Monitoring drinking behavior in bucket-fed dairy calves using an ear-attached tri-axial accelerometer: A pilot study

Roland, Leonie; Lidauer, Laura; Sattlecker, Georg; Kickinger, Florian; Auer, Wolfgang; Sturm, Valentin; Efrosinin, Dmitry; Drillich, M.; Iwersen, M.

doi:10.1016/j.compag.2018.01.008

Cited by 20 publications

(16 citation statements)

References 19 publications

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“…In this current study, the behaviour classification model for the neck-collar tri-axial accelerometer was more accurate than the ear-tag tri-axial accelerometer, with Cohen’s Kappa coefficient for the neck-collar deployment model being also superior to the ear-tag deployment. The substantial agreement between actual and model-predicted behaviour was higher in the present study than studies with dairy cows by Bikker et al [ 57 ] and dairy calves by Roland et al [ 16 ] who found 0.77 and 0.68 of Cohen’s kappa value for eating and drinking using an ear-attached accelerometer. The lower kappa coefficient for the ear-tag accelerometer compared to that for the neck-collar was affected by complex and repetitive ear movements.…”

Section: Discussioncontrasting

confidence: 64%

“…Recent investigations have reported that tri-axial accelerometers were capable of categorising oral and intake behaviours of ruminants such as suckling [ 12 ], ruminating, eating [ 13 ], grazing [ 14 ], chewing, biting [ 11 ], and drinking [ 15 ]. Apart from reducing observation time, the capability of accelerometers to discriminate feeding behaviours indicates the potential for developing algorithms to accurately predict feed intake [ 16 ]. Greenwood et al [ 17 ] formulated a simple algorithm to predict pasture intake by individual cattle using accelerometers and Williams et al [ 15 ] reported that accelerometers could be used to predict water intake of grazing cattle based on prediction of visiting frequency and duration per visit to the water trough.…”

Section: Introductionmentioning

confidence: 99%

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A Pilot Study Using Accelerometers to Characterise the Licking Behaviour of Penned Cattle at a Mineral Block Supplement

Simanungkalit

Barwick

Cowley

et al. 2021

Animals

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Identifying the licking behaviour in beef cattle may provide a means to measure time spent licking for estimating individual block supplement intake. This study aimed to determine the effectiveness of tri-axial accelerometers deployed in a neck-collar and an ear-tag, to characterise the licking behaviour of beef cattle in individual pens. Four, 2-year-old Angus steers weighing 368 ± 9.3 kg (mean ± SD) were used in a 14-day study. Four machine learning (ML) algorithms (decision trees [DT], random forest [RF], support vector machine [SVM] and k-nearest neighbour [kNN]) were employed to develop behaviour classification models using three different ethograms: (1) licking vs. eating vs. standing vs. lying; (2) licking vs. eating vs. inactive; and (3) licking vs. non-licking. Activities were video-recorded from 1000 to 1600 h daily when access to supplement was provided. The RF algorithm exhibited a superior performance in all ethograms across the two deployment modes with an overall accuracy ranging from 88% to 98%. The neck-collar accelerometers had a better performance than the ear-tag accelerometers across all ethograms with sensitivity and positive predictive value (PPV) ranging from 95% to 99% and 91% to 96%, respectively. Overall, the tri-axial accelerometer was capable of identifying licking behaviour of beef cattle in a controlled environment. Further research is required to test the model under actual grazing conditions.

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Section: Discussioncontrasting

confidence: 64%

Section: Introductionmentioning

confidence: 99%

A Pilot Study Using Accelerometers to Characterise the Licking Behaviour of Penned Cattle at a Mineral Block Supplement

Simanungkalit

Barwick

Cowley

et al. 2021

Animals

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“…However, analysis of variance and regression are commonly used to evaluate ingestive behavior; however, understanding a time series data on a mean implies loss of information about behavior pattern belonging to a circadian cycle. Thus, another method has been proposed to assess feeding behavior on ruminants with observations taken sequentially during a 24-hour period composing a circadian pattern (Roland et al, 2018;Ruuska, Kajava, Mughal, Zehner, & Mononen, 2016). This approach using time series data have been used to understand the relationship between different types of activities, states and causes of ingestive behavior (Fischer, Dutilleul, Deswysen, Dèspres, & Lobato, 2000) and their relationship with animal performance.…”

Section: Introductionmentioning

confidence: 99%

Ingestive behavior of dairy goats fed diets containing increasing levels of neutral detergent fiber and particle size using multivariate analysis

Schultz

Amaral

Glória

et al. 2019

Acta Sci. Anim. Sci.

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The purpose of this study was to evaluate the effect of interaction between increasing neutral detergent fiber content and particle sizes on ingestive behavior of dairy goats. Forty-eight lactating, multiparous Saanen and Alpine goats, with average milk production of 1.4 ±0.57 kg d -1 , around 60 th ±12 day of lactation were distributed in a 3 x 4 factorial completely randomized design. The diets consisted: three particles sizes (02, 05 or 15 cm) and four levels of neutral detergent fiber (34, 41, 49 or 57% NDFf) from forage (Tifton 85 hay). The ingestive behavior was monitored during 24 hours. A regression and a multivariate time series cluster analysis were performed. No interaction was found (p > 0.05) between treatments. Feeding time was different according to the particle size, having an increasing linear effect. Rumination and idle times were not affected (p > 0.05). The temporal feeding behavior was clustered into two groups according to the profile of particle size of the diet. Rumination peaks were randomly distributed with more intense activity before morning and afternoon meals. The increase in NDFf content in the diet did not change the ingestive behavior. The multivariate cluster analysis in a time series data is useful to interpret animal feeding behavior.

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“…In our study, we used the Smartbow system (SB; Smartbow GmbH), which consists of an accelerometer (3-dimensional) and location (2-dimensional) sensor fixed in an ear tag. Previous studies have evaluated the capabilities of the system to detect rumination (Reiter et al, 2018), predict calving (Krieger et al, 2017), detect estrus (Schweinzer et al, 2019), and monitor drinking events in calves (Roland et al, 2018). Additional studies have evaluated the location feature by focusing on the system's distance (in meters) accuracy in a cow barn (Wolfger et al, 2017), for dairy cows on pasture (Byrne et al, 2019), and for pigs maintained in a gestation stall (Will et al, 2017).…”

mentioning

confidence: 99%

Use of a real-time location system to detect cows in distinct functional areas within a barn

Chapa

Lidauer²,

Steininger³

et al. 2021

JDS Communications

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Cow location and time spent in relevant areas of the barn are important parameters that can be indicative of health and welfare status. Real-time location systems (RTLS) have the potential to measure these parameters on an individual level. We evaluated the ability of the Smartbow (Smartbow GmbH) RTLS to locate and measure the time cows spent in relevant areas of the barn. This work demonstrated that RTLS are capable of identifying individual cows in important areas of the barn and consequently are able to measure time budgets of cows. Highlights• The RTLS achieved high accuracy in locating cows in alleys, feed bunk and cubicles.• Location and time spent in important barn areas can be automatically determined and used as indicators of health. • The potential of combining RTLS with other sensors technologies was discussed.

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Monitoring drinking behavior in bucket-fed dairy calves using an ear-attached tri-axial accelerometer: A pilot study

Cited by 20 publications

References 19 publications

A Pilot Study Using Accelerometers to Characterise the Licking Behaviour of Penned Cattle at a Mineral Block Supplement

A Pilot Study Using Accelerometers to Characterise the Licking Behaviour of Penned Cattle at a Mineral Block Supplement

Ingestive behavior of dairy goats fed diets containing increasing levels of neutral detergent fiber and particle size using multivariate analysis

Use of a real-time location system to detect cows in distinct functional areas within a barn

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