4.1 Article

Wireless sensor networks to study, monitor and manage cattle in grazing systems

期刊

ANIMAL PRODUCTION SCIENCE
卷 54, 期 10, 页码 1687-1693

出版社

CSIRO PUBLISHING
DOI: 10.1071/AN14368

关键词

behaviour; GPS; grazing livestock; live weight; remote sensing

资金

  1. Queensland Smart State

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Monitoring and management of grazing livestock production systems can be enhanced with remote monitoring technologies collecting information with high temporal and spatial detail. However, the potential benefits of such technologies have yet to be realised and challenges still exist with hardware, and data analysis and interpretation. The objective of this paper was to propose analytical methods and demonstrate the value of remotely collected liveweight (LW) and behaviour of beef cattle grazing tropical pastures. Three remote weighing systems were set up at the water troughs to capture LW of three groups of 20 animals for 341 days. LW data reflected short-term effects following the first rain event (>50 mm) at the end of the dry season, which resulted in LW losses of 22 +/- 8.8 kg of LW at a rate of -1.54 +/- 0.46 kg/day (n = 60). This period was followed by a peak daily LW change (LWC) of +2 kg/day. The remote weighing system also captured longer environmental effects related to seasonal changes in forage quality and quantity with highest LWC during the wet season and weight loss during the dry season. Effects of management on LW and LWC were observed as a result of moving animals to paddocks with more edible forage during the dry season when the negative trend in LWC was reversed after rotating animals. Behavioural monitoring indicated that resting and ruminating took place at camping sites, and foraging resulted in grazing hotspots. Remotely collected LW data captured both short-and long-term temporal changes associated with environmental and management factors, whereas remote monitoring collars captured the spatial distribution of behaviours in the landscape. Wireless sensor networks have the ability to provide data with sufficient detail in real-time making it possible for increased understanding of animal biology and early management interventions that should result in increased production, animal welfare and environmental stewardship.

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