Application of the Welfare Quality ® protocol to assess growing pigs kept under intensive conditions in Spain

• Published in: Journal of veterinary behavior Vol. 6; no. 2; pp. 138 - 149
• Main Authors: Temple, Déborah, Dalmau, Antoni, Ruiz de la Torre, José L., Manteca, Xavier, Velarde, Antonio
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.03.2011
• Subjects: animal welfare; animal-based measures; farm; farms; growing pig; swine; welfare assessment system; Welfare Quality; Spain; Welfare Quality; farm; growing pig; animal-based measures; animal welfare; welfare assessment system
• ISSN: 1558-7878
• DOI: 10.1016/j.jveb.2010.10.003

This study is a first step toward the validation of the Welfare Quality ® protocol for assessing welfare of growing pigs kept on farms. The feasibility and sensitivity of the entire protocol was evaluated on 30 conventional farms in Spain, and a methodology to identify farms with particular welfare problems was proposed. A total of 64,496 pigs were assessed on the basis of 12 criteria related to the following 4 welfare principles: good feeding, housing, health, and appropriate behavior. Good feeding, housing, and health measures were scored at the pen- or individual-level using a 3-point scale ranging from 0 (good welfare) to 2 (poor or unacceptable). Appropriate behavior was assessed by scan sampling of social and exploratory behavior, qualitative behavior assessment, and a human–animal relationship test. The mean time taken for performing the full protocol was 6 hours and 20 minutes ± 51 minutes per visit. The between-farm variability of moderate and severe bursitis, presence of manure on less than 50% of the body surface, expression of positive and negative social behaviors, and exploration helped in the assessment of discrimination among farms. However, other animal-based measures, especially the ones related to the good health principle, presented very little variation that could be used to differentiate among farms. For each animal-based measure, confidence limits were estimated so as to make statistical inferences at the population level. This methodology could be useful to identify farms with poor welfare conditions.