Literature DB >> 29395141

Evaluation of an ear-tag-based accelerometer for monitoring rumination in dairy cows.

S Reiter1, G Sattlecker2, L Lidauer2, F Kickinger2, M Öhlschuster2, W Auer2, V Schweinzer1, D Klein-Jöbstl1, M Drillich1, M Iwersen3.   

Abstract

The objective of this study was to evaluate the ear-tag-based accelerometer system Smartbow (Smartbow GmbH, Weibern, Austria) for detecting rumination time, chewing cycles, and rumination bouts in indoor-housed dairy cows. For this, the parameters were determined by analyses of video recordings as reference and compared with the results of the accelerometer system. Additionally, we tested the intra- and inter-observer reliability as well as the agreement of direct cow observations and video recordings. Ten Simmental dairy cows in early lactation were equipped with 10-Hz accelerometer ear tags and kept in a pen separated from herd mates. A total mixed ration was fed twice a day via a roughage intake control system. During the study, cows' rumination and other activities were directly observed for 20 h by 2 trained observers. Additionally, cows were video recorded for 19 d, 24 h a day. After exclusion of unsuitable videos, 2,490 h of cow individual 1-h video sequences were eligible for further analyses. Out of this, one hundred 1-h video sequences were randomly selected and visually and manually classified by a trained observer using professional video analyses software. Based on these analyses, half of the data was used for development (based on data of 50-h video analyses) and testing (based on data of additional 50-h video analyses) of the Smartbow algorithms, respectively. Inter- and intra-observer reliability as well as the comparison of direct against video observations revealed in high agreements for rumination time and chewing cycles with Pearson correlation coefficients >0.99. The rumination time, chewing cycles, as well as rumination bouts detected by Smartbow were highly associated (r > 0.99) with the analyses of video recordings. Algorithm testing revealed in an underestimation of the average ± standard deviation rumination time per 1-h period by the Smartbow system of 17.0 ± 35.3 s (i.e., -1.2%), compared with visual observations. The average number ± standard deviation of chewing cycles and rumination bouts was overestimated by Smartbow by 59.8 ± 79.6 (i.e., 3.7%) and by 0.5 ± 0.9 (i.e., 1.6%), respectively, compared with the video analyses. In summary, the agreement between the Smartbow system with video analyses was excellent. From a practical and clinical point of view, the detected differences were negligible. However, further research is necessary to test the system under various field conditions and to evaluate the benefit of incorporating rumination data into herd management decisions.
Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  accelerometer; cow; monitoring; rumination

Mesh:

Year:  2018        PMID: 29395141     DOI: 10.3168/jds.2017-12686

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  5 in total

1.  Early Detection of Respiratory Diseases in Calves by Use of an Ear-Attached Accelerometer.

Authors:  Nasrin Ramezani Gardaloud; Christian Guse; Laura Lidauer; Alexandra Steininger; Florian Kickinger; Manfred Öhlschuster; Wolfgang Auer; Michael Iwersen; Marc Drillich; Daniela Klein-Jöbstl
Journal:  Animals (Basel)       Date:  2022-04-23       Impact factor: 3.231

2.  Evaluation of an electronic system for monitoring dairy cow rumination in a grazing-based system.

Authors:  Roberto Kappes; Deise Aline Knob; Angelica Leticia Scheid; Daniella Thais de Castro Bessani; Luís Henrique Schaitz; Laiz Perazzoli; Dileta Regina Moro Alessio; André Thaler Neto
Journal:  Trop Anim Health Prod       Date:  2021-06-29       Impact factor: 1.559

3.  Setup, Test and Validation of a UHF RFID System for Monitoring Feeding Behaviour of Dairy Cows.

Authors:  Felix Adrion; Markus Keller; Giulia Bianca Bozzolini; Christina Umstatter
Journal:  Sensors (Basel)       Date:  2020-12-09       Impact factor: 3.576

4.  Assessment of the Relationship between Postpartum Health and Mid-Lactation Performance, Behavior, and Feed Efficiency in Holstein Dairy Cows.

Authors:  Malia J Martin; Kent A Weigel; Heather M White
Journal:  Animals (Basel)       Date:  2021-05-13       Impact factor: 2.752

5.  Combination of Sensor Data and Health Monitoring for Early Detection of Subclinical Ketosis in Dairy Cows.

Authors:  Valentin Sturm; Dmitry Efrosinin; Manfred Öhlschuster; Erika Gusterer; Marc Drillich; Michael Iwersen
Journal:  Sensors (Basel)       Date:  2020-03-08       Impact factor: 3.576

  5 in total

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