Evaluation of an activity and rumination monitor in dairy cattle grazing two types of forages

Abstract

The aim of the present study was to evaluate the accuracy of a newer version of an activity- and rumination-monitoring system by comparison against direct visual observations, for the following three different types of behaviour: grazing, resting (described as lying or standing idle) and ruminating for cows grazing either annual ryegrass or chicory-based swards. Eight non-lactating Holstein–Friesian cows were fitted with the sensor tags, and grazed on annual ryegrass pasture for a target consumption of 10 kg DM ryegrass/cow.day for 7 days. The experiment was then repeated with cattle offered a similar allowance of chicory. Observations were conducted by two trained observers in two observation periods each day, to capture the above described behaviours. In each period, electronic behavioural measurements were recorded continuously by the sensors, while visual observations were also continuous (during observation periods), and the two datasets were matched. On average, each cow was visually observed for 87.2 min/day. For each behavioural state (at 1-min intervals, n = 6963), probability of agreement, sensitivity, specificity and positive predicted value were determined for grazing as 98%, 98.3%, 97.3% and 98.9% respectively, for resting as 80%, 77.5%, 99.1% and 92.9% and for ruminating as 87%, 86.9%, 98.4% and 90.68%. Concordance correlation coefficient (CCC) and Pearson correlations (r) were used to investigate the relationships between visual observations and data generated from the tags. Different behaviours were analysed separately. Significant correlations were found for the three behaviours (grazing: CCC = 0.99, r = 0.99; resting: CCC = 0.95, r = 0.97; ruminating: CCC = 0.80, r = 0.80), with no differences detected between the two forages. We conclude that, under the conditions of the present study, the activity- and rumination-monitoring system tag measured grazing, resting and ruminating behaviours with high accuracy on the basis of comparison to visual observations.

Validation of an Accelerometer Sensor-Based Collar for Monitoring Grazing and Rumination Behaviours in Grazing Dairy Cows

“…Moreover, it has been suggested by previous studies that dry matter intake (DMI) from grazed herbage is regulated by the time spent grazing and intake rate [ 5 , 6 , 7 ]. Similarly, rumination has been associated with nutrition and health in dairy cows [ 8 , 9 ] Thus, measuring grazing and rumination behaviours can be a potential management tool to facilitate improved health, welfare, and productivity in dairy cows [ 10 , 11 ]. Measuring those behaviours is also potentially important for the management of pasture and feed availability [ 12 ].…”

Automated Monitoring of Panting for Feedlot Cattle: Sensor System Accuracy and Individual Variability

“…To determine the impact of heat load on the individual animal across time, and for the strategic mitigation of cattle heat stress at an individual level, automated monitoring of the real-time animal response to heat stress is required. Commercially available accelerometer-based sensors (HR-LDn; SCR Engineers Ltd., Netanya, Israel) monitor the behaviour of cattle [37,38], including 'heavy breathing' (referred to as 'panting' in the latter sections), as defined by forward-backward heaving with an increased rate of respiration and thoracic wall extension [39]. Accelerometer-based ear tag sensors have been previously validated to monitor cattle behaviour and provide a promising tool for the automated monitoring of eating, ruminating, and resting behaviours [40][41][42].…”

Technical note: Accelerometer-based recording of heavy breathing in lactating and dry cows as an automated measure of heat load

“…This training set came from previously collected data gathered during product development. Although the HR-LDn tags have been demonstrated as accurately classifying ruminating, resting, and grazing behaviors in pastured cows (Molfino et al, 2017), they have not yet been externally validated in the context of heavy breathing.…”