Literature DB >> 23498014

Technical note: evaluation of data loggers for measuring lying behavior in dairy calves.

S Bonk1, O Burfeind, V S Suthar, W Heuwieser.   

Abstract

Lying behavior might indicate how the animal interacts with its environment and is an important indicator of cow and calf comfort. Measuring behavior can be time consuming; therefore, behavioral recording with the help of loggers has become common. Recently, the Hobo Pendant G data logger (Onset Computer Corp., Bourne, MA) was validated for measuring lying behavior in cows but no work to date has validated this logger for measuring lying behavior in calves. The objective of this study was to test the accuracy of the Hobo Pendant G data logger for measuring total lying time and frequency of lying bouts in dairy calves. In 2 experiments (experiment 1: thirty-seven 2-h observation periods; experiment 2: nineteen 24-h observation periods), we tested the effect of 2 different recording intervals, the effect of attachment to different legs, and the effect of removing short, potentially erroneous readings. We found an excellent relationship when comparing the 30-s and 60-s recording intervals. For total lying time and bout frequency, the highest correlation was found when the logger was attached to the hind legs and recording was conducted with a 60-s sampling interval. In experiment 2, average total lying time was 1,077 ± 54 min/24 h (18.0 ± 0.9h/24h), with an average frequency of 19.4 ± 4.5 bouts per day. Predictability, sensitivity, and specificity for experiment 2 were >97% using the 60-s recording interval and removing single readings of lying or standing from the data set compared with direct observation as reference. The data logger accurately measured total lying time and bout frequency when the sampling interval was ≤ 60 s and short readings of lying and standing up to 1 min were converted into the preceding behavior. The best results were achieved by attaching the logger to the right hind leg.
Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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Year:  2013        PMID: 23498014     DOI: 10.3168/jds.2012-6003

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


  8 in total

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Journal:  Animals (Basel)       Date:  2022-04-23       Impact factor: 3.231

2.  Effect of milk feeding strategy and lactic acid probiotics on growth and behavior of dairy calves fed using an automated feeding system1.

Authors:  Melissa C Cantor; Amy L Stanton; David K Combs; Joao H C Costa
Journal:  J Anim Sci       Date:  2019-03-01       Impact factor: 3.159

3.  Assessment of heat stress in 7-week old dairy calves with non-invasive physiological parameters in different thermal environments.

Authors:  Levente Kovács; Fruzsina Luca Kézér; Ferenc Ruff; Viktor Jurkovich; Ottó Szenci
Journal:  PLoS One       Date:  2018-07-18       Impact factor: 3.240

4.  Physiological and behavioral responses as indicators for early disease detection in dairy calves.

Authors:  G L Lowe; M A Sutherland; J R Waas; A L Schaefer; N R Cox; M Stewart
Journal:  J Dairy Sci       Date:  2019-04-17       Impact factor: 4.034

5.  A Systematic Review of Automatic Health Monitoring in Calves: Glimpsing the Future From Current Practice.

Authors:  Dengsheng Sun; Laura Webb; P P J van der Tol; Kees van Reenen
Journal:  Front Vet Sci       Date:  2021-11-26

6.  Lying down frequency as a discomfort index in heat stressed Holstein bull calves.

Authors:  Levente Kovács; Fruzsina L Kézér; Mikolt Bakony; Viktor Jurkovich; Ottó Szenci
Journal:  Sci Rep       Date:  2018-10-10       Impact factor: 4.379

7.  Using Non-Invasive Monitoring Technologies to Capture Behavioural, Physiological and Health Responses of Dairy Calves to Different Nutritional Regimes during the First Ten Weeks of Life.

Authors:  Gillian Scoley; Alan Gordon; Steven Morrison
Journal:  Animals (Basel)       Date:  2019-10-02       Impact factor: 2.752

8.  Measurement of dairy calf behavior prior to onset of clinical disease and in response to disbudding using automated calf feeders and accelerometers.

Authors:  M A Sutherland; G L Lowe; F J Huddart; J R Waas; M Stewart
Journal:  J Dairy Sci       Date:  2018-06-13       Impact factor: 4.034

  8 in total

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