A sensor-based solution to monitor grazing cattle drinking behaviour and water intake
Autor: | Greg Bishop-Hurley, Dave L. Swain, Lauren R. Williams, Steven T. Moore |
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Rok vydání: | 2020 |
Předmět: |
0106 biological sciences
Drinking behaviour Water flow Ear tag Forestry 04 agricultural and veterinary sciences Horticulture Beef cattle Trough (economics) Accelerometer 01 natural sciences Computer Science Applications Animal science Duration (music) Grazing 040103 agronomy & agriculture 0401 agriculture forestry and fisheries Environmental science Agronomy and Crop Science 010606 plant biology & botany |
Zdroj: | Computers and Electronics in Agriculture. 168:105141 |
ISSN: | 0168-1699 |
DOI: | 10.1016/j.compag.2019.105141 |
Popis: | The aim of the study was to bring together a combination of stationary (Radio Frequency IDentification (RFID), water flow meter) and animal-attached (accelerometer) sensors in an automated approach to record beef cattle drinking behaviour and herd water intake in grazing systems. An experiment was conducted to collect and validate data from the behaviour monitoring system. A water trough located in an enclosed water point was equipped with a water flow meter. The water point entry and exit gates were each fitted with a RFID panel reader. The eight beef heifers that grazed the experimental site wore a RFID ear tag in the right ear and a motion sensing neck collar that contained a triaxial accelerometer. The heifers had ad libitum access to the water point at all times. Sensor data and video observations were recorded over four consecutive weeks. When operational, the RFID readers correctly recorded 95% (94/99) of heifer movements in and out of the water point and were correlated (r = 0.99) to observed entry and exit times. Volumes of water recorded by the water meter were correlated (r = 0.99) to measured water volumes taken from the trough’s inlet and from water in the trough while under the control of a float valve. An algorithm was developed to classify drinking using accelerometer measures of head-neck position, activity and movement frequency. The accelerometer algorithm detected 94% (98/104) of drinking events that were greater than 10 s in duration (F1 score = 77%) and was correlated (r = 0.84) to the observed duration of drinking events. Differences between observed and predicted estimates of the number of drinking events that were greater than 10 s in duration (1.6 ± 1.1 vs. 2.0 ± 1.8, respectively) and the time spent drinking (45.8 ± 24.1 vs. 43.1 ± 42.8, respectively) per heifer visit to the water yard were not significant (p > 0.05). The approach is considered reliable for recording a number of behavioural measures including the number, duration and frequency of visits per animal to a water point, the number and duration of drinking events per animal visit and the time each animal spends drinking. |
Databáze: | OpenAIRE |
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