Remote Health Monitoring Improves Dairy Cow’s Well-being

Productivity and longevity of dairy cows are greatly influenced by proper nutrition programs. Human-animal interaction in larger dairies is limited, and ailments detection relies heavily on employees. Metabolic disorders and their complications such as hypocalcaemia, fatty liver, ketosis, displaced abomasum, acidosis, and laminitis may result from dietary inadequacies. Early veterinary attention increases treatment effectiveness and reduces overall costs. Troubleshooting dietary problems can be done by checking how many cows chew their cud, recording intake changes, manure consistency, and presence of undigested feed particles. Changes in short-term feeding behavior detected through computerized feeders have been associated with the onset of feeding disorders. Ketosis was associated with rapid decreases in daily intake, feeding period length and rate 3.6 days before clinical detection by employees (Gonzalez et al. 2008). In that same experiment cows with acute locomotion disorders had smaller daily decreases in intake, feeding period length, and daily increases in feeding rates during 7.7 days before actual clinical detection. Feeding disorders for example were detected in 80% of the cows at least 1 d before. 

Producers, veterinarians and nutritionists have long relied on cud chewing to monitor cow health. One rule of thumb has been that among the cows lying down properly in stalls 50 to 60 percent should be chewing their cud. Assessing rumen activity and health in commercial dairies can nowadays be done through electronic monitoring of cud chewing. Graph 1 shows typical rumination activity in a healthy cow observed as daily peaks (yellow arrows; mid-night) and valleys (white arrows; mid-day) of rumination. As can be seen in the graph most rumination takes place during the night when the cows are resting. 

Graph 2 depicts a fresh cow with starts to increase intake and thus rumination and all of a sudden rumination falls abruptly on day 5. This cow has to be looked closer for ketosis or even acidosis. Today’s electronic systems can also track the cow’s the cow’s activity simultaneously which is used to detect heats (Graph 3). Each cow is fitted with a reading tag that hangs from her neck. For the average dairy farm monitoring it the number of tags needed would probably be around one third of the total milking cows. The data stored in the tag is transmitted from through infrared communication each time a cow passes under a reading station (transceiver ID). This generates a report for every cow than can be read in the farm’s computer graphing rumination time, chewing rhythm and time between feed boluses. It also records the cow’s general activity both all animal movement and their intensity (walking, running, laying, standing up, head movements, etc.). 

As cows in heat increase their activity this feature of the tags has been critical in substitution for visual heat detection. This feature has a great degree of accuracy when used in combination with the rumination graph (Graph 4) as a cow in heat will not only increase its activity but it will also reduce its intake. This has resulted in more than 95% heat detection according to producers that use the system. Even cystic ovaries can be detected which usually appear as consecutive intermittent activity peaks. In today’s dairy farms where trained help is difficult to come by this new technology can reduce labor, optimize time, and reduce veterinary costs.