The adoption of automated milk feeders and group housing of preweaning dairy calves has become more common in Canada; however, disease detection in group-housed calves remains a challenge. The aim of this cross-sectional study was to assess whether feeding behavior data collected from a single point in time could be used to aid in the detection of neonatal calf diarrhea (NCD), bovine respiratory disease (BRD), and general disease, in preweaning group-housed calves being fed via an automated milk feeder. The data used was collected in an earlier study. A total of 8 dairy farms recruited from an online survey of calf-management practices were enrolled into the study. There was a total of 523 observations with 130 events of NCD, 115 events of BRD, and 210 events of general disease. Each farm was visited once in each of the fall, winter, spring, and summer, when the calves' health was scored, and the data were collected from the automated milk feeders. Mixed linear regression models were used to identify associations between feeding behavior data (milk consumption, time spent at the feeder, drinking speed, and the number of rewarded and unrewarded visits) and the presence of NCD, BRD, or general disease (having one or more of NCD, BRD, or umbilical infection), on the day of health scoring. Generalized linear mixed models were used to analyze the percentage of milk the calf consumed from their daily milk allotment. Calves with BRD consumed 63% less of their daily allotment of milk, had 2 fewer unrewarded visits to the automated milk feeder, and drank milk 152 mL/min slower compared with calves without BRD. Calves with NCD consumed 57% less of their daily milk allotment, consumed 758 mL less per day, and drank 92 mL/min slower than calves compared with calves without NCD. Calves with general disease drank 50% less of their daily milk allowance, consumed 496 mL less per day, drank 80 mL/min slower, and had 2 fewer unrewarded visits to the automated milk feeder, when compared with calves without disease. No significant associations were found between the presence of NCD, BRD, or general disease and time spent at the feeder or number of rewarded visits. Sensitivity and specificity values for disease identification were low when evaluating the feeding behaviors individually, so parallel testing was completed. To do so, if any significant feeding behavior was below the optimal cut point for disease detection as determined using a ROC curve, the calf was considered positive for disease and the sensitivity and specificity were recalculated. Parallel testing resulted in a sensitivity of 0.82, 0.78, and 0.84, and a specificity of 0.26, 0.23, and 0.21, for BRD, NCD, and general disease, respectively. This suggests that automated milk feeders may serve as a useful preliminary tool in the detection of diseased calves. For example, producers could use feeding behavior data to identify calves requiring further inspection; however, they should not use feeding behavior data as a sole disease detection method.
|Number of pages||11|
|Journal||Journal of Dairy Science|
|State||Published - Sep 2021|
Bibliographical noteFunding Information:
This research was supported by Food from Thought at the University of Guelph (Guelph, ON, Canada), which is funded in part by the Canada First Research Excellence Fund. The authors have not stated any conflicts of interest.
© 2021 American Dairy Science Association
- group housing
ASJC Scopus subject areas
- Food Science
- Animal Science and Zoology