Thanks to repetition, dustbathing detection can be automated combining accelerometry and wavelet analysis

FONSECA, ROCIO GUADALUPE; MARÍA CANDELARIA BOSCH; FLORENCIA CECILIA SPANEVELLO; MARIA VICTORIA DE LA FUENTE; MARIN, RAUL H.; LUCAS BARBERIS; JACKELYN M. KEMBRO; ANA GEORGINA FLESIA

ETHOLOGY

WILEY-BLACKWELL PUBLISHING, INC

Lugar: Londres; Año: 2024

0179-1613

Birds from at least a dozen orders engage in dustbathing, including Galliformes. Dustbathing is generally considered a behavioural need for poultry. It involves a precise and orderly sequence of movements repeated over time. The most characteristic movement involves tossing the dust with the wings and undulating the body beneath the dust shower. Thus, repetitive changes in body position during dustbathing could be automatically detected through data processing of body-mounted accelerometer recordings. The approach was tested in 13 adult male Japanese quail (Coturnix japonica) fitted with a body mounted triaxial accelerometer. Behaviour was video recorded for at least 6 hours. Observations showed that when the animal lies on its left- or right-side during dustbathing, the lateral (swaying) component of the acceleration vector adopts values of +1 or -1, respectively. Analysis shows that the bird repeats these shifts in body position every 25 to 60 seconds. The wavelet analysis (i.e complex Morlet continuous wavelet transform) detected this oscillatory behaviour within the time series as higher power values. This characteristic was used to automate the detection of dustbathing events, for which a threshold value for the maximum power value estimated was established for the corresponding range of scales between 25-60s. The overall general accuracy of this classification method for dustbathing detection was 80%, with individual variations falling within the range of 66-100%. Lastly, an example of the potential of this method in the study of temporal dynamics, such as daily rhythms of dustbathing, is provided. Our results show that combining accelerometry and wavelet analysis could be useful for the assessment of intra- and inter-individual variability in dustbathing dynamics over long-term studies, even within large complex environments, such as natural habitats or breeding facilities. Moreover, this approach could open doors for future in-depth studies exploring the relationship between dustbathing and poultry welfare.