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Psychology

Françoise Wemelsfelder, PhD

Welfare assessment

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Full-Text Articles in Organisms

Use Of Qualitative Behaviour Assessment As An Indicator Of Welfare In Donkeys, Michela Minero, Emanuela Dalla Costa, Francesca Dai, Leigh Anne Margaret Murray, Elisabetta Canali, Françoise Wemelsfelder Jun 2016

Use Of Qualitative Behaviour Assessment As An Indicator Of Welfare In Donkeys, Michela Minero, Emanuela Dalla Costa, Francesca Dai, Leigh Anne Margaret Murray, Elisabetta Canali, Françoise Wemelsfelder

Françoise Wemelsfelder, PhD

One of the objectives of the Animal Welfare Indicators project was to develop animal-based indicators to assess donkey welfare, including their emotional state. This study aimed to develop a fixed rating scale of Qualitative Behaviour Assessment (QBA) for donkeys, to evaluate the inter-observer reliability when applied on-farm, and to assess whether the QBA outcomes correlate to other welfare measures.

A fixed list of 16 descriptors was designed on the basis of a consultation in a focus group. The fixed list was then used by four trained observers to score nine 2 min videos of groups of donkeys owned by six …


Welfare Assessment: Correlations And Integration Between A Qualitative Behavioural Assessment And A Clinical/Health Protocol Applied In Veal Calves Farms, Marta Brscic, Françoise Wemelsfelder, Elena Tessitore, Flaviana Gottardo, Giulio Cozzi, Cornelis G. Van Reenen Jun 2016

Welfare Assessment: Correlations And Integration Between A Qualitative Behavioural Assessment And A Clinical/Health Protocol Applied In Veal Calves Farms, Marta Brscic, Françoise Wemelsfelder, Elena Tessitore, Flaviana Gottardo, Giulio Cozzi, Cornelis G. Van Reenen

Françoise Wemelsfelder, PhD

This study is aimed at finding correlations and possible integration among Qualitative Behavioural assessment (QBA) and a specific protocol of clinical/health evaluation. Both welfare assessment methods were based on direct animal observation and were applied in 24 Italian veal calves farms at 3 weeks (wks) of rearing. Principal component analysis (PCA) summarized 20 QBA descriptors on two main components (PC1 and PC2) with eigenvalues above 4 and explaining 29.6 and 20.3% of the variation respectively. PCA on residuals obtained after correcting for housing condition yielded highly similar results, indicating that the rearing environment of the calves was not an important …