Milk yield resilience indicators and sensor features for a more diverse and sustainable dairy production landscape

This information can be used for example to design and optimise low-input dairy farming systems, thereby improving animal functioning and welfare.

Global sustainability issues such as climate change, biodiversity loss and food security require food systems to become more resource efficient and better embedded in the local environment. In order to achieve these goals, an agricultural transition towards more diverse, circular and low-input dairy farming with animals best suited to the specific production situation is necessary. This type of farming can be a resource-efficient way of producing high-quality food for human consumption.

Resilient dairy cows

Farmers aim to maintain health, fertility, longevity and production of dairy cows as well as possible. One strategy is to avoid exposure to disturbances by controlling the production environment. Breeds selected in such a regime tend to depend more heavily on favourable conditions. Another strategy is to minimize the impact of disturbances on health and welfare by selecting cows that are less affected by these challenges. Developing and utilizing resilient cows is particularly relevant in the latter case.

Previous research showed that traits for which resilience is relevant differ between cattle breeds. In addition, while resilience may be improved via genetic selection or farm management, both methods require large-scale quantification of these traits by quantifying the impact of disturbances on the cows. In the past, this was performed using variability and dynamics of daily milk yield records (for example with sensor features and resilience indicators) of Holstein Friesian (HOL) cows only. In the context of diversification of the dairy sector, it is crucial to understand and quantify these milk-based resilience traits for other breeds and crossbred animals as well.

Using sensor features and resilience indicators

Unfortunately, a classical breed comparison for these features is currently impossible, as it would require explicitly considering the herd and environment effect. For this, insufficient data are available from farms in which multiple animals of different breeds are kept in the same environment. Thus, the scientists opted for a different approach. By comparing 40 sensor features and resilience indicators (based on daily milk yield records) across breeds and cross-bred animals, as well as between herds with a low or high number of HOL cows, they aimed to identify the specific sensor features and resilience indicators that can be used to differentiate between herds grouped by non-HOL cows and herds that consist almost exclusively of HOL cows. This is needed to gain insight in to what extent high-frequency data can help phenotyping complex traits and to formulate proper recommendations towards a more sustainable and diverse dairy sector.

Data for a more diverse and sustainable production landscape

“We found substantial differences between farms when studying the sensor features and resilience indicators,” says Ines Adriaens, researcher at ABG. “In specific farm contexts, these features can be used as precision phenotypes for breeding and management decisions, for example, to move towards cows that are less dependent on favourable farming conditions. This allows for diversification of dairy production according to different breeding and production goals, which supports the development of a more diverse production landscape in which the sustainability is improved with minimal impact on the environment.”