Quantification of behavioural variation among sheep grazing on pasture using accelerometer sensors

Abstract

Context. Monitoring the behaviour of animals can provide early warning signs of disease or indicate loss of appetite. Also, an understanding of the variation in behaviours among animals and their distributions is essential for meaningful statistical inference. Therefore, quantifying the variation of behaviours is of both biological and statistical interest. Aim. The objectives of this study were to determine the distributions and quantify the variation among animals with respect to the times spent grazing, ruminating, idling, walking, and licking. Methods. The activities of 147 (male = 67, female = 80) Merino lambs at 10-11 months of age on a commercial farm in Edenhope, Victoria, Australia were recorded for 26 days, using ActiGraph accelerometer sensors attached to the left side of the sheep's muzzle. The male and female sheep were kept in separate paddocks. A Support Vector Machine algorithm was used to differentiate sheep behaviour into six categories: grazing, ruminating, idling, walking, licking, and other activities. The distributions of behaviours were analysed using energy statistics-based tests and Generalised Additive Models for Location, Scale, and Shape (GAMLSS). Different distributions were compared using Akaike Information Criterion (AIC) values. Key results. Among the distributions that were considered, we found that times spent ruminating in both male and female sheep populations as well as idling in male sheep were best described by the skew exponential type 2 distribution. Grazing, walking and licking behaviours were best described by the Box-Cox t distribution. The distribution of time spent grazing was symmetrical and unimodal in males, and adequately modelled by a normal distribution, but the distribution in females had a prominent left skew. Also, we found that females typically grazed for a longer time than males. However, males spent more time ruminating than grazing. Conclusions. The time spent by the animal in each activity varied during the day. Within each population, the variation among animals in the time spent grazing was best described by a Box-Cox t distribution. Implications. This study has enhanced our understanding of grazing behaviour and will facilitate more appropriate analyses of the causes of variation among animals in grazing behaviour.

Bio-logging reveals heritable patterns of natural behaviours in sheep

“…The other high variance clusters are likely to represent behaviours such as walking and running. The roughly even split between high and lower movement behaviours is comparable with other studies [19] as is the time spent resting, ruminating, and grazing [20].…”

Rumination Detection in Sheep: A Systematic Review of Sensor-Based Approaches

“…Table 2 provides more information on these studies. Almasi et al [27] used ActiGraph (wGT3X-BT; ActiGraph LLC, Pensacola, FL, USA) sensors to study the distributions and variation in behaviors among sheep on a commercial farm with respect to the times spent grazing, ruminating, idling, walking, and licking. In a separate publication, Almasi et al [4] described that ActiGraph accelerometer sensors can be used to determine grazing and rumination activities of sheep, which has a potential application for breeding strategies.…”

“…The device is able to hold up to 4.0 GB of raw data. Almasi et al [27] used ActiGraph sensors embedded into halters and positioned at the left side of the muzzle of 10-11-month-old Merino sheep (45.8 ± 14 kg) to determine the distributions and quantify the variation among animals with respect to the times spent grazing, ruminating, idling, walking, and licking. The authors reported that some of the sensors fell off of the animals during the study, and some of them did not record the necessary information, without specifying the proportion of animals affected.…”

The repeatability and heritability of traits derived from accelerometer sensors associated with grazing and rumination time in an extensive sheep farming system

“…The pasture availability was found to be 1,500 kg/ha in the ewes' paddock and 2,000 kg/ha in the rams' paddock. The details of the sheep and their feeding management were described in Almasi et al (2022). In total, there were 160 sheep (female, n = 86; male, n = 74) with an average initial weight (± standard deviation) of 45.8 kg (± 14.0 kg) in our experiment.…”

“…Feed intake has also has been reported to have a positive genetic correlation with growth traits, despite large standard errors (Fogarty et al, 2009). However, sensor technology provides a rapid and accurate estimation of time spent on grazing, ruminating, and other behaviors under commercial conditions when animals graze on pasture (Gonzaĺez et al, 2015;Greenwood et al, 2017;Almasi et al, 2022;Sohi et al, 2022). In a study by Greenwood et al (2017), pasture intake in grazing cattle (n = 10) was estimated using an algorithm based on the time spent grazing.…”