The use of animal sensor data for predicting sheep metabolisable energy intake using machine learning

H. Suparwito; D.T. Thomas; K.W. Wong; H. Xie; S. Rai

doi:10.1016/j.inpa.2020.12.004

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The use of animal sensor data for predicting sheep metabolisable energy intake using machine learning

Journal article

Peer reviewed

The use of animal sensor data for predicting sheep metabolisable energy intake using machine learning

H. Suparwito, D.T. Thomas, K.W. Wong, H. Xie and S. Rai

Information Processing in Agriculture, Vol.8(4), pp.494-504

2021

DOI: https://doi.org/10.1016/j.inpa.2020.12.004

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Abstract

The use of sensors for monitoring livestock has opened up new possibilities for the management of livestock in extensive grazing systems. The work presented in this paper aimed to develop a model for predicting the metabolisable energy intake (MEI) of sheep by using temperature, pitch angle, roll angle, distance, speed, and grazing time data obtained directly from wearable sensors on the sheep. A Deep Belief Network (DBN) algorithm was used to predict MEI, which to our knowledge, has not been attempted previously. The results demonstrated that the DBN method could predict the MEI for sheep using sensor data alone. The mean square error (MSE) values of 4.46 and 20.65 have been achieved using the DBN model for training and testing datasets, respectively. We also evaluated the influential sensor data variables, i.e., distance and pitch angle, for predicting the MEI. Our study demonstrates that the application of machine learning techniques directly to on-animal sensor data presents a substantial opportunity to interpret biological interactions in grazing systems directly from sensor data. We expect that further development and refinement of this technology will catalyse a step-change in extensive livestock management, as wearable sensors become widely used by livestock producers.

Details

Title: The use of animal sensor data for predicting sheep metabolisable energy intake using machine learning
Authors/Creators: H. Suparwito (Author/Creator) - Murdoch University
D.T. Thomas (Author/Creator) - Commonwealth Scientific and Industrial Research Organisation
K.W. Wong (Author/Creator) - Murdoch University
H. Xie (Author/Creator) - Murdoch University
S. Rai (Author/Creator) - Murdoch University
Publication Details: Information Processing in Agriculture, Vol.8(4), pp.494-504
Publisher: Production and hosting by Elsevier B.V. on behalf of KeAi.
Identifiers: 991005544600807891
Murdoch Affiliation: School of Information Technology
Language: English
Resource Type: Journal article

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