ArticleSensors (Basel, Switzerland)2024
A New Approach to Recording Rumination Behavior in Dairy Cows.
Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Detection of Chewing Strokes from Jaw Movement Signals in Dairy Cows Using a Nose-Mounted Accelerometer.Sensors (Basel, Switzerland) · 2026Article
- Robust Automated Monitoring of Dairy Cow Rumination via Improved YOLOv11 and BoT-SORT in Complex Environments.Animals : an open access journal from MDPI · 2026Article
- Novel OA-ICOS Sensor for Real-Time Quantification of Enteric Methane from Ruminants.Sensors (Basel, Switzerland) · 2026Article
- Non-contact detection of post-regurgitation deep inhalation in calves using infrared thermography and deep learning-based nostril segmentation.BMC veterinary research · 2026Article
- Artificial Intelligence and Circadian Thresholds for Stress Detection in Dairy Cattle.Sensors (Basel, Switzerland) · 2025Article
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Authors and funding
5 authors.
Funding
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Abstract
Rumination behavior in cattle can provide valuable information for monitoring health status and animal welfare, but continuous monitoring is essential to detect changes in rumination behavior. In a previous study validating the use of a respiration rate sensor equipped with a triaxial accelerometer, the regurgitation process was also clearly visible in the pressure and accelerometer data. The aim of the present study, therefore, was to measure the individual lengths of rumination cycles and to validate whether the sensor data showed the same number of regurgitations as those counted visually (video or direct observation). For this purpose, 19 Holstein Friesian cows equipped with a respiration rate sensor were observed for two years, with a focus on rumination behavior. The results showed a mean duration of 59.27 ± 9.01 s (mean ± SD) per rumination cycle and good agreement (sensitivity: 99.1-100%, specificity: 87.8-95%) between the two methods (sensor and visual observations). However, the frequency of data streaming (continuously or every 30 s) from the sensor to the data storage system strongly influenced the classification performance. In the future, an algorithm and a data cache will be integrated into the sensor to provide rumination time as an additional output.
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Registered trials
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