传感器数据与健康监测相结合，早期发现奶牛亚临床酮病。
Combination of Sensor Data and Health Monitoring for Early Detection of Subclinical Ketosis in Dairy Cows.
机构信息
Linz Center of Mechatronics GmbH, 4040 Linz, Austria.
Institute of Stochastics, Johannes Kepler University Linz, 4040 Linz, Austria.
出版信息
Sensors (Basel). 2020 Mar 8;20(5):1484. doi: 10.3390/s20051484.
Subclinical ketosis is a metabolic disease in early lactation. It contributes to economic losses because of reduced milk yield and may promote the development of secondary diseases. Thus, an early detection seems desirable as it enables the farmer to initiate countermeasures. To support early detection, we examine different types of data recordings and use them to build a flexible algorithm that predicts the occurence of subclinical ketosis. This approach shows promising results and can be seen as a step toward automatic health monitoring in farm animals.
亚临床酮病是泌乳早期的一种代谢疾病。它会导致产奶量下降，造成经济损失，并且可能会促进继发疾病的发展。因此，早期检测似乎是必要的，因为这可以使农民能够采取相应的对策。为了支持早期检测，我们检查了不同类型的数据记录，并使用这些数据来构建一个灵活的算法，以预测亚临床酮病的发生。该方法显示出有希望的结果，可以被视为农场动物自动健康监测的一个步骤。
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