Closing data-gaps between calves and cows Conceptualization of a specified sensor system for data acquisition in calf and heifer husbandry

Today the use of modern sensor technique to analyze the status, health, and productivity of dairy cattle is getting more common for adult dairy cows but is infrequent during the rearing time of calves and heifers. During the adolescence, the animal lays out its foundations for future productivity and health. Even though data is acquired in large scale for different reasons, it is fragmentary with major gaps during the period of heifer and not used for illness detection in early stages, neither for breeding references as the potential milk yield or genetic breeding performance. A cluster with complete data is to this point not developed yet. By adapting state-of-the-art sensor technique in all stages of growing cows and reaching out over the birth of the adult cow’s first calf, the issue of data gaps will be solved. To reach the goal, we applied numerous sensors on three research farms in Germany. For all calves, activity sensors were applied around the neck. The milk uptake of single housed calves is measured at the single boxes, while the milk uptake, water, and concentrate intake in group housing is detected and assigned by identifying the animal via radio-frequency identification (RFID) in the specific feeding-station. Besides the amount of intake, different activity, time, weight, and temperature data is collected in the stations as well. In the development stage of heifers, activity data, water, and concentrate intake is detected and measured using the same sensors as used for calves. Due to the large-scale design, quantitative data can be collected, gathered, and stored online in a cloud for analysis. In further work, we will use the data to extract the information which indicates healthiness and analyze it automatically by an algorithm to give comprehensive information about the health status of the specific animal. The goal is to detect changes induced by early stages of illness and to give early recommendation for possible treatments. We will use the acquired data for breeding references, as included data from the previous generation gives information about the future performance and milking potential of heifers.