Assessment of the multi-criteria evaluation system of the Welfare Quality® protocol for growing pigs

Abstract

Animal welfare has become an important subject of public and political debate, leading to the necessity of an objective evaluation system for on-farm use. As welfare is a multi-dimensional concept, it makes sense to use a multi-criteria aggregation system to obtain an overall welfare score. Such an aggregation system is provided by the Welfare Quality® Network. The present paper focusses on the assessment of the multi-criteria evaluation model included in the Welfare Quality® protocol for growing pigs in order to aggregate the animal-based indicators first to criteria, then to principles and finally to an overall welfare score. Specifically, the importance of the indicators on the overall assessment of growing pig farms is analysed in a given population which consisted of a total of 198 protocol assessments carried out on a sample of 24 farms in Germany. By means of partial least squares modelling, the influence of measures in the calculation procedure is estimated by calculation and interpretation of Variable Importance for Projection (VIP) scores. Variable Importance for Projection scores revealed some meaningful, unexpected influences as the multi-criteria evaluation model of Welfare Quality® aimed at avoiding interferences and double-counting. Some of these influences led to the assumption that some measures might have potential as iceberg indicators, whereas others showed lesser importance. Thus, feasibility can be gained by the deletion and special weighting of indicators according to their importance. Altogether, the study is an essential contribution to the further development of the Welfare Quality® protocols as well as the application of multi-criteria decision systems in the field of animal welfare science in general.

Application of a Protocol to Assess Camel Welfare: Scoring System of Collected Measures, Aggregated Assessment Indices, and Criteria to Classify a Pen

“…The second step of the proposed model consisted of calculations to obtain Partial Indices (PIs). Each PI was expressed on a scale of 0 (the worst situation) to 100 (the best situation), in agreement with the indices proposed in the literature for other animal species [14,17,19,25,38]. These PIs may be an effective tool to identify areas of concern and hazards, allowing the farmers to apply corrective actions for the improvement of their camels' welfare.…”

“…More standardized methods to aggregate the measures include a sum of ranks (the measures obtained in a farm have the same importance and are aggregated by summing them) and a weighted sum of scores (i.e., scores obtained on several measures by a farm are given different weights and summed). The main criticisms levelled at these methods are the following: they are complicated, and often lacking in the identification of welfare risk factors or in the suggestion of corrective actions [19,20]. A user-friendly methodology and interpretation of the data are important in a welfare assessment protocol.…”

Severity assessment in pigs after partial liver resection: evaluation of a score sheet

“…The observation of spontaneous behaviour is a widely used parameter for severity assessment. 23,24 But it is important to ensure that the observation of the spontaneous behaviour is done by well-trained personnel who are familiar with the species, 21 otherwise it will lead to high observer variability.…”

Pre-slaughter cattle welfare indicators for use in commercial abattoirs with voluntary monitoring systems: A systematic review

“…Increasing world trade associated with a growing demand for animal protein has increased the number of cattle raised, transported and slaughtered, also increasing welfare problems at various points in the supply chain (Miranda-de la Lama, 2013). As welfare is a multi-dimensional concept, it makes sense to use a multi-criteria aggregation system to assess it (Czycholl, Kniese, Schrader, & Krieter, 2017). Even though there are limitations to using CWI at slaughter plants, they could greatly improve handling by reducing stress and pain caused by poor management (Grandin, 2017).…”