Abstract

Assessment of chicken welfare using camera surveillance of behaviour has great potential as a supplement to good stockmanship and as an aid to improving flock management. Suitable cameras are now readily available and the automated analysis of the lengthy video sequences from the cameras can be accomplished from statistical descriptors of the ‘optical flow’ patterns produced by flock movements. However, although optical flow measures have been shown to correlate with welfare outputs such as mortality, hockburn, pododermatitis and gait score, it is not yet clear how the optical flow algorithms achieve this – i.e. what variation in behaviour of individuals the cameras are picking up.The aim of this paper is to clarify the relationship between optical flow, behaviour and welfare by correlating optical flow (mean, variance, skew and kurtosis) taken from 15min video sequences of commercial broilers at 25 days of age with bird behaviour recorded from the same sequences and with welfare measures from the same flocks (n=24). There were no significant between-flock correlations (r2) between mean optical flow and % birds walking, % sitting/lying, walking speed or an estimate of the numbers of birds walking continuously for 10s. or longer (p>0.02, 2-tailed). Mean % birds walking was, however, significantly and negatively correlated with hock burn (r2=−0.44 p<0.05). Skew and kurtosis of optical flow showed no correlation with % birds walking, % birds sitting/lying or with walking speed (p>0.02) but were significantly and positively correlated with the number of birds walking continuously for at least 10s (for skew, r2=0.51, p<0.01; for kurtosis, r2=0.46, p<0.05).We conclude that there is no simple connection between optical flow and behaviour or between the behaviour recorded here and mortality, hockburn, pododermatis and gait score. However, reduced numbers of birds walking continuously for 10s or more appear to be responsible for the increased kurtosis of flow in flocks with higher (less good) gait scores. Optical flow measures correlate more strongly these welfare outcomes than any single behavioural measure.

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