Using Real-Time GNSS Tracking Tags to Monitor Alpaca Activity in an Australian Extensive Production System

Australian alpacas contribute to a developing alternative fibre industry with an increasing number of larger-scale enterprises requiring real-time management options. This study aimed to investigate the ability of GNSS real-time tracking tags to monitor alpaca herd behaviour in an extensive production system and assess their suitability as a future management tool. A total of 32 alpacas were fitted with collar-mounted GNSS tracking livestock tags, and an additional 32 alpacas were used as a control group without tags. Both Huacaya (n = 32) and Suri (n = 32) breeds were included. There was no effect of treatment on body condition score change (p = 0. 3648). Breed had a significant effect on distance travelled (p < 0.0184), with Suri alpacas travelling 1.03 (±0.058) km and Huacayas 0.9 (±0.058) km per day. Season significantly impacted the distance travelled each day (p< 0.0001), with alpacas moving a greater distance in winter and spring compared to summer and autumn. The alpacas displayed an increase in activity between 0600 and 1600, with the majority (60%) of their activity occurring during daylight hours. This study outlines normal paddock behaviour for extensively raised alpacas in Australia and showcases the potential for GNSS remote monitoring technology to be utilised as a management tool.

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Publication Details

Journal
Agriculture
Published
2025-08-29
DOI
https://doi.org/10.3390/agriculture15171839
Primary Topic
Smart Agriculture and AI
Type
article
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article

Using Real-Time GNSS Tracking Tags to Monitor Alpaca Activity in an Australian Extensive Production System

R. D. Bush, Evelyn Hall, Imogen Boughey
Agriculture
Smart Agriculture and AI
article

Using Real-Time GNSS Tracking Tags to Monitor Alpaca Activity in an Australian Extensive Production System

R. D. Bush, Evelyn Hall, Imogen Boughey
article en

Abstract

Australian alpacas contribute to a developing alternative fibre industry with an increasing number of larger-scale enterprises requiring real-time management options. This study aimed to investigate the ability of GNSS real-time tracking tags to monitor alpaca herd behaviour in an extensive production system and assess their suitability as a future management tool. A total of 32 alpacas were fitted with collar-mounted GNSS tracking livestock tags, and an additional 32 alpacas were used as a control group without tags. Both Huacaya (n = 32) and Suri (n = 32) breeds were included. There was no effect of treatment on body condition score change (p = 0. 3648). Breed had a significant effect on distance travelled (p < 0.0184), with Suri alpacas travelling 1.03 (±0.058) km and Huacayas 0.9 (±0.058) km per day. Season significantly impacted the distance travelled each day (p< 0.0001), with alpacas moving a greater distance in winter and spring compared to summer and autumn. The alpacas displayed an increase in activity between 0600 and 1600, with the majority (60%) of their activity occurring during daylight hours. This study outlines normal paddock behaviour for extensively raised alpacas in Australia and showcases the potential for GNSS remote monitoring technology to be utilised as a management tool.

AgricultureVol. 15(17)
The University of Sydney (AU)
Openalex Percentile: Top 83%
Smart Agriculture and AI
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