Elaboration of basic methods for automatic analysis of cows' gait.

Two different methods for automatic registration and analysis were used to produce data for comparison and analysis of lame and healthy animals’ gait in Estonia. A walk over mat with two quazi-piezoelectric sensors was elaborated and tested in cooperation with University of Helsinki. Preliminary analysis indicates that lameness can be seen as asymmetric gait and thus the quazi-piezoelectric walk-over mat is a promising tool for automatic leg problem detection. A video-system was introduced to record walking pattern of cows in co-operation with Catholic University of Leuven. For video recordings three cameras were used to obtain top, side and leg views with StreamPix software video-signal capture. Possibilities of image based separation of dairy cows with real time vision system and preliminary settlement of this was developed. A model-based motion scoring system is proposed for derivation of image parameters needed for lameness detection. About 600 cows once a week were investigated in a large dairy farm during four months’ period. Dairy cows’ gait pattern was recorded with the aid of quazi-piezoelectric walk-over mat and video-system. Preliminary lameness scoring was performed in the cowshed visually by two experts. These scoring results were later specified by expert commission on the basis of video-recordings. Lameness scores (according to Sprecher et al) were assigned as follows: 1–6,012 cases, 2–1,181 cases, 3–522 cases, 4–105 cases and 5–37 cases from total 10,653 cases. The database of cows’ identification numbers, lameness scores and disordered legs description was created, that allows synchronization of walk-over mat signals data and video files.

[1]  D. Sprecher,et al.  A lameness scoring system that uses posture and gait to predict dairy cattle reproductive performance. , 1997, Theriogenology.

[2]  Daniel Berckmans,et al.  Acquisition techniques for dairy cow gait analysis , 2007 .

[3]  M. M. Neto,et al.  Dairy Cattle Linear and Angular Kinematics during the Stance Phase , 2007 .

[4]  Daniel Berckmans,et al.  Image Based Separation of Dairy Cows for Automatic Lameness Detection with a Real Time Vision System , 2009 .

[5]  M. Endres,et al.  Prevalence of lameness in high-producing holstein cows housed in freestall barns in Minnesota. , 2006, Journal of dairy science.

[6]  Daniel Berckmans,et al.  Automatic detection of lameness in dairy cattle-Vision-based trackway analysis in cow's locomotion , 2008 .

[7]  M Pastell,et al.  Contactless measurement of cow behavior in a milking robot , 2006, Behavior research methods.

[8]  Matti Pastell,et al.  Monitoring cow health in a milking robot , 2005 .

[9]  R. M. Dyer,et al.  A System for Identifying Lameness in Dairy Cattle , 2002 .

[10]  Daniel Berckmans,et al.  AUTOMATIC ON-LINE MONITORING OF ANIMALS BY PRECISION LIVESTOCK FARMING , 2004 .

[11]  M. Kujala,et al.  Assessing cows' welfare : weighing the cow in a milking robot , 2006 .

[12]  Sidney Cox,et al.  Precision livestock farming. , 2003 .

[13]  D. Berckmans,et al.  Approach to model based motion scoring for lameness detection in dairy cattle , 2009 .

[14]  M.B.M. Bracke,et al.  Scientist' assessment of the impact of housing and management on animal welfare , 2001 .

[15]  Daniel Berckmans.  Preface: Precision livestock farming (PLF) , 2008 .

[16]  Matti Pastell,et al.  Detecting cow's lameness using force sensors , 2008 .

[17]  A. Lefcourt,et al.  Comparison of models to identify lame cows based on gait and lesion scores, and limb movement variables. , 2006, Journal of dairy science.

[18]  Jukka Lekkala,et al.  ElectroMechanical Film (EMFi) — a new multipurpose electret material , 2000 .