Academic Journal

PSXI-8 Comparison of Spectral and Motion Sensing for Grazing Behavior Determination in Extensive Systems

التفاصيل البيبلوغرافية
العنوان: PSXI-8 Comparison of Spectral and Motion Sensing for Grazing Behavior Determination in Extensive Systems
المؤلفون: Wright, Ryan, Simcik, Charleez, White, Robin R
المصدر: Journal of Animal Science ; volume 101, issue Supplement_3, page 596-597 ; ISSN 0021-8812 1525-3163
بيانات النشر: Oxford University Press (OUP)
سنة النشر: 2023
الوصف: There is a need to classify eating behaviors of grazing animals to better understand time budgets and intake levels of extensively managed livestock. The objective of this work was to compare spectral and motion-based sensing for classification of animal grazing versus standing behaviors within extensive production systems. The sensor was an open-source setup with a TTGO-T-Beam microprocessor (Shenzhen Xin Yuan Electronic Technology Co, China), soldered with an AS7265x Spectral Triad (SparkFun Electronics, Niwot, CO) and generic 9 degree of freedom inertial motion unit. The sensors were attached to a mesh face mask and placed on 5 horses for 10 minutes of data collection. Within the data collection period, animals were allowed to graze for 5 minutes, and required to stand for 5 minutes. The order of grazing and standing was randomized among animals. Data were collected by the microprocessor at 100 hertz and averaged over a 20 second period. Average data were transmitted via long range radio (LoRa) to a base station. Data were matched by timestamp to ground truth observations of animal standing vs grazing behaviors. A random forest algorithm was used to explore predicting animal grazing versus standing behaviors based on motion data (average pitch, yaw, and roll of animals over the experimental period) individually, based on the top features selected from the spectral data individually, or based on all collected data together. The model using the motion data only returned an out of bag estimated error rate of 26.5%. The model using the top features selected from the spectral data yielded a much lower out of bag estimated error rate (8.82%), which was not improved by leveraging all data together. By comparing the spectral data with GPS coordinates attached to each observation, we were able to clearly distinguish the spatial area used for grazing compared with that used for standing. One potential impact of this preliminary exploration is in low-cost, low-power, more precise behavioral classification for ...
نوع الوثيقة: article in journal/newspaper
اللغة: English
DOI: 10.1093/jas/skad281.694
الاتاحة: https://doi.org/10.1093/jas/skad281.694
https://academic.oup.com/jas/article-pdf/101/Supplement_3/596/52958683/skad281.694.pdf
Rights: https://academic.oup.com/pages/standard-publication-reuse-rights
رقم الانضمام: edsbas.F836B448
قاعدة البيانات: BASE