Quantitative assessment of the effects of space allowance, group size and floor characteristics on the lying behaviour of growing-finishing pigs
- PMID: 22444133
- DOI: 10.1017/S1751731109991613
Quantitative assessment of the effects of space allowance, group size and floor characteristics on the lying behaviour of growing-finishing pigs
Abstract
To obtain quantitative information that can be later used in animal welfare modelling, the relationship between the lying behaviour of growing-finishing pigs (initial body weight (BW) between 19 and 87 kg) and different factors related to the housing conditions, with a potential negative effect on their welfare, was studied by means of a meta-analytical approach. Data from 22 experiments reported in 21 scientific publications were collected. The space allowance, expressed on an allometric basis by means of a k-value (m2/BW0.667), the group size (n) and the floor characteristics (fully and partly slatted v. non-slatted floor), as well as their significant two-way interactions were used as fixed effects, and the experiment was used as a random factor to take into account the interexperiment effect. Further regression analyses were performed on the predicted values of observations in order to improve the adjustment of data. A significant quadratic relationship was established between space allowance (k-value, P < 0.05; squared k-value, P < 0.01) and the percentage of time spent lying. A significant interaction between the k-value and the floor type was also found (P < 0.05), showing that the relationship between space allowance and lying behaviour is affected by the presence or absence of slats. Threshold k-values were obtained using broken-line analyses, being about 0.039 for slatted floors and almost double for non-slatted floors. Compared to other studies, these values suggest that the ability to rest as space availability decreases may be compromised before a reduced performance becomes apparent. Group size did not show a significant effect. Additional information should be added to the model, as further data become available, to adjust the proposed parameters as well as to try to include the effect of other important aspects such as that of ambient temperature.
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