Quantifying the frequency and volume of urine deposition by grazing sheep using tri-axial accelerometers

Marsden, Karina A.; Lush, Lucy; Holmberg, J. Anders; Whelan, Mick; Webb, Sophie; King, Andrew J.; Wilson, Rory P.; Jones, Davey L.; Charteris, Alice F.; Cardenas, L. M.; Chadwick, David R.

doi:10.1016/j.animal.2021.100234

Cited by 5 publications

(3 citation statements)

References 24 publications

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“…The neck-mounted device had the best results (90% of accuracy). Various sensors were also evaluated in recording some specific behaviors-for instance, urination events-with an accurate estimation rate of 100% [58], or lameness with three different placements (leg, ear, and neck), with the best results (87% of accuracy) for the leg deployment [13].…”

Section: Sheep Activity and Behaviormentioning

confidence: 99%

“…Cont. Intensive system with constant access to pasture United States The diseases had negative effects on ruminating and walking [96] Rotational grazing system Australia 24 h before the symptoms, heifers moved less [12] Pasture-based Germany Associations found between sensor behavior traits and monitored cow behavior [48] Pedometer Individual pens ( Wales 100% accuracy for urination events [58] Australia Accuracy was best (87%) for the leg deployment [13] Pasture-based Australia Ear-mounted sensor was the most accurate with 86% to 95% [56] Semi-improved pasture for the 1st study and a small pen in the 2nd study Australia Grazing behavior was the easiest to detect [105] Pasture-based but they were gradually removed from pasture…”

Section: United Statesmentioning

confidence: 99%

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Application of Precision Technologies to Characterize Animal Behavior: A Review

Hlimi,

El Otmani,

Elame

et al. 2024

Animals

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This study aims to evaluate the state of precision livestock farming (PLF)’s spread, utilization, effectiveness, and evolution over the years. PLF includes a plethora of tools, which can aid in a number of laborious and complex tasks. These tools are often used in the monitoring of different animals, with the objective to increase production and improve animal welfare. The most frequently monitored attributes tend to be behavior, welfare, and social interaction. This study focused on the application of three types of technology: wearable sensors, video observation, and smartphones. For the wearable devices, the focus was on accelerometers and global positioning systems. For the video observation, the study addressed drones and cameras. The animals monitored by these tools were the most common ruminants, which are cattle, sheep, and goats. This review involved 108 articles that were believed to be pertinent. Most of the studied papers were very accurate, for most tools, when utilized appropriate; some showed great benefits and potential.

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Section: Sheep Activity and Behaviormentioning

confidence: 99%

Section: United Statesmentioning

confidence: 99%

Application of Precision Technologies to Characterize Animal Behavior: A Review

Hlimi,

El Otmani,

Elame

et al. 2024

Animals

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“…Although not yet commercially available in the agricultural industry, the use of accelerometers on sheep in experimental settings has increased in recent years (Fogarty et al, 2018) and has been used to detect behavioural states in ewes including grazing, resting, lying, standing, walking and ruminating (Alvarenga et al, 2016;Giovanetti et al, 2017;le Roux et al, 2017;Barwick et al, 2018b;Mansbridge et al, 2018;Walton et al, 2018 and many more). More specific applications have included the identification of urination events (Lush et al, 2018;Marsden et al, 2021), detection of parturition (Fogarty et al, 2020b(Fogarty et al, , 2021, posture discrimination (Radeski and Ilieski, 2017;Fogarty et al, 2020a) and lameness prediction (Al-Rubaye et al, 2018;Barwick et al, 2018a;Kaler et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Classifying the posture and activity of ewes and lambs using accelerometers and machine learning on a commercial flock

Price

Langford

Fawcett

et al. 2022

Applied Animal Behaviour Science

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A tri‐axial acceleration‐based behaviour template for translocated birds: the case of the Asian houbara bustard

Chopra,

Wilson,

Shepard

et al. 2024

Wildlife Biology

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Understanding the behaviours and time budgets of translocated animals post‐release has the potential to improve rearing and release protocols, and therefore survival rate. Otididae (bustards) inhabit open landscapes across the Middle East and Asia, are highly mobile on the ground and have similar lifestyles and body plans. The Asian houbara Chlamydotis macqueenii is a bustard of conservation concern inhabiting the Middle East to Central Asia and is frequently reared in captivity for population management. We deployed tri‐axial accelerometers on 20 captive Asian houbaras in two seasons to catalogue basic behaviours, provide a template applicable to other bustard species and examine seasonal differences in behaviour. We created Boolean algorithms to define the following behaviours using raw acceleration data and derived metrics: stationary, eating/drinking and locomotion. We used video recordings to cross‐validate the algorithms, yielding recalls from 95 to 97%, and precisions between 97 and 98%. Houbaras spent significantly more time ‘stationary' and less time on ‘locomotion' in summer (June) compared to spring (March). Simple Boolean algorithms proved useful in identifying several behaviours and have the potential to be applicable to other bustard species, in captivity and in the wild post‐release.Keywords: accelerometer, animal behaviour, Asian houbara bustard, captive breeding, conservation translocation

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Quantifying the frequency and volume of urine deposition by grazing sheep using tri-axial accelerometers

Cited by 5 publications

References 24 publications

Application of Precision Technologies to Characterize Animal Behavior: A Review

Application of Precision Technologies to Characterize Animal Behavior: A Review

Classifying the posture and activity of ewes and lambs using accelerometers and machine learning on a commercial flock

A tri‐axial acceleration‐based behaviour template for translocated birds: the case of the Asian houbara bustard

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