Jenny Sneddon

Dr. Jenny Sneddon


Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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25 October 2022 in Animals
Verified
Journal Article
Open access
PDF file
NKNatasa Kleanthous
Natasa Kleanthous
AHAbir Jaafar Hussain
Abir Jaafar Hussain
JSJenny Sneddon
Jenny Sneddon
Wasiq KhanWasiq Khan
Wasiq Khan
Bilal KhanBilal Khan
Bilal Khan
PLPanos Liatsis
Panos Liatsis
Fencing in livestock management is essential for location and movement control yet with conventional methods to require close labour supervision, leading to increased costs and reduced flexibility. Consequently, virtual fencing systems (VF) have recently gained noticeable attention as an effective method for the maintenance and control of restricted areas for animals. Existing systems to control animal movement use audio followed by controversial electric shocks which are prohibited in various countries. Accordingly, the present work has investigated the sole application of audio signals in training and managing animal behaviour. Audio cues in the range of 125–17 kHz were used to prohibit the entrance of seven Hebridean ewes from a restricted area with a feed bowl. Two trials were performed over the period of a year which were video recorded. Sound signals were activated when the animal approached a feed bowl and a restricted area with no feed bowl present. Results from both trials demonstrated that white noise and sounds in the frequency ranges of 125–440 Hz to 10–17 kHz successfully discouraged animals from entering a specific area with an overall success rate of 89.88% (white noise: 92.28%, 10–14 kHz: 89.13%, 15–17 kHz: 88.48%, 125–440 Hz: 88.44%). The study demonstrated that unaided audio stimuli were effective at managing virtual fencing for sheep.

1 January 2014 in International Journal on Smart Sensing and Intelligent Systems
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Journal Article
Open access
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JSJenny Sneddon
Jenny Sneddon
Alex MasonAlex Mason
Alex Mason
Non-invasive methods for monitoring foraging choice in free ranging grazing animals are largely limited to accelerometers and video calibration. Acoustic data from a wireless microphone attached to the skull has been used to distinguish between resting and feeding bouts in free ranging cattle, sheep and goats. Similar data has been reported in restrained sheep presented with forage of differing dry matter content. We take these approaches further by using a small video camera attached to a halter in free range sheep, and software developed specifically for the analysis of animal sounds. Combined biting and mastication sounds allowed us to distinguish between foraged grasses and browsing activity, and non-foraging chewing activity in four sheep of differing body size and breed in the height of a UK summer for up to 8 hours.

4 August 2023
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Book Chapter
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JSJenny Sneddon
Jenny Sneddon