Short communication: Evaluation of an eating time sensor for use in pasture-based dairy systems.

J Dairy Sci

Lincoln University, Department of Agricultural Sciences, Faculty of Agricultural and Life Sciences, Lincoln 7647, Christchurch, New Zealand.

Published: October 2020

The assessment of grazing behavior is important for research and practice in pasture-grazed dairy farm systems. However, few devices are available that enable assessment of cow grazing behavior at an individual animal level. This study investigated whether commercially available Smarttag "eating time" sensors (Nedap Livestock Management, Groenlo, the Netherlands) were suitable for recording the grazing time of cows. Smarttag sensors were mounted on the neck collars of multiparous Holstein-Friesian cows in a herd in Taranaki, New Zealand. Cows were randomly selected each observation day from the milking herd for 8 separate days across a 1-mo period. Trained observers conducted 90-min observation periods to evaluate the relationship between the sensor eating time measure and grazing time. A set of 5 defined cow behaviors (2 "head up" and 3 "head down" behaviors) were assessed. In total, observations of 37 cows were recorded in 14 sessions over 8 d in the study period, providing 55.5 total hours of observations. Observation data were aligned with sensor data according to the sensor time stamps and grouped into matching 15-min intervals. Interobserver reliability was assessed both before and after the main trial period, and the mean percentage eating time per observer had a coefficient of variation of 0.46% [mean 93.2, standard deviation (SD) 0.425] before and 0.07% (mean 96.3, SD 0.074) after. In the main trial, the relationship between observed (mean 70.8%) and sensor-derived (mean 69.3%) percentage eating time over the observation period gave a Pearson correlation coefficient of 0.971, concordance correlation coefficient 0.968, mean difference 1.50% points, and SD 5.8% points. Therefore, sensor-identified percentage "eating time" and observed percentage active grazing time were shown to be both very well correlated and concordant (in agreement, with high correlation and little bias). Therefore, the relationship between observed and sensor-derived data had a high degree of agreement for identifying cow grazing activity. In conclusion, Smarttag sensors are a valid and useful tool for estimating grazing activity at time periods of 1 h or more.

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http://dx.doi.org/10.3168/jds.2020-18173DOI Listing

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