Are automated sensors a reliable tool to estimate behavioural activities in grazing beef cattle?

Poulopoulou, I.; Lambertz, Christian; Gauly, Matthias

doi:10.1016/j.applanim.2019.04.009

Cited by 26 publications

(28 citation statements)

References 33 publications

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“… Werner et al (2018) also found that accelerometer-based detection of standing behavior was possible using the RumiWatch System sensor platform. Similar results were found by Poulopoulou et al (2019) evaluating the ability of a three triaxial accelerometer on predicting behavioral activities in grazing beef cattle. Although these studies all show that wearable technologies have promise as a means to classify standing behavior, the concordance correlation coefficient (CCC) to determine the accuracy between readings from the sensor and direct observations of existing evaluations is 0.88–0.97 ( Werner et al, 2018 ; Poulopoulou et al, 2019 ).…”

Section: Resultssupporting

confidence: 81%

“…Similar results were found by Poulopoulou et al (2019) evaluating the ability of a three triaxial accelerometer on predicting behavioral activities in grazing beef cattle. Although these studies all show that wearable technologies have promise as a means to classify standing behavior, the concordance correlation coefficient (CCC) to determine the accuracy between readings from the sensor and direct observations of existing evaluations is 0.88–0.97 ( Werner et al, 2018 ; Poulopoulou et al, 2019 ). Leveraging this more flexible research platform for sensor evaluation may enable the development of algorithms to more reliably classify standing behavior.…”

Section: Resultssupporting

confidence: 81%

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An open-source research tool to study triaxial inertial sensors for monitoring selected behaviors in sheep

Reis

Fuka

Easton

et al. 2020

Translational Animal Science

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The use of automated systems for monitoring animal behavior provides information on individual animal behavior and can be used to enhance animal productivity. However, advancement of this industry is hampered by technology costs, challenges with power supplies, limited data accessibility, and inconsistent testing approaches for confirming detection of livestock behaviors. Development of open-source research tools similar to commercially available wearable technologies may contribute to development of more efficient and affordable technologies. The objective of this study was to demonstrate an open-source, microprocessor-based sensor designed to monitor and enable differentiation among selected behaviors of adult wethers. The sensor was comprised of an inexpensive espressif ESP-32-WROOM-32 microprocessor with Bluetooth communication, a generic MPU92/50 motion sensor which contains a 3-axis accelerometer, 3 -axis magnetometer, and a 3-axis gyroscope, and a 5V rechargeable Lithium ion battery. The open source Arduino IDE software was used to program the microprocessor and to adjust the frequency of sampling, the data packet to send, and the operating conditions. For demonstration purposes, sensors were placed on 6 housed sheep for 3, 1 h increments with concurrent visual behavioral observation. Sensor readings (X-, Y-, and Z-axis) were summarized (mean and sd) within minute and compared to animal behavior observations (also on a by-minute basis) using a linear mixed-effect model with animal as a random effect and behavioral classifier as a fixed effect. This analysis demonstrated the basic utility of the sensor to differentiate among animal behaviors based on sensed data (P<0.001). Although substantial additional work is needed for algorithm development, power source testing, and network optimization, this open-source platform appears to be a promising strategy to research wearable sensors in a generalizable manner.

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Section: Resultssupporting

confidence: 81%

Section: Resultssupporting

confidence: 81%

An open-source research tool to study triaxial inertial sensors for monitoring selected behaviors in sheep

Reis

Fuka

Easton

et al. 2020

Translational Animal Science

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“…[37,38]. According to Poulopoulou et al [39], high correlations were confirmed for the activities feeding, ruminating, standing and lying. Significantly reduced motion activity was found in ketotic animals compared to healthy animals [12].…”

Section: Resultsmentioning

confidence: 90%

Relation of Subclinical Ketosis of Dairy Cows with Locomotion Behaviour and Ambient Temperature

Antanaitis

Juozaitienė

Televičius

et al. 2020

Animals

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Rumination time, chewing time and drinking time are indicators that can be assessed in case of cow disease. In this research, two groups of cows were formed: cows with subclinical ketosis (SCK; n = 10) and healthy cows (HG; n = 10). Behaviour such as walking activity, feeding time with head position up, feeding time with head position down, change of activity and average, minimal and maximal ambient temperature of cows were recorded by the RumiWatch noseband system (RWS; RumiWatch System, Itin+Hoch GmbH, Liestal, Switzerland). The RWS comprises a noseband halter with a built-in pressure sensor and a liquid-filled pressure tube. Data from each studied cow were recorded for 420 h. According to the results of our study, it was determined that cows diagnosed with subclinical ketosis showed a tendency to change their activity more frequently. Our data indicates that minimal and maximal ambient temperatures are related with SCK.

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“…Traditional methods of recording behaviour in animals can be time consuming, laborious and not always suitable for on-farm welfare assessment. The value of accelerometer technology is already well recognised for monitoring behaviour in adult cattle and has benefits over traditional methods of recording behaviour; in particular, the ability to record activity over long periods of time [43] and generate large amounts of data that would be impractical to generate using visual observation techniques [31]. This study has described and evaluated different methods of utilising raw data generated by a commercially available tri-axial accelerometer to detect play behaviour in very young calves without the need for extra software or advanced data manipulation.…”

Section: Discussionmentioning

confidence: 99%

“…Accelerometers have been evaluated as tools for identifying many different types of bovine behaviour including lying behaviours [30][31][32][33][34][35], locomotion [34,36,37], feeding/drinking behaviours [35,[38][39][40] and play behaviour [41,42]. Whilst accelerometer generated data have shown good correlation with visual observations for standing and lying behaviours in adult cows [21,32,35,43,44] and lying behaviours in calves [30,45], the reported correlation between accelerometer measurements and locomotor activity in calves is inconsistent. For example, Luu et al [41] reported a good correlation between the number of acceleration peaks and the duration of time engaged in running, jumping/kicking and walking (r = 0.96, 0.86 and 0.75, respectively), whereas Trénel et al [33] reported a low sensitivity (raw data sensitivity = 0.15; filtered data sensitivity = 0.22) for identifying movement in calves.…”

Section: Introductionmentioning

confidence: 99%

Use of a Tri-Axial Accelerometer Can Reliably Detect Play Behaviour in Newborn Calves

Gladden

Cuthbert

Ellis

et al. 2020

Animals

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Traditionally, the welfare assessment of farm animals has focused on health and production outcomes. Positive welfare is, however, not merely the absence of negative welfare and is an important part of a life worth living. Play behaviour is widely considered to be an indicator of positive emotions because it is a “luxury” behaviour. Direct visual observation is considered the most accurate method of behavioural analysis, but it is time consuming and laborious. There is increasing interest in the use of remote monitoring technology to quantify behaviour. We compared the data output (“motion index” (MI)) from a commercially available tri-axial accelerometer fitted to newborn dairy calves to video footage of the same calves, with a focus on play behaviour. The motion index values over 48 h were positively correlated with both the duration of play behaviour and the number of play bouts. The motion index threshold in each sample interval with the optimal sensitivity and specificity for the identification of play behaviour was MI ≥ 2.5 at a 1 min resolution (sensitivity (Se) = 98.0%; specificity (Sp) = 92.9%) and MI ≥ 24.5 at a 15 min resolution (Se = 98.0%; Sp = 89.9%), but these values consistently overestimated the overall proportion of sample intervals in which play was observed. The MI that best reflected the results obtained from visual one-zero sampling was MI ≥ 23 for 1 min intervals and MI ≥ 62 for 15 min intervals—this may therefore be the basis of a more conservative approach to the identification of play behaviour from accelerometer-generated data. Our results indicate that accelerometer-generated data can usefully indicate the amount of play behaviour shown by newborn calves for up to 48 h, providing an efficient method for identifying this important parameter in future work.

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Are automated sensors a reliable tool to estimate behavioural activities in grazing beef cattle?

Cited by 26 publications

References 33 publications

An open-source research tool to study triaxial inertial sensors for monitoring selected behaviors in sheep

An open-source research tool to study triaxial inertial sensors for monitoring selected behaviors in sheep

Relation of Subclinical Ketosis of Dairy Cows with Locomotion Behaviour and Ambient Temperature

Use of a Tri-Axial Accelerometer Can Reliably Detect Play Behaviour in Newborn Calves

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