The 10th Anniversary of Veterinary Sciences—Recent Advances in the Epidemiology of Cattle Health and Welfare

A special issue of Veterinary Sciences (ISSN 2306-7381). This special issue belongs to the section "Veterinary Microbiology, Parasitology and Immunology".

Deadline for manuscript submissions: 10 March 2025 | Viewed by 1113

Special Issue Editors


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Guest Editor
Department of Population Health and Reproduction, School of Veterinary Medicine, University of California, Davis, CA 95616, USA
Interests: veterinary medicine; epidemiology; biostatistics

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Guest Editor
Veterinary Medicine Teaching and Research Center, School of Veterinary Medicine, University of California Davis, Tulare, CA 93274, USA
Interests: dairy cattle diseases; epidemiology; foreign animal diseases; antimicrobial resistance

Special Issue Information

Dear Colleagues,

Cattle are a major source of high-value protein necessary to meet the increasing human population demand for food and income in communities worldwide. Sustainable cattle production necessitates healthy herds and animal welfare. To that end, the best management practices identified using epidemiological study designs and empirical and observational studies on all breeds and production stages of both dairy and beef cattle are paramount to advancing our knowledge.

The current Special Issue seeks to bring together researchers to share their research advances on the occurrence, risk factors, control, and prevention of cattle diseases and the conditions that affect animal welfare.

Scientists, clinicians, and extension and outreach specialists working on advancing cattle health and welfare are invited to submit their research in all areas concerning the health and welfare of dairy and beef cattle. Specifically, cattle management practices, infectious diseases, reproduction, nutrition, behavior, and welfare topics are welcome.

Prof. Dr. Sharif S. Aly
Dr. Wagdy R. Elashmawy
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Veterinary Sciences is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2100 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • cattle
  • health management
  • infectious diseases
  • epidemiology
  • welfare

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Published Papers (1 paper)

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Research

19 pages, 23108 KiB  
Article
Automated Classification System Based on YOLO Architecture for Body Condition Score in Dairy Cows
by Emre Dandıl, Kerim Kürşat Çevik and Mustafa Boğa
Vet. Sci. 2024, 11(9), 399; https://doi.org/10.3390/vetsci11090399 - 1 Sep 2024
Viewed by 590
Abstract
Body condition score (BCS) is a common tool used to assess the welfare of dairy cows and is based on scoring animals according to their external appearance. If the BCS of dairy cows deviates from the required value, it can lead to diseases [...] Read more.
Body condition score (BCS) is a common tool used to assess the welfare of dairy cows and is based on scoring animals according to their external appearance. If the BCS of dairy cows deviates from the required value, it can lead to diseases caused by metabolic problems in the animal, increased medication costs, low productivity, and even the loss of dairy cows. BCS scores for dairy cows on farms are mostly determined by observation based on expert knowledge and experience. This study proposes an automatic classification system for BCS determination in dairy cows using the YOLOv8x deep learning architecture. In this study, firstly, an original dataset was prepared by dividing the BCS scale into five different classes of Emaciated, Poor, Good, Fat, and Obese for images of Holstein and Simmental cow breeds collected from different farms. In the experimental analyses performed on the dataset prepared in this study, the BCS values of 102 out of a total of 126 cow images in the test set were correctly classified using the proposed YOLOv8x deep learning architecture. Furthermore, an average accuracy of 0.81 was achieved for all BCS classes in Holstein and Simmental cows. In addition, the average area under the precision–recall curve was 0.87. In conclusion, the BCS classification system for dairy cows proposed in this study may allow for the accurate observation of animals with rapid declines in body condition. In addition, the BCS classification system can be used as a tool for production decision-makers in early lactation to reduce the negative energy balance. Full article
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