The objective of this study was to validate the CowManager SensOor ear-tag accelerometer (Agis Automatisering BV, Harmelen, the Netherlands) against visual observations of feeding, rumination, resting, and active behaviors of tiestall-housed dairy cows. Prior validation of the sensor has been published for freestall and grazing dairy herds. However, the behavioral differences that exist among these and a tiestall system necessitate additional validation. Lactating Holstein cows (n = 10) at different lactation stages and parities were included in the study. Cows were monitored both visually and with the sensor for 10 h/d for 4 consecutive days (10 cows × 10 h × 4 d = 400 h of observation total). A single trained observer classified each minute of visual observation into 1 of 13 behaviors and then summarized them into the 4 behavioral categories of eating, rumination, not active, or active. The sensor registered ear movements continuously and, based on a proprietary model, converted them into the behavioral categories. Multivariate mixed models were run to obtain covariance estimates, from which correlation coefficients were computed to assess agreement between visual observation and sensor data. The models included the percentage of time spent performing each behavior per day as the dependent variable and technology (visual observation versus sensor) and day as fixed effects. The models also included the random effects of technology and the repeated effects of technology and day. The correlation strength between visual observation and sensor data varied from poor to almost perfect by behavioral category

No abstract

No abstract

No abstract

In a previous study (Assessment 1), an on-farm assessment tool was used to establish a standard across 60 Quebec dairy farms using animal-, stall-, and management-based measures of cow comfort. The objective of the present follow-up study (Assessment 2) was to perform a reassessment using an identical cow comfort assessment tool on a subset of the original farms expected to benefit most from applying the recommended changes, and to determine the effects of the modifications on cow comfort. From the subsample of farms, 24 reported applying stall modifications based on recommendations from Assessment 1 with the aim of promoting cow comfort (Adopters), while the remaining 10 farms did not (Non-adopters). The assessment tool included 19 target areas, grouped into 9 critical areas based on measures of cow comfort that considered: housing, feed-water, health, and welfare. The on-farm report of Assessment 1 was found to increase producer awareness of issues in cow comfort measures on farms, as shown by an improvement in stall design according to recommendations based on cow body dimensions and reduced injury prevalence. Routine reassessment of cow comfort measures may be important to use in supporting target achievement improvements as part of welfare improvement strategies.