The Importance of Low Daily Risk for the Prediction of Treatment Events of Individual Dairy Cows with Sensor Systems
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Institute of Animal Science, Physiology Unit, University of Bonn, 53115 Bonn, Germany
2
Department of Educational Science, Faculty of Educational and Social Sciences, University of Education Heidelberg, 69120 Heidelberg, Germany
3
Institute for Agricultural Engineering, Livestock Technology Section, University of Bonn, 53115 Bonn, Germany
*
Author to whom correspondence should be addressed.
Sensors 2021, 21(4), 1389; https://doi.org/10.3390/s21041389
Received: 30 November 2020
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Revised: 29 January 2021
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Accepted: 11 February 2021
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Published: 17 February 2021
(This article belongs to the Special Issue Sensors for Animal Health Monitoring and Precision Livestock Farming)
The prediction of health disorders is the goal of many sensor systems in dairy farming. Although mastitis and lameness are the most common health disorders in dairy cows, these diseases or treatments are a rare event related to a single day and cow. A number of studies already developed and evaluated models for classifying cows in need of treatment for mastitis and lameness with machine learning methods, but few have illustrated the effects of the positive predictive value (PPV) on practical application. The objective of this study was to investigate the importance of low-frequency treatments of mastitis or lameness for the applicability of these classification models in practice. Data from three German dairy farms contained animal individual sensor data (milkings, activity, feed intake) and were classified using machine learning models developed in a previous study. Subsequently, different risk criteria (previous treatments, information from milk recording, early lactation) were designed to isolate high-risk groups. Restricting selection to cows with previous mastitis or hoof treatment achieved the highest increase in PPV from 0.07 to 0.20 and 0.15, respectively. However, the known low daily risk of a treatment per cow remains the critical factor that prevents the reduction of daily false-positive alarms to a satisfactory level. Sensor systems should be seen as additional decision-support aid to the farmers’ expert knowledge.
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Keywords:
mastitis; lameness; machine learning; animal welfare
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MDPI and ACS Style
Post, C.; Rietz, C.; Büscher, W.; Müller, U. The Importance of Low Daily Risk for the Prediction of Treatment Events of Individual Dairy Cows with Sensor Systems. Sensors 2021, 21, 1389. https://doi.org/10.3390/s21041389
AMA Style
Post C, Rietz C, Büscher W, Müller U. The Importance of Low Daily Risk for the Prediction of Treatment Events of Individual Dairy Cows with Sensor Systems. Sensors. 2021; 21(4):1389. https://doi.org/10.3390/s21041389
Chicago/Turabian StylePost, Christian, Christian Rietz, Wolfgang Büscher, and Ute Müller. 2021. "The Importance of Low Daily Risk for the Prediction of Treatment Events of Individual Dairy Cows with Sensor Systems" Sensors 21, no. 4: 1389. https://doi.org/10.3390/s21041389
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