National Veterinary Institute, SE-751 89 Uppsala, Sweden.
Acta Vet Scand. 2011;53 Suppl 1(Suppl 1):S8. doi: 10.1186/1751-0147-53-S1-S8. Epub 2011 Jun 20.
Pre-recorded register data from dairy herds are available in almost all Nordic countries. These databases can be used for research purposes, and one of the research areas is animal welfare. The aim of this study was to investigate if pre-recorded register data could be used to identify herds with good welfare, and to investigate if a combination of register data sets could be used to be able to more correctly distinguish between herds with good welfare and herds with welfare deficiencies.
As a first step, nine animal-based measurements on calves, young stock and cows in 55 randomly selected herds were performed on-farm as the basis for a classification of welfare at the herd level. The definition for being a case herd with "good welfare" was no score lying among the 10% worst in any of the nine welfare measurements. Twenty-eight of the 55 herds were cases according to this definition. As a second step, 65 potential welfare indicators, based on register data in a national dairy database, were identified by expert opinion. In the final step, the extent to which the suggested welfare indicators predicted farms' as having good welfare according to the stated definition was assessed. Moreover, the effect of combining in sequence a previously developed model that identified herds with poor welfare with the present model identifying herds with good welfare was investigated.
The final set of welfare indicators used to identify herds with good animal welfare included two fertility measures, cow mortality, stillbirth rate, mastitis incidence and incidence of feed-related diseases (including gastrointestinal disturbances but excluding paralyses and cramps). This set had a test sensitivity of correctly classifying herds with no score lying among the 10% worst of the nine welfare measurements of 96 %. However, the specificity of the test was only 56% indicating difficulties for the test to correctly classifying herds with one or more scores lying among the 10% worst. Combining the previously developed model with the present model, improved the welfare classification.
This study shows that pre-collected register data may be used to give approval to dairy farms with "good welfare" and that combining different sets of register data can improve the classification of herd welfare.
几乎所有北欧国家都有预先录制的奶牛场登记数据。这些数据库可用于研究目的，其中一个研究领域是动物福利。本研究的目的是调查预先录制的登记数据是否可用于识别福利良好的牛群，并调查是否可以结合多个数据集来更准确地区分福利良好的牛群和福利不足的牛群。
作为第一步，在 55 个随机选择的牛群中，对小牛、青年牛和奶牛进行了九项基于动物的测量，作为牛群福利分类的基础。被定义为“福利良好”的病例牛群的定义是，在任何九个福利测量中，没有得分位于 10%最差之列。根据这一定义，28 个牛群为病例牛群。作为第二步，通过专家意见，确定了基于全国奶牛数据库中登记数据的 65 个潜在福利指标。在最后一步，评估了建议的福利指标根据所陈述的定义预测农场具有良好福利的程度。此外，还研究了按顺序组合先前开发的识别不良福利牛群的模型和本识别良好福利牛群的模型的效果。
用于识别具有良好动物福利的牛群的最终福利指标集包括两个生育指标、奶牛死亡率、死产率、乳腺炎发病率和与饲料相关疾病的发病率（包括胃肠道疾病，但不包括瘫痪和抽筋）。该指标集的测试灵敏度为正确分类九个福利测量中得分位于 10%最差之列的牛群，准确率为 96%。然而，测试的特异性仅为 56%，表明该测试难以正确分类得分位于 10%最差之列的牛群。将先前开发的模型与本模型结合使用，改善了福利分类。
本研究表明，预先收集的登记数据可用于批准“福利良好”的奶牛场，并且结合不同的数据集可以提高牛群福利的分类。
