Monitoring systems assist farmers in monitoring the health of dairy cows by predicting behavioral patterns (e.g., lying) and their changes with machine learning models. However, the available systems were developed either for indoors or for pasture and fail to predict the behavior in other locations. Therefore, the goal of our study was to train and evaluate a model for the prediction of lying on a pasture and in the barn. On three farms, 7–11 dairy cows each were equipped with the prototype of the monitoring system containing an accelerometer, a magnetometer and a gyroscope. Video observations on the pasture and in the barn provided ground truth data. We used 34.5 h of datasets from pasture for training and 480.5 h from both locations for evaluating. In comparison, random forest, an orientation-independent feature set with 5 s windows without overlap, achieved the highest accuracy. Sensitivity, specificity and accuracy were 95.6%, 80.5% and 87.4%, respectively. Accuracy on the pasture (93.2%) exceeded accuracy in the barn (81.4%). Ruminating while standing was the most confused with lying. Out of individual lying bouts, 95.6 and 93.4% were identified on the pasture and in the barn, respectively. Adding a model for standing up events and lying down events could improve the prediction of lying in the barn.

Climate change is accompanied by temperatures exceeding the thermal comfort zone of dairy cows, resulting in numerous consequences for production and welfare. Early detection of heat load enables taking countermeasures and can be realized using monitoring systems. We aimed at investigating heat load-induced changes in the behavior and physiology of grazing Simmental cows. Data were collected on five (round 1; r1) and eight (round 2; r2) consecutive days on a dairy farm combining a freestall barn with permanent access to pasture. Weather data, respiration rate, milk yield, milk composition, and fecal cortisol of eleven (r1) and thirteen (r2) cows were collected. The behavior of five animals was recorded with collar-based monitoring systems. Previously reported thresholds of different weather indices were exceeded on two days in r1 and on four days in r2. Under heat load, respiration rate and somatic cell count increased. Fecal cortisol did not change in r1 but increased steadily in r2. Grazing time decreased in r1. Rumination mainly occurred at night in both rounds, and its synchrony decreased in r2. Although limited by sample size, our results give a first impression on heat load induced physiological and behavioral reactions of Simmental dairy cows on pasture.

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