Literature DB >> 28842192

Evaluation of the RumiWatchSystem for measuring grazing behaviour of cows.

J Werner1, L Leso2, C Umstatter3, J Niederhauser4, E Kennedy5, A Geoghegan5, L Shalloo5, M Schick3, B O'Brien5.   

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.
Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Bout criteria; Grazing bites; Grazing time; Monitoring behavior; Sensor technology; Validation

Mesh:

Year:  2017        PMID: 28842192     DOI: 10.1016/j.jneumeth.2017.08.022

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


  12 in total

Review 1.  Industry 4.0 and Precision Livestock Farming (PLF): An up to Date Overview across Animal Productions.

Authors:  Sarah Morrone; Corrado Dimauro; Filippo Gambella; Maria Grazia Cappai
Journal:  Sensors (Basel)       Date:  2022-06-07       Impact factor: 3.847

Review 2.  Understanding intake on pastures: how, why, and a way forward.

Authors:  William B Smith; Michael L Galyean; Robert L Kallenbach; Paul L Greenwood; Eric J Scholljegerdes
Journal:  J Anim Sci       Date:  2021-06-01       Impact factor: 3.159

3.  Methane Emissions and Milk Fatty Acid Profiles in Dairy Cows Fed Linseed, Measured at the Group Level in a Naturally Ventilated Housing and Individually in Respiration Chambers.

Authors:  Jernej Poteko; Sabine Schrade; Kerstin Zeyer; Joachim Mohn; Michael Zaehner; Johanna O Zeitz; Michael Kreuzer; Angela Schwarm
Journal:  Animals (Basel)       Date:  2020-06-24       Impact factor: 2.752

4.  Evaluation and application potential of an accelerometer-based collar device for measuring grazing behavior of dairy cows.

Authors:  J Werner; C Umstatter; L Leso; E Kennedy; A Geoghegan; L Shalloo; M Schick; B O'Brien
Journal:  Animal       Date:  2019-02-08       Impact factor: 3.240

5.  A Systematic Review on Commercially Available and Validated Sensor Technologies for Welfare Assessment of Dairy Cattle.

Authors:  Anna H Stygar; Yaneth Gómez; Greta V Berteselli; Emanuela Dalla Costa; Elisabetta Canali; Jarkko K Niemi; Pol Llonch; Matti Pastell
Journal:  Front Vet Sci       Date:  2021-03-29

6.  The Effect of Frequency of Fresh Pasture Allocation on the Feeding Behaviour of High Production Dairy Cows.

Authors:  Jessica G Pollock; Alan W Gordon; Kathryn M Huson; Deborah A McConnell
Journal:  Animals (Basel)       Date:  2022-01-20       Impact factor: 2.752

7.  Evaluation of a Binary Classification Approach to Detect Herbage Scarcity Based on Behavioral Responses of Grazing Dairy Cows.

Authors:  Leonie Hart; Uta Dickhoefer; Esther Paulenz; Christina Umstaetter
Journal:  Sensors (Basel)       Date:  2022-01-26       Impact factor: 3.576

8.  Grazing Cow Behavior's Association with Mild and Moderate Lameness.

Authors:  Niall W O'Leary; Daire T Byrne; Pauline Garcia; Jessica Werner; Morgan Cabedoche; Laurence Shalloo
Journal:  Animals (Basel)       Date:  2020-04-11       Impact factor: 2.752

9.  Machine Learning Based Prediction of Insufficient Herbage Allowance with Automated Feeding Behaviour and Activity Data.

Authors:  Abu Zar Shafiullah; Jessica Werner; Emer Kennedy; Lorenzo Leso; Bernadette O'Brien; Christina Umstätter
Journal:  Sensors (Basel)       Date:  2019-10-16       Impact factor: 3.576

Review 10.  Animal Welfare Implications of Digital Tools for Monitoring and Management of Cattle and Sheep on Pasture.

Authors:  Anders Herlin; Emma Brunberg; Jan Hultgren; Niclas Högberg; Anna Rydberg; Anna Skarin
Journal:  Animals (Basel)       Date:  2021-03-15       Impact factor: 2.752

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