Zwygart Sibylle, Lutz Barbara, Thomann Beat, Stucki Dimitri, Meylan Mireille, Becker Jens
Clinic for Ruminants, Vetsuisse Faculty, University of Bern, Bern, Switzerland.
Centre for Proper Housing of Ruminants and Pigs, Federal Food Safety and Veterinary Office, Agroscope, Ettenhausen, Switzerland.
Front Vet Sci. 2024 Jul 17;11:1436719. doi: 10.3389/fvets.2024.1436719. eCollection 2024.
Welfare assessment protocols have been developed for dairy cows and veal calves during the past decades. One practical use of such protocols may be conducting welfare assessments by using routinely collected digital data (i.e., data-based assessment). This approach can allow for continuous monitoring of animal welfare in a large number of farms. It recognises changes in the animal welfare status over time and enables comparison between farms. Since no comprehensive data-based assessment for veal calves is currently available, the purposes of this review are (i) to provide an overview of single existing data-based indicators for veal calves and (ii) to work out the necessary requirements for data-based indicators to be used in a comprehensive welfare assessment for veal calves in Switzerland. We used the Welfare Quality Protocol (WQ) for veal calves and the Terrestrial Animal Health Code from the World Organisation of Animal Health for guidance throughout this process. Subsequently, routinely collected data were evaluated as data sources for welfare assessment in Swiss veal operations. The four WQ principles reflecting animal welfare, i.e., , ', ' and were scarcely reflected in routinely available data. Animal health, as one element of animal welfare, could be partially assessed using data-based indicators through evaluation of mortality, treatments, and carcass traits. No data-based indicators reflecting feeding, housing and animal behaviour were available. Thus, it is not possible to assess welfare in its multidimensionality using routinely collected digital data in Swiss veal calves to date. A major underlying difficulty is to differentiate between veal calves and other youngstock using routine data, since an identifying category for veal calves is missing in official Swiss databases. In order to infer animal welfare from routine data, adaptations of data collection strategies and animal identification are required. Data-based welfare assessment could then be used to complement on-farm assessments efficiently and, e.g., to attribute financial incentives for specifically high welfare standards accordingly.
在过去几十年里，已经为奶牛和犊牛制定了福利评估方案。此类方案的一个实际用途可能是通过使用常规收集的数字数据进行福利评估（即基于数据的评估）。这种方法可以对大量农场的动物福利进行持续监测。它能够识别动物福利状况随时间的变化，并实现农场之间的比较。由于目前尚无针对犊牛的全面基于数据的评估，本综述的目的是：（i）概述现有的犊牛单一基于数据的指标；（ii）确定在瑞士犊牛综合福利评估中使用基于数据的指标的必要要求。在整个过程中，我们以犊牛的福利质量协议（WQ）和世界动物卫生组织的《陆生动物卫生法典》为指导。随后，对常规收集的数据作为瑞士犊牛养殖中福利评估的数据源进行了评估。反映动物福利的四个WQ原则，即 、 、 和 ，在常规可得数据中几乎没有体现。动物健康作为动物福利的一个要素，可以通过评估死亡率、治疗情况和胴体特征，使用基于数据的指标进行部分评估。没有反映饲养、住房和动物行为的基于数据的指标。因此，迄今为止，利用瑞士犊牛常规收集的数字数据不可能对福利的多维度进行评估。一个主要的潜在困难是使用常规数据区分犊牛和其他幼畜，因为瑞士官方数据库中缺少犊牛的识别类别。为了从常规数据中推断动物福利，需要调整数据收集策略和动物识别方法。基于数据的福利评估随后可用于有效地补充农场评估，例如，相应地为特别高的福利标准给予经济激励。
