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Ingestive Behaviour Activities Based on Bioacoustic Signals in Grazing Cattle

Ingestive Behaviour Activities Based on Bioacoustic Signals in Grazing Cattle

Guilherme Augusto Defalque, Ricardo Santos, Victor Leonardo Yoshimura, Fabiana Villa Alves
Copyright: © 2020 |Volume: 11 |Issue: 4 |Pages: 15
ISSN: 1947-3192|EISSN: 1947-3206|EISBN13: 9781799806967|DOI: 10.4018/IJAEIS.2020100105
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MLA

Defalque, Guilherme Augusto, et al. "Ingestive Behaviour Activities Based on Bioacoustic Signals in Grazing Cattle." IJAEIS vol.11, no.4 2020: pp.69-83. http://doi.org/10.4018/IJAEIS.2020100105

APA

Defalque, G. A., Santos, R., Yoshimura, V. L., & Alves, F. V. (2020). Ingestive Behaviour Activities Based on Bioacoustic Signals in Grazing Cattle. International Journal of Agricultural and Environmental Information Systems (IJAEIS), 11(4), 69-83. http://doi.org/10.4018/IJAEIS.2020100105

Chicago

Defalque, Guilherme Augusto, et al. "Ingestive Behaviour Activities Based on Bioacoustic Signals in Grazing Cattle," International Journal of Agricultural and Environmental Information Systems (IJAEIS) 11, no.4: 69-83. http://doi.org/10.4018/IJAEIS.2020100105

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Abstract

This work focuses on the development of an autonomous, electronic platform based on bioacoustic techniques to monitor animal sounds related to ingestive activities and sub-activities in beef cattle. The authors have developed an electronic platform that leverage the usage of applications to predict health and welfare conditions based on the bioacoustic signals. The platform architecture is comprised of electronic subsystems covering the signal acquiring and filtering; sampling, processing, data storage system; and the coupling of the electronic and computing. The platform is coupled to the animal's halter so that the electronic system is in a case on the animal's forehead. Experiments were performed on grazing cattle (Nelore breed) in three field tests. The system was fully able to acquire, process, and store the animal's bioacoustic sounds. The authors used an audio file processing software to identify ingestive activities such as grazing, rumination, and idle periods. The results, based on the signal waveform, achieved high accuracy when compared to the visual monitoring method.