Please use this identifier to cite or link to this item:
https://hdl.handle.net/1959.11/56616
Title: | On the Deployment of Sensor-Based Technologies for Monitoring Supplement Intake Behaviours in Grazing Cattle-dataset | Contributor(s): | Simanungkalit, Gamaliel (creator) ; Hegarty, Roger (supervisor) | Publication Date: | 2022-02-18 | DOI: | 10.25952/ptrr-w496 | Handle Link: | https://hdl.handle.net/1959.11/56616 | Related Research Outputs: | https://hdl.handle.net/1959.11/56615 | Abstract/Context: | The dataset consists of a collection of radio-frequency identification (RFID) system and accelerometer datasets from five experimental studies in grazing beef cattle. The RFID system was integrated into an automatic supplement feeder for monitoring the presence of individual grazing cattle when accessing block supplement provided through the feeder platform. Each individual cattle were fitted with an ear-tag accelerometer for identifying licking behaviour at the block supplement. The RFID data were collected using the structured query language (SQL) while the accelerometer data were downloaded using a proprietary software (OmGUI, Axivity Ltd, Newcastle Helix, Newcastle upon Tyne, UK). | Publication Type: | Dataset | Fields of Research (FoR) 2020: | 310901 Animal behaviour 300303 Animal nutrition 320907 Sensory systems |
Socio-Economic Objective (SEO) 2020: | 100401 Beef cattle | Keywords: | Block supplement Radio-Frequency identification Accelerometer Licking behaviours Grazing cattle |
Location: | Armidale, New South Wales, Australia | HERDC Category Description: | X Dataset | Project: | On the Deployment of Sensor-Based Technologies for Monitoring Supplement Intake Behaviours in Grazing Cattle | Dataset Managed By: | Gamaliel Simanungkalit | Rights Holder: | Gamaliel Simanungkalit | Dataset Stored at: | University of New England | Primary Contact Details: | Gamaliel Simanungkalit - gamasimanungkalit@gmail.com | Dataset Custodian Details: | Gamaliel Simanungkalit - gamasimanungkalit@gmail.com |
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Appears in Collections: | Dataset School of Environmental and Rural Science |
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