Using monitoring technologies for management of dairy calves and herd health with Dr. Melissa Cantor, Penn State University; Dr. Julio O. Giordano, Cornell University; Dr. Bob James, Down Home Heifer Consulting

This episode was recorded at the 2025 Western Dairy Management Conference in Reno, Nevada.

Dr. Cantor gives an overview of her presentation at the conference, focusing on data from accelerometers and robotic feeders to predict calf sickness. While the correlations are there and we know calves change activity, behavior and feeding behavior before they get sick, there is more work to be done before the technology is ready for wide implementation. When data from both accelerometers and robotic feeders were used, Dr. Cantor’s group was able to find respiratory disease with a 96% accuracy six days before clinical symptoms. (2:36)

Dr. James and Dr. Cantor discuss the use of robotic feeders in the industry and the under-utilization of data collected by the feeders. Dr. James shares observations from a farm he works with about heifers coming in to the milking herd who were raised on robotic feeders compared to those raised in calf hutches. (6:15)

The panel discusses the accuracy, specificity and sensitivity of the predictions from monitoring technologies. They also touch on challenges around deciding what parameters to use to classify an animal experiencing the onset of clinical disease and how that will vary depending on the disease. They go on to share their experiences with training algorithms and how computer scientists have different goals than animal scientists with this type of technology. (11:17)

Dr. James talks about how data collection and using data can be a hard sell on some calf ranches. The panel talks about some of the challenges they have seen with adoption of technology and recordkeeping on dairies of various sizes. (28:30)

Dr. Giordano gives an overview of his presentation on using monitoring technology in fresh cows to predict disease. His group has worked with wearable sensors that monitor rumination time and physical activity. More recently, sensor companies have added eating behavior and body temperature. Variations in these parameters create a health alert to check on that particular animal. (39:08)

He goes on to describe two extremes in dairy farms. One spends little time and effort on looking for sick cows, while the other puts a lot of time and effort into this task. He discusses how bringing technology to these two types of farms benefits them and what drawbacks there are, along with an economic analysis for each. (43:14)

The panel discusses how implementing monitoring technologies require a change in management. Allowing animals the opportunity to express their natural behavior is critical to success. They also talk about how veterinarians view this technology and the target age for calves to best learn how to use a robotic feeder. (48:54)

Panelists share their take-home thoughts. (57:11)

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