Project
Quantification of climate impact for breeding and decision support at dairy farms
Climate change results in an increased frequency of extreme weather conditions. Dairy cows have a high metabolic rate, and easily suffer from heat stress when the temperature-humidity index (THI) is high. This negatively affects milk production, fertility and welfare, as it results in a decreased appetite and rumen health (i.e., pH buffering), and higher disease and lameness incidence rates. Previously, we investigated the impact of THI on group-level and individual cow production and behaviour, using a method that allowed to (1) distinguish the group and individual differences, and (2) quantify timely and time-lagged effects. Our research showed variation in the response of individual dairy cows, which offers opportunities to detect and select cows based on heat stress sensitivity. Building upon our previous work, in this project, we aim to develop a machine-learning data-driven prediction model that takes the pre-processed behavioural features of the sensor time series and predicts the severity of heat stress impact in dairy cows.
High-frequency behavioural sensor data of fourteen farms from the Netherlands and Belgium were collected in 2022. For all farms, cow information and hourly climatic data are also available. Using the individual cow behavioural time series and the relevant covariates (e.g. parity), we first construct biologically meaningful features by combining domain knowledge with high-frequency behavioural sensor data. We use these features to develop machine learning models that predict the individual cows’ sensitivity to heat stress. In step 1 we apply a univariate approach (impact on production and health separately), which is followed by a multivariate approach in step 2 (production and health combined). With the integration of multiple data sources (production, health, and behavioural data from the farms, and climatic data from weather stations), we further improve the current use of these data streams to support the adaptation of dairy farms to the changing climate. Upon better understanding and prediction of the impact of heat stress on dairy cows in different farm environments, farmers and breeders can (1) better anticipate on the impact of the stressor for individual cows, e.g. by separating the most vulnerable from the more tolerant animals, reducing its impact on production and the short and long-term welfare and health consequences; and (2) select the best animal-in-environment herd by identifying which cows deal better with the specific imposed (heat stress) challenges.