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Predicting morbidity and mortality using automated milk feeders: A scoping review.

J. L. Morrison

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06-23-2020

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Abstract:

T28
Predicting morbidity and mortality using automated milk feeders: A scoping review.
J. L. Morrison*1, C. B. Winder1, J. H. C. Costa2, M. A. Steele1, D. L. Renaud1. 1University of Guelph Guelph, ON, Canada, 2University of Kentucky Lexington, KY.

Automated milk feeders (AMF) provide producers with a tool that can be used to more efficiently raise dairy calves. AMF are computerized systems that allow for the easier implementation of a higher plane of nutrition to dairy calves. AMF also have the ability to track individualized data, such as milk consumption, drinking speed, and the number of visits to the feeder, that could be used to predict disease. The objective of this scoping review was to characterize the body of literature investigating the use of AMF data to predict morbidity and mortality in dairy calves during the preweaning stage. This review will list the parameters that have been examined for associations with disease in calves and identify gaps in knowledge. Five databases and relevant conference proceedings were searched. Eligible studies focused on the use of behavioral parameters measured by AMF to predict morbidity or mortality in preweaned dairy calves. Two reviewers independently screened titles and abstracts from 6,679 initially identified records. Of those, 386 studies were included and then assessed at the full text level. Ninety-three studies fed calves using an AMF and provided some measure of morbidity and mortality. Of these, 15 examined AMF parameters for associations with morbidity or mortality. The studies were completed in North America (n = 7), Europe (n = 6) or New Zealand (n = 2). The studies varied in sample size ranging from 30 to 1,052 calves with an average of 225 calves. Seven of the studies used a mixture of Holstein or Jersey (or both) heifers and bulls, while the rest used exclusively bulls (n = 4) or heifers (n = 3). The most common parameters assessed for associations with health included drinking speed (L/min) (n = 8), rewarded and unrewarded visits (n = 9), and amount of milk consumed (L/day) (n = 14). Morbidity descriptions (time at risk and case definition) varied between studies. This scoping review revealed a small number of studies examining use of data from an AMF to predict disease in calves, with potential challenges with comparability of outcomes. Further research is needed to determine the efficacy of these parameters in commercial settings.

Keywords: dairy calf, computerized feeder, AMF.

Biography: Jannelle Morrison is currently completing her Master's Thesis at the University of Guelph in Population Medicine. Before moving to Ontario, she completed her undergraduate degree at the University of Alberta completing her Bachelor of Science in Animal Health with Distinction, majoring in Food Animal Production.