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J Anim Sci. 2013 Oct;91(10):4899-907. doi: 10.2527/jas.2012-5554. Epub 2013 Aug 21.

Methodology for quantifying the behavioral activity of dairy cows in freestall barns.

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Department of Agricultural and Environmental Sciences, Università degli Studi di Milano, I-20133 Milan, Italy.


The objectives of this study were to 1) evaluate the validity of automated monitoring systems as assessment method for the behavioral activity of dairy cows compared with video recording, and 2) determine the sampling intervals required to obtain reliable estimates of the daily behavior. To determine lying, standing, and walking, 12 cows were equipped with automatic recording devices (IceTag = 12 cows, HOBO Pendant G = 5 cows), and their behavior was simultaneously recorded using a video recording system. The correspondence between the IceTag, HOBO logger, and video recording data was analyzed using 2 × 2 contingency tables, and we determined the sensitivity, specificity, and predictive value (positive and negative). Both types of loggers demonstrated high sensitivity (Sen ≥ 0.961) and specificity (Sp ≥ 0.951) for lying and standing behaviors with predictive values near 1.00. The HOBO logger can accurately describe the laterality of lying behavior, whereas the IceTag device inadequately recorded walking, with probability predictive values ≤ 0.303. Daily behaviors of the dairy cows were compared for 10 different sampling intervals (1 s, and 1, 2, 3, 4, 5, 10, 15, 30, and 60 min) collected by the IceTag, using linear regression. A strong relationship (R(2) ≥ 0.978) was found between the total lying times from data on a per-second basis and estimates obtained by 1, 2, 3, 4, 5, 10, and 15 min sampling intervals. The sampling intervals of 1 and 2 min were comparable for all aspects of lying behavior (R(2) ≥ 0.813; P > 0.05 for slope = 1, intercept = 0). Long sampling intervals (30 and 60 min) showed positive relationship for estimating time spent lying and standing (R(2) ≥ 0.774), but were inappropriate for predicting these behaviors, because they lacked accuracy and precision. Both the IceTag and HOBO logger accurately measured all aspects of lying and standing behavior. Reliable estimates of lying and standing time can be generated using relatively short interval lengths (e.g., 3, 4, 5, 10, or 15 min). Shorter sampling intervals (≤ 2 min) are required to accurately measure aspects of lying behavior such as number of lying bouts per day. The automated monitoring systems are time- and labor-saving tools that can be used by research or on farm to assess cow comfort related to lying behavior.

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