Evaluation of Four Different Automated Activity Monitoring Systems to Identify Anovulatory Cows in Early Lactation

Abstract

The objective of this study was to evaluate four different automated activity monitoring (AAM) systems to identify anovulatory cows in early lactation. A total of 852 lactating Holstein cows (221 primiparous and 631 multiparous cows) from four commercial dairy herds were enrolled. On each farm, cows were equipped with a respective AAM system (SB: Smartbow; HT: Heatime; DP: Delpro; and CM: CowManager). Each cow was sampled three times within the voluntary waiting period (VWP) in a two-week interval to detect the blood progesterone (P4) concentration. Cows were classified based on the concentration of P4 as follows: (1) none of the three blood P4 concentrations exceeded 1.0 ng/mL (anovulatory); (2) at least one of the three blood P4 concentrations was above 1.0 ng/mL (ovulatory). Cows were classified based on estrus alerts as follows: (1) no estrus alert was detected by an AAM system from 7 to 60 DIM (anestrus); (2) at least one estrus alert was detected by an AAM system from 7 to 60 DIM (estrus). Accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were calculated for each AAM system for anovulatory cows [(SB: 77.6%; 26.8%; 89.3%; 36.7%; and 84.1%); (HT: 79.2%; 63.6%; 83.6%; 52.8%; and 88.9%); (DP: 47.2%; 78.8%; 41.5%; 19.5%; and 91.6%); (CM: 80.5%; 23.7%; 92.7%; 39.1%; and 85.3%)].