POSTER PRESENTATION: Utilizing Precision Dairy Technology (PDT) to Monitor Behavioral and Physiological Parameters in Dairy

Utilizing Precision Dairy Technologies (PDT) for monitoring behavioral and physiological parameters in dairy cows, enhances on-farm decision-making. Understanding individual cow variations in behavioral patterns can help farmers to make more informative decisions, promoting greater cow health and welfare. This study aimed to investigate individual variations in rumination, locomotion and feeding activity, inactivity, and panting time (h/d) in dairy cows, utilizing a comprehensive dataset from 298 Brazilian dairy farms. Individual data on these variables were gathered from dairy farms (n = 3,902,551 records from 12,851 dairy cows) using behavior monitoring collars. Following data cleaning and outlier removal, 90.61% (3,802,463 records) were retained. To assess animal variability for each response variable, we applied the Wood model to each cow data. The Wood model, comprising parameters a, b, and c, was selected after visually evaluating the average curve for each response variable across lactation days. We defined cow variability as the residual standard deviation derived from each adjusted model. The average and median rumination time variability were 0.766 and 0.742 h/d, respectively (n = 12,739; min = 0.199, first quartile (Q1) = 0.658; third quartile (Q3) = 0.845; max = 1.763, skewness = 1.1 (right skewed)). The average and median locomotion and feeding activity time variability were 0.827 and 0.791 h/d, respectively (n = 12,775; min = 0.172, Q1 = 0.677; Q3 = 0.933; max = 2.648, skewness = 1.372 (right skewed)). The average and median inactivity time variability were 0.935 and 0.901 h/d, respectively (n = 12,618; min = 0.063, Q1 = 0.789; Q3 = 1.040; max = 2.479 skewness = 1.293 (right skewed)). The average and median panting time variability were 0.326 and 0.306 h/d, respectively (n = 12,726; min = 0.128, Q1 = 0.275; Q3 = 0.358; max = 0.754, skewness = 1.45 (right skewed)). In conclusion, this study displays the variability of dairy cow behaviors and physiological parameters, providing insights that can enable the identification of abnormal patterns, potentially supporting interventions for improved animal health and management.