Abstract
ABSTRACT Understanding heat stress in dairy cows is important for ensuring their welfare and productivity. While the Temperature Humidity Index is commonly used to determine heat stress conditions it does not consider outdoor factors (e.g. wind speed and solar radiation). To address this, the Grazing Heat Load Index (GHLI) which predicts respiration rate, an indicator of heat stress, was previously developed using data from the Waikato region in New Zealand. This study updated the GHLI using a weather data and animal heat stress indicators (e.g. respiration rate and drooling), collected from dairy herds in the Northland, Waikato, Canterbury, and Southland regions. A mixed-effects linear model, which included air temperature, solar radiation and wind speed as inputs was developed using data from these diverse locations. The updated model slightly outperformed the previous model on a validation dataset when predicting respiration rate. While air temperature remained the primary driver of respiration rate, solar radiation was an exacerbating factor, whereas wind exerted a mitigating effect. Challenges persist in characterising heat stress in conditions such as high wind speed. Non-linear modelling techniques could enhance the predictive capability of the GHLI model, thereby refining heat stress assessment in pasture-based dairy systems nationwide.
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