Literature DB >> 22459822

Automatic measurement of touch and release angles of the fetlock joint for lameness detection in dairy cattle using vision techniques.

A Pluk1, C Bahr, A Poursaberi, W Maertens, A van Nuffel, D Berckmans.   

Abstract

This paper describes a synchronized measurement system combining image and pressure data to automatically record the angle of the metacarpus and metatarsus bones of the cow with respect to a vertical line, which is useful for lameness detection in dairy cattle. A camera system was developed to record the posture and movement of the cow and the timing and position of hoof placement and release were recorded using a pressure sensitive mat. Experiments with the automatic system were performed continuously on a farm in Ghent (Belgium) for 5 wk in September and October 2009. In total, 2,219 measurements were performed on 75 individual lactating Holstein cows. As a reference for the analysis of the calculated variables, the locomotion of the cows was visually scored from recorded videos by a trained observer into 3 classes of lameness [53.5% were scored with gait score (GS)1, 33.3% were scored with GS2, and 9.3% were scored with GS3]. The contact data of the pressure mat and the camera images recorded by the system were synchronized and combined to measure different angles of the legs of the cows, together with the range of motion of the leg. Significant differences were found between the different gait scores in the release angles of the front hooves, in the range of motion of the front hooves, and in the touch angles of the hind hooves. The contact data of the pressure mat and the camera images recorded by the system were synchronized and combined to measure different angles of the legs of the cows, together with the range of motion of the leg. With respect to the classification of lameness, the range of motion of the front hooves (42.1 and 42.8%) and the release angle of the front hooves (41.7 and 42.0%) were important variables. In 83.3% of the cows, a change in GS led to an increase in within-cow variance for the range of motion or the release angle of the front hooves. In 76.2% of the cows, an increase in GS led to a decrease in range of motion or an increase in release angle of the front hooves.
Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22459822     DOI: 10.3168/jds.2011-4547

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


  8 in total

Review 1.  Precision Technologies to Address Dairy Cattle Welfare: Focus on Lameness, Mastitis and Body Condition.

Authors:  Severiano R Silva; José P Araujo; Cristina Guedes; Flávio Silva; Mariana Almeida; Joaquim L Cerqueira
Journal:  Animals (Basel)       Date:  2021-07-30       Impact factor: 3.231

2.  Quantification of the effects of fur, fur color, and velocity on Time-Of-Flight technology in dairy production.

Authors:  Jennifer Salau; Ulrike Bauer; Jan H Haas; Georg Thaller; Jan Harms; Wolfgang Junge
Journal:  Springerplus       Date:  2015-03-26

Review 3.  Lameness Detection in Dairy Cows: Part 2. Use of Sensors to Automatically Register Changes in Locomotion or Behavior.

Authors:  Annelies Van Nuffel; Ingrid Zwertvaegher; Stephanie Van Weyenberg; Matti Pastell; Vivi M Thorup; Claudia Bahr; Bart Sonck; Wouter Saeys
Journal:  Animals (Basel)       Date:  2015-08-28       Impact factor: 2.752

Review 4.  Lameness Detection in Dairy Cows: Part 1. How to Distinguish between Non-Lame and Lame Cows Based on Differences in Locomotion or Behavior.

Authors:  Annelies Van Nuffel; Ingrid Zwertvaegher; Liesbet Pluym; Stephanie Van Weyenberg; Vivi M Thorup; Matti Pastell; Bart Sonck; Wouter Saeys
Journal:  Animals (Basel)       Date:  2015-08-28       Impact factor: 2.752

5.  A Feasibility Study on the Use of a Structured Light Depth-Camera for Three-Dimensional Body Measurements of Dairy Cows in Free-Stall Barns.

Authors:  Andrea Pezzuolo; Marcella Guarino; Luigi Sartori; Francesco Marinello
Journal:  Sensors (Basel)       Date:  2018-02-24       Impact factor: 3.576

Review 6.  A Review: Development of Computer Vision-Based Lameness Detection for Dairy Cows and Discussion of the Practical Applications.

Authors:  Xi Kang; Xu Dong Zhang; Gang Liu
Journal:  Sensors (Basel)       Date:  2021-01-22       Impact factor: 3.576

7.  Automated monitoring of dairy cow body condition, mobility and weight using a single 3D video capture device.

Authors:  M F Hansen; M L Smith; L N Smith; K Abdul Jabbar; D Forbes
Journal:  Comput Ind       Date:  2018-06       Impact factor: 7.635

8.  Recording behaviour of indoor-housed farm animals automatically using machine vision technology: A systematic review.

Authors:  Kaitlin Wurtz; Irene Camerlink; Richard B D'Eath; Alberto Peña Fernández; Tomas Norton; Juan Steibel; Janice Siegford
Journal:  PLoS One       Date:  2019-12-23       Impact factor: 3.240

  8 in total

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