4.5 Article

Are automated sensors a reliable tool to estimate behavioural activities in grazing beef cattle?

Journal

APPLIED ANIMAL BEHAVIOUR SCIENCE
Volume 216, Issue -, Pages 1-5

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.applanim.2019.04.009

Keywords

Feeding and locomotion behaviour; Accelerometer; Direct observation; Beef; Grazing

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The use of automated sensors, that record feeding and locomotion behaviour in livestock, become more and more prominent, for example for the early detection of diseases in dairy cows. Their application may be also significant in extensive beef cattle production systems, where there is an infrequent farmer-to-animal contact. The aim of the present study was to determine the ability of a three dimensions accelerometer, compiled by a halter and a pedometer, to accurately discriminate and estimate behavioural activities in grazing beef cattle using direct observations (DO) as the golden standard. Eight beef cattle grazing in a vineyard were used in the present study, six animals were at the age of one year (283 +/- 42 kg), and two above two years of age (643 +/- 35 kg). The animals were equipped with halters and pedometers for an experimental period of 8 consecutive days. During that period, DO were also performed for 6 days for 6 h per day to estimate the accuracy of the sensors to correctly define and determine feeding, ruminating, drinking, walking, standing and lying. The instantaneous scan sampling technique with 10-minute intervals was used to record the mentioned behavioural parameters. Spearman correlation coefficients between accelerometer data and DO were calculated for each behavioural activity. Correlation coefficients (r(s)) between accelerometers and DO for feeding, ruminating, standing and lying were high (r(s) > 0.68), while for drinking and walking they were moderate and weak, respectively. In conclusion, the use of sensors is a promising method to predict feeding, ruminating, standing and lying behaviours of grazing beef cattle, while further research is needed to improve their ability to accurately estimate all behavioural activities and possibly evaluate their further use as health indicators.

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