With growing interest in provision of brushes to cattle, and implications of brush use for behavioral development and welfare, there is a need to validate methodology for quantifying grooming behavior. Our objectives were to characterize patterns of brush use, including bouts, diurnal activity, and individual variability over 24-h periods and to validate time sampling methodologies to characterize these traits, including instantaneous recording at various time intervals and continuous recording for subsets of the day. Data sets from previous experiments involving steers (Experiment 1; n = 18) and heifers (Experiment 2; n = 64), consisting of start and end times of brush use continuously recorded from video, were used to analyze brush use. We extrapolated data sets representative of a range of instantaneous recording intervals and compared daily brush duration and bout characteristics with corresponding values from continuous recording using linear regression. To assess validity of sampling subsets of the day, we selected 2-h time periods representative of different functional parts of the day and compared hourly brush rates with continuous data using Spearman’s rank order correlation. Brush use was variable among individuals. All steers used the brush in Experiment 1, but 17 % (n = 11 of 64) of heifers in Experiment 2 did not. Bout analysis revealed that individuals that used the brush for, on average 7 to 8 brush bouts, lasting 4 to 6 min, leading to an average of 24 and 36 min/day for Experiment 1 and 2, respectively. Cattle used the brush mainly during daylight hours, with peaks around sunrise, sunset, and the afternoon. Instantaneous recording at intervals less than 1-3 min, depending on the experiment, provided good estimates of daily brush use duration (R² > 0.95 and slope and intercept not different from 1 and 0, respectively) with intervals > 3 min being less reliable. For bout characteristics, the intercept of the modeled line differed from 0 for most recording intervals for both experiments, and the slope differed from 1 for recording intervals greater than 30 s in Experiment 1, suggesting that time sampling may be underestimating true values. Of the 2-h periods compared to 24 h of observation, 1800-2000 h was most highly correlated (r_s = 0.84) for Experiment 1, and 1800-2000 and 1400-1600 were the most highly correlated (r_s = 0.71 and 0.74, respectively) for Experiment 2 with daily values. When using time sampling methods to characterize brush use, we suggest that the recording interval used and time of day observed should be carefully considered, as time sampling at an interval of 1-3 min may measure daily brush use duration, but continuous recording may be required to capture bout characteristics.

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Data were collected at the University of California Davis. In the Excel file, there is a directory of spreadsheets "Spreadsheet description" and of the headings and variables used throughout "Heading description". The SAS script used to analyze each dataset is provided.