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Article

An Absorbing Markov Chain Model to Predict Dairy Cow Calving Time

1
Interdisciplinary Graduate School of Agriculture and Engineering, University of Miyazaki, Miyazaki 889-2192, Japan
2
Graduate School of Engineering, University of Miyazaki, Miyazaki 889-2192, Japan
3
Field Science Center, Faculty of Agriculture, University of Miyazaki, Miyazaki 889-2192, Japan
4
Center of Animal Disease Control, University of Miyazaki, Miyazaki 889-2192, Japan
*
Author to whom correspondence should be addressed.
Sensors 2021, 21(19), 6490; https://doi.org/10.3390/s21196490
Submission received: 6 August 2021 / Revised: 17 September 2021 / Accepted: 23 September 2021 / Published: 28 September 2021

Abstract

Abnormal behavioral changes in the regular daily mobility routine of a pregnant dairy cow can be an indicator or early sign to recognize when a calving event is imminent. Image processing technology and statistical approaches can be effectively used to achieve a more accurate result in predicting the time of calving. We hypothesize that data collected using a 360-degree camera to monitor cows before and during calving can be used to establish the daily activities of individual pregnant cows and to detect changes in their routine. In this study, we develop an augmented Markov chain model to predict calving time and better understand associated behavior. The objective of this study is to determine the feasibility of this calving time prediction system by adapting a simple Markov model for use on a typical dairy cow dataset. This augmented absorbing Markov chain model is based on a behavior embedded transient Markov chain model for characterizing cow behavior patterns during the 48 h before calving and to predict the expected time of calving. In developing the model, we started with an embedded four-state Markov chain model, and then augmented that model by adding calving as both a transient state, and an absorbing state. Then, using this model, we derive (1) the probability of calving at 2 h intervals after a reference point, and (2) the expected time of calving, using their motions between the different transient states. Finally, we present some experimental results for the performance of this model on the dairy farm compared with other machine learning techniques, showing that the proposed method is promising.
Keywords: absorbing Markov chain; cow behavior analysis; prediction of calving time absorbing Markov chain; cow behavior analysis; prediction of calving time

Share and Cite

MDPI and ACS Style

Maw, S.Z.; Zin, T.T.; Tin, P.; Kobayashi, I.; Horii, Y. An Absorbing Markov Chain Model to Predict Dairy Cow Calving Time. Sensors 2021, 21, 6490. https://doi.org/10.3390/s21196490

AMA Style

Maw SZ, Zin TT, Tin P, Kobayashi I, Horii Y. An Absorbing Markov Chain Model to Predict Dairy Cow Calving Time. Sensors. 2021; 21(19):6490. https://doi.org/10.3390/s21196490

Chicago/Turabian Style

Maw, Swe Zar, Thi Thi Zin, Pyke Tin, Ikuo Kobayashi, and Yoichiro Horii. 2021. "An Absorbing Markov Chain Model to Predict Dairy Cow Calving Time" Sensors 21, no. 19: 6490. https://doi.org/10.3390/s21196490

APA Style

Maw, S. Z., Zin, T. T., Tin, P., Kobayashi, I., & Horii, Y. (2021). An Absorbing Markov Chain Model to Predict Dairy Cow Calving Time. Sensors, 21(19), 6490. https://doi.org/10.3390/s21196490

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