chews. The accordance between visual observation and automated measurement by the RumiWatchSystem was high with CCC=0.78 and CCC=0.94 for grazing bites and rumination chews, respectively. These results indicate that the RumiWatchSystem is a reliable sensor technology for observing cow activity and feeding behaviour in a pasture based milk production system, and may be used for research purposes in a grazing environment.

Highlights

With increasing scale on farms, and declining available labour, there is a requirement for technologies that assist farmers in their day to day management
This study was part of a larger study where different levels of feed allowance were allocated to dairy cows across different periods of the lactation and for different durations. 2.1 Sensor technology The RumiWatchSystem consists of two separate devices with associated software packages for managing the sensors (RumiWatch Manager) and analysing data (RumiWatch Converter)
The Cohen’s Kappa value was κ = 0.84 for the visual feeding behaviour measurements compared with the noseband sensor and κ = 0.89 for the visual activity measurements compared to the pedometer

Summary

Introduction

With increasing scale on farms, and declining available labour, there is a requirement for technologies that assist farmers in their day to day management. In a pasture based system the balance between the feed offered and the herd demand needs to be optimized to maximise grass utilisation while simultaneously ensuring that animals are well fed at pasture. Shortage in labour and time to observe animals makes it difficult for farmers to monitor all animals intensely. Automated monitoring for quantifying physiological and behavioural parameters, e.g. oestrus, somatic cell count and feeding behaviour, can give an insight into overall health status, important animal events as well as helping with feeding management. For a continuous monitoring of these physiological and behavioural parameters sensor-based, easy-to-use tools for farmers need to be developed

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