The impact of health disorders on automated sensor measures and feed intake in lactating Holstein dairy cattle

Abstract

Animal health and feed intake are closely interrelated, with the latter being an important indicator of an animal’s health status. Automated sensors for dairy cattle have been developed to detect changes in indicators of health, such as decreased rumination or activity. Previous studies have identified associations between sensor measurements and feed intake. Thus, the objective of this study was to determine if health disorders impact the associations identified between sensors and dry matter intake (DMI), and to measure the impact of health disorders on DMI. A total of 934 cows with health disorders (lameness, mastitis, and other), of which 57, 94, and 333 cows had observations for a rumen bolus and one of two ear tags, were analyzed to determine how health disorders impact the association of sensors with DMI. Eleven sensor measurements were collected across the three sensors, including total and point-in-time activity, rumination time, inner-ear temperature, rumen pH and rumen temperature. Associations of health disorders and sensor measures with DMI were evaluated when accounting for systematic effects (i.e., contemporary group, parity, and days in milk) and energy sinks accounted for in determination of feed efficiency (e.g., milk production, body weight and composition). In order to determine if inclusion of health disorders or sensor measures improved model fit, model AICs were assessed. Health disorders were significantly associated with all sensor measurements (P< 0.0001), with the direction of association dependent on sensor measure and health disorder. Moreover, DMI decreased with all health disorders, with larger impacts observed in animals in third and higher lactations. Numerous sensor measurements were associated with DMI, including when DMI was adjusted for energy sink variables and health. Inclusion of rumen bolus temperature, rumination or activity with health data reduced model AIC when evaluating DMI as the dependent variable. Some sensor measures, including measurements of activity, temperature and rumination, accounted for additional variation in feed intake when adjusted for health disorders. Results from the study indicate that feed intake and sensor measures are impacted by health disorders. These findings may have implications for use of sensors in genetic evaluations and precision feeding of dairy cattle.