Literature DB >> 26549665

Creating a model to detect dairy cattle farms with poor welfare using a national database.

C Krug1, M J Haskell2, T Nunes3, G Stilwell3.   

Abstract

The objective of this study was to determine whether dairy farms with poor cow welfare could be identified using a national database for bovine identification and registration that monitors cattle deaths and movements. The welfare of dairy cattle was assessed using the Welfare Quality(®) protocol (WQ) on 24 Portuguese dairy farms and on 1930 animals. Five farms were classified as having poor welfare and the other 19 were classified as having good welfare. Fourteen million records from the national cattle database were analysed to identify potential welfare indicators for dairy farms. Fifteen potential national welfare indicators were calculated based on that database, and the link between the results on the WQ evaluation and the national cattle database was made using the identification code of each farm. Within the potential national welfare indicators, only two were significantly different between farms with good welfare and poor welfare, 'proportion of on-farm deaths' (p<0.01) and 'female/male birth ratio' (p<0.05). To determine whether the database welfare indicators could be used to distinguish farms with good welfare from farms with poor welfare, we created a model using the classifier J48 of Waikato Environment for Knowledge Analysis. The model was a decision tree based on two variables, 'proportion of on-farm deaths' and 'calving-to-calving interval', and it was able to correctly identify 70% and 79% of the farms classified as having poor and good welfare, respectively. The national cattle database analysis could be useful in helping official veterinary services in detecting farms that have poor welfare and also in determining which welfare indicators are poor on each particular farm.
Copyright © 2015 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Animal welfare; Dairy cattle; National cattle database; Welfare Quality

Mesh:

Year:  2015        PMID: 26549665     DOI: 10.1016/j.prevetmed.2015.10.014

Source DB:  PubMed          Journal:  Prev Vet Med        ISSN: 0167-5877            Impact factor:   2.670


  2 in total

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Journal:  Animals (Basel)       Date:  2021-03-06       Impact factor: 2.752

Review 2.  Data-Based Variables Used as Indicators of Dairy Cow Welfare at Farm Level: A Review.

Authors:  Barbara Lutz; Sibylle Zwygart; Christina Rufener; Joan-Bryce Burla; Beat Thomann; Dimitri Stucki
Journal:  Animals (Basel)       Date:  2021-12-04       Impact factor: 2.752

  2 in total

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