Literature DB >> 24612813

Short communication: Decrease in rumination time as an indicator of the onset of calving.

S Büchel1, A Sundrum2.   

Abstract

The aim of this study was to investigate whether rumination time (RT) is affected by the onset of calving. The relationship between both feeding time and dry matter intake (DMI) to the onset of calving was also examined. In addition, the correlation between feeding behavior characteristics, described here as RT, feeding time, and DMI, was evaluated. Under test conditions, the feeding behavior of pregnant Holstein cows was recorded from the time when they were moved into calving pens (usually 7 to 5d prepartum) until the onset of calving. Feeding time and DMI were recorded by automatic feed bins; RT was measured continuously by a measuring halter based on electromyography (DairyCheck; BITSz Engineering GmbH, Zwickau, Germany), which constitutes a new approach regarding feeding behavior detection. Data analysis related to the final 72 h, before the onset of calving, which were divided into twelve 6-h blocks. The last 6h (one 6-h block) before calving were compared with the 72- to 7-h time frame (11 times 6-h blocks) before calving, which was defined as the reference period. For this time period, feeding behavior data for 17 cows was fully available, which was the precondition for data analysis. In the final 6h before imminent birth, RT was significantly reduced. During this time, it was found that the mean minimum RT was 69.9 ± 28.5 min/6h compared with the mean RT of 95.5 ± 30.8 min/6h in the reference period. The average decrease in RT was 27% (25.6 min/6h). In addition, feeding time and DMI were significantly reduced. The average decrease in feeding time was 57% (20.8 min/6h), and in DMI it was 56% (1.9 kg/6h). High correlation coefficients between feeding behavior characteristics were only found between feeding time and DMI. Values of feeding behavior among cows were characterized by high variability. Recording RT can serve as a useful tool for predicting the timing of birth for dairy cows, but further research is necessary.
Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  birth; feeding behavior; management support; measurement system

Mesh:

Year:  2014        PMID: 24612813     DOI: 10.3168/jds.2013-7613

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


  5 in total

1.  The effects of source and concentration of dietary fiber, starch, and fatty acids on the daily patterns of feed intake, rumination, and rumen pH in dairy cows.

Authors:  I J Salfer; M C Morelli; Y Ying; M S Allen; K J Harvatine
Journal:  J Dairy Sci       Date:  2018-10-11       Impact factor: 4.034

2.  Efficacy of statistical process control procedures to identify deviations in continuously measured physiologic and behavioral variables in beef steers experimentally challenged with Mannheimia haemolytica.

Authors:  William C Kayser; Gordon E Carstens; Ira L Parsons; Kevin E Washburn; Sara D Lawhon; William E Pinchak; Eric Chevaux; Andrew L Skidmore
Journal:  J Anim Sci       Date:  2020-02-01       Impact factor: 3.159

3.  Efficacy of statistical process control procedures to identify deviations in continuously measured physiological and behavioral variables in beef heifers resulting from an experimentally combined viral-bacterial challenge.

Authors:  William Christian Kayser; Gordon E Carstens; Ira Loyd Parsons; Kevin E Washburn; Sara D Lawhon; William E Pinchak; Eric Chevaux; Andrew L Skidmore
Journal:  J Anim Sci       Date:  2021-09-01       Impact factor: 3.338

4.  Assessment of Sensitivity and Profitability of an Intravaginal Sensor for Remote Calving Prediction in Dairy Cattle.

Authors:  Martina Crociati; Lakamy Sylla; Giuseppe Stradaioli; Maurizio Monaci; Alfonso Zecconi
Journal:  Sensors (Basel)       Date:  2021-12-14       Impact factor: 3.576

Review 5.  How to Predict Parturition in Cattle? A Literature Review of Automatic Devices and Technologies for Remote Monitoring and Calving Prediction.

Authors:  Martina Crociati; Lakamy Sylla; Arianna De Vincenzi; Giuseppe Stradaioli; Maurizio Monaci
Journal:  Animals (Basel)       Date:  2022-02-08       Impact factor: 2.752

  5 in total

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