Literature DB >> 29029873

Prediction of calving time in dairy cattle.

Mahmoud Fadul1, Christopher Bogdahn2, Maher Alsaaod2, Jürg Hüsler3, Alexander Starke4, Adrian Steiner2, Gaby Hirsbrunner5.   

Abstract

This prospective study was carried out to predict the calving time in primiparous (n=11) and multiparous (n=22) Holstein-Friesian cows using the combination of data obtained from the RumiWatch noseband-sensor and 3D-accelerometer. The animals included in the study were fitted with the RumiWatch noseband-sensor and 3D-accelerometer at least 10days before the expected calving day. The calving event was defined as the time of the first appearance of the calves' feet outside the vulva, and this moment was determined by farm staff and/or confirmed by video monitor. As primiparous and multiparous cows behaved differently, two models including data of noseband-sensors and 3D-accelerometers were used to predict the calving time in each group. Lying bouts (LB) increased and rumination chews (RC) decreased similarly in both groups; besides that, boluses (B) decreased and other activities (OA) increased significantly in multiparous and primiparous cows, respectively. The sensitivity (Se) and specificity (Sp) for prediction of the onset of calving within the next 3h were determined with the logistic regression and ROC analysis (Se=88.9%, 85% and Sp=93.3%, 74% for multiparous and primiparous cows, respectively). This pilot study revealed that the RumiWatch system is a useful tool to predict calving time under farm conditions.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Calving; Dairy; Multiparous; Prediction; Primiparous; RumiWatch

Mesh:

Year:  2017        PMID: 29029873     DOI: 10.1016/j.anireprosci.2017.10.003

Source DB:  PubMed          Journal:  Anim Reprod Sci        ISSN: 0378-4320            Impact factor:   2.145


  7 in total

1.  Comparison between a Calving Predictive System and a Routine Prepartal Examination in German Holstein Heifers and Cows.

Authors:  Lara Górriz-Martín; Annabel Koenig; Klaus Jung; Wiebke Bergforth; Dirk von Soosten; Martina Hoedemaker; Árpád Csaba Bajcsy
Journal:  Vet Sci       Date:  2022-04-15

2.  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

3.  Chewing and Drinking Activity during Transition Period and Lactation in Dairy Cows Fed Partial Mixed Rations.

Authors:  Viktoria Brandstetter; Viktoria Neubauer; Elke Humer; Iris Kröger; Qendrim Zebeli
Journal:  Animals (Basel)       Date:  2019-12-05       Impact factor: 2.752

4.  Activity-Integrated Hidden Markov Model to Predict Calving Time.

Authors:  Kosuke Sumi; Swe Zar Maw; Thi Thi Zin; Pyke Tin; Ikuo Kobayashi; Yoichiro Horii
Journal:  Animals (Basel)       Date:  2021-02-03       Impact factor: 2.752

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

6.  Assessment of feeding, ruminating and locomotion behaviors in dairy cows around calving - a retrospective clinical study to early detect spontaneous disease appearance.

Authors:  Mahmoud Fadul; Luigi D'Andrea; Maher Alsaaod; Giuliano Borriello; Antonio Di Lori; Dimitri Stucki; Paolo Ciaramella; Adrian Steiner; Jacopo Guccione
Journal:  PLoS One       Date:  2022-03-04       Impact factor: 3.240

Review 7.  Accuracy to Predict the Onset of Calving in Dairy Farms by Using Different Precision Livestock Farming Devices.

Authors:  Ottó Szenci
Journal:  Animals (Basel)       Date:  2022-08-08       Impact factor: 3.231

  7 in total

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