Foot health records are useful in monitoring the degree of lameness within dairy herds and, perhaps more importantly, providing insight into the underlying factors causing lameness. A database containing the incidence of foot lesions on large confinement dairy operations is largely unavailable but could prove useful to demonstrate the importance of collecting and analyzing foot lesion data to reduce lameness. Our objective was to merge foot lesion records from several dairy herds and establish a database to demonstrate how to use such data to better understand when and why foot lesions occur as an important means to manage lameness in dairy herds. The database consisted of 12 mo of records from 17 dairies (14 freestall, 1 combination dirt lot and freestall, 2 dirt lot) representing 58,155 cows from herds ranging in size from 631 to 9,355 animals in 9 states from the United States and 2 herds located in the Southern Hemisphere. Data were partitioned and analyzed as 2 separate data sets: (1) herds recording only lame events (cows lame when examined; n=8), and (2) herds recording both lame and routine trim events (n=9). Data were analyzed using PROC FREQ (SAS Institute Inc., Cary, NC) and significance was determined using Chi-square. White line disease, sole ulcer, toe ulcer, digital dermatitis, and foot rot comprised 93 and 40% (excluding routine trim with no lesion, 55%) of lesions for herds recording only lame events and those recording lame and trim events, respectively. Ratio of infectious to noninfectious lesions decreased with increasing lactation number in both data sets. Digital dermatitis and foot rot were greatest in the first 60 d in milk and differed across lactation number. Noninfectious lesions were greatest following summer heat stress, whereas infectious lesions were greatest during the coolest quarter of the year. In conclusion, analysis of the foot health data from these dairies demonstrates that (1) infectious lesions of the foot skin and soft tissues predominate in early lactation and during cooler months of the year, and (2) noninfectious lesions predominate during the 3 mo following summer heat stress and their distribution follows a typical lactation curve.
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http://dx.doi.org/10.3168/jds.2012-6017 | DOI Listing |
J Anim Sci
January 2025
USDA-Agricultural Research Service, U.S. Meat Animal Research Center (USMARC), Clay Center, NE, USA.
Sow lameness results in premature culling, causing economic loss and well-being issues. A study, utilizing a pressure-sensing mat (GAIT4) and video monitoring system (NUtrack), was conducted to identify objective measurements on gilts that are predictive of future lameness. Gilts (N = 3656) were categorized to describe their lifetime soundness: SOUND, retained for breeding with no detected mobility issues; LAME_SOW, retained for breeding and detected lame as a sow; CULL_STR, not retained due to poor leg structure; LAME_GILT, not retained due to visible signs of lameness; and CULL, not retained due to reasons other than leg structure.
View Article and Find Full Text PDFCancer Med
December 2024
Laboratoire de Génie Industriel, CentraleSupélec-Paris-Saclay Campus, Gif Sur Yvette, France.
J Dairy Res
October 2024
Department of Surgery, Faculty of Veterinary Medicine, Aydin Adnan Menderes University, Isikli, Aydin, Turkey.
This research paper proposes a simple image processing technique for automatic lameness detection in dairy cows under farm conditions. Seventy-five cows were selected from a dairy farm and visually assessed for a reference/real lameness score (RLS) as they left the milking parlor, while simultaneously being video-captured. The method employed a designated walking path and video recordings processed through image analysis to derive a new computerized automatic lameness score (ALDS) based on calculated factors from back arch posture.
View Article and Find Full Text PDFJ Am Med Inform Assoc
November 2024
CentraleSupélec, Laboratoire de Génie Industriel, Université Paris-Saclay, 91190 Gif-sur-Yvette, France.
Objectives: Clinical Data Warehouses (CDW) are the designated infrastructures to enable access and analysis of large quantities of electronic health record data. Building and managing such systems implies extensive "data work" and coordination between multiple stakeholders. Our study focuses on the challenges these stakeholders face when designing, operating, and ensuring the durability of CDWs for research.
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