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Supported by improved genetics and management practices, the cows’ milk production almost doubled over the last 50 years. Just like top athletes, these animals need a lot of care and attention to maintain a good health and welfare and achieve maximum production levels with minimal environmental impact. On the other hand, the high volatility of the milk price forces the dairy sector to focus on profitability and risk management by upscaling their business. Therefore, to better manage their expanding herds, dairy farmers require reliable technology to monitor the health, production, behavior, welfare and environmental impact of individual animals.
Sensor technology is already well-integrated in dairy farming with applications in measuring milk production, milk quality, feed intake, animal behavior and condition, etc. Nevertheless, most of these systems produce an overload of data, rather than clear, useful and accurate information ready to use by the farmer to optimize its animal management. The essence of precision livestock farming is about correctly interpreting the collected data and extracting reliable information using advanced data-processing techniques. Ideally, these intelligent algorithms provide explicit information on the cow’s health and welfare status by combining different sources of sensor data and relying on physiology-based knowledge.In this project, data-based tools to monitor the udder health and energy balance of dairy cows will be developed, validated and implemented. To this end, both data obtained from sensors already widely available on modern dairy farms as well as innovative technologies will be involved. At the end of this 4-year PhD project, the practical implementation of the obtained models and knowledge will help dairy farmers to increase animal health and welfare, make more efficient use of labor and medicines, improve profitability and create a wider social support for sustainable dairy farming.
