Can we predict disease earlier in preweaned dairy calves using milk feeding behaviour?

Jannelle Morrison, MSc, Dr. Dave Renaud, Assistant Professor and Dr. Charlotte Winder, Assistant Professor, University of Guelph

Producers are always looking for new and innovative ways to reduce disease in preweaned dairy calves to raise healthier and more profitable animals. Group housing of calves has increased in popularity among dairy and veal producers, as it improves calf welfare and public perception of the calf raising industry (compared to individual housing). However, the rise in group housing has amplified another on-farm problem; disease detection of calves, which can be more challenging in groups. When housed in groups, producers may have less one-on-one time with individual calves as this usually occurs around feeding times.

One promising solution to help with disease detection in group housed calves is the use of automated milk feeders (AMF). These computerized systems allow producers to feed a heightened plane of milk nutrition and access individualized feeding metrics for each calf. It is thought that some of these feeding metrics may have the ability to predict disease in these preweaned dairy calves including:

  • Milk consumption – how much milk the calf consumes daily
  • Drinking speed – how fast the calf consumes its daily milk allotment
  • Rewarded visits – the number of times the calf visits the AMF and receives a milk meal
  • Unrewarded visits – the number of times a calf visits the AMF and is turned away without receiving a milk meal due to:
    • Not enough time has elapsed since the last milk meal
    • The calf has consumed its daily allotment already

A scoping review was published that identified the current body of literature looking into the usage of AMF to predict disease. This review found that there is limited published research in this field, however the number of papers on this topic continues to grow. It was found that the majority of studies agreed that prior to disease detection, sick calves showed reduced milk consumption, and had a reduction in drinking speed, as well as fewer unrewarded visits and rewarded visits to the AMF, when compared to healthy calves.

In follow-up to the review, another study was completed to determine how feeding behaviours measured by the AMF change surrounding disease detection in a commercial production setting. This study found similar results to that of the review, in that milk consumption and drinking speed were found to be useful predictors as early as four days prior to disease detection and unrewarded visits as early as three days prior to disease detection, when compared to healthy calves. However, rewarded visits were not found to be useful as a predictor.

But why do these feeding metrics change around time of disease detection? When the calf’s immune system encounters a foreign pathogen, it mounts a defense. The immune system produces a response through the calf’s blood system inducing fever. This leads to the development of sickness behaviours such as lethargy, anorexia, and general disinterest in socialization. Due to these behaviours, the calf’s feeding behaviour changes—it will consume less milk at a slower pace and will only visit the feeder when necessary, to obtain a milk meal.

These computerized systems show great promise in aiding producers in predicting disease in dairy calves, however, there are on-farm factors which must also be taken into consideration before utilizing this technology. One of the most important factors to consider is the amount of milk being fed to the calves through the AMF. When calves are fed a restricted amount of milk (four to six litres per day), the changes in feeding behaviour are not as readily observed. This is thought to occur as the drive for hunger is a stronger motivator than sickness behaviours. Therefore, it is suggested that when feeding calves on an AMF, to feed a heightened plane of nutrition (greater than nine litres per day), so changes to feeding behaviours will be more readily observed during time of illness. It is also important to consider the number of calves in each pen; large group sizes can increase competition for the AMF, changing feeding behaviours of less dominant calves.

Overall, AMF have great potential to predict disease in preweaned dairy calves. However, it is important to remember that this technology is not meant to replace daily health checks by producers. This computerized feeder instead acts as an important tool to aid producers and allow potentially sick calves to be found earlier. Additionally, this information can also be used on farms without AMF—producers can watch calves during feeding times, allowing for identification of any calves drinking less or slower and further health checks as necessary.