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Research of Estrus Detection Models in Dairy Cows by Activity

Received: 20 June 2018    Accepted:     Published: 22 June 2018
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Abstract

The detection of estrus in large-scale ranch is an extremely labor-intensive task. Accurate and efficient detection can shorten the tires spacing of cow and increase economic income of ranch.The change in activity is one of the most important external features of dairy cows' estrus.In this paper, the activity of cows was collected remotely using activity collectors, wireless transmission networks and cloud servers, and the data was framed, labeled and preprocessed. The logistic regression, MLPs and SVMs model were trained by differential activity data of current and historical dates within the same hour.The experimental results show that the detection model by cow activity has a higher accuracy in predicting the estrus of cows. The SVMs in the three models have the best prediction effect. The recall and accuracy rate reach 90.12% and 93.74%, respectively.In the actual ranch test, the estrus detection system using the SVM model has more than double the exposure rate than the manual disclosure.

DOI 10.11648/j.sd.20180602.15
Published in Science Discovery (Volume 6, Issue 2, April 2018)
Page(s) 102-109
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Cows Estrus Prediction, Activity, Logistic Regression, Multilayer Perceptions, Support Vector Machine

References
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[12] 侯云涛,蔡晓华,吴泽全,等.奶牛行为特征识别方法的研究与实现—基于支持向量机[J].农机化研究, 2018, 40(8):36-41。
[13] 张爽.奶牛个体反刍行为监测技术研究[D].东北农业大学,2017。
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Author Information
  • College of Electronic Information Engineering, Inner Mongolia University, Hohhot, China

  • College of Electronic Information Engineering, Inner Mongolia University, Hohhot, China

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    Daoerji Fan, Huijuan Wu. (2018). Research of Estrus Detection Models in Dairy Cows by Activity. Science Discovery, 6(2), 102-109. https://doi.org/10.11648/j.sd.20180602.15

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    ACS Style

    Daoerji Fan; Huijuan Wu. Research of Estrus Detection Models in Dairy Cows by Activity. Sci. Discov. 2018, 6(2), 102-109. doi: 10.11648/j.sd.20180602.15

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    AMA Style

    Daoerji Fan, Huijuan Wu. Research of Estrus Detection Models in Dairy Cows by Activity. Sci Discov. 2018;6(2):102-109. doi: 10.11648/j.sd.20180602.15

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  • @article{10.11648/j.sd.20180602.15,
      author = {Daoerji Fan and Huijuan Wu},
      title = {Research of Estrus Detection Models in Dairy Cows by Activity},
      journal = {Science Discovery},
      volume = {6},
      number = {2},
      pages = {102-109},
      doi = {10.11648/j.sd.20180602.15},
      url = {https://doi.org/10.11648/j.sd.20180602.15},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.sd.20180602.15},
      abstract = {The detection of estrus in large-scale ranch is an extremely labor-intensive task. Accurate and efficient detection can shorten the tires spacing of cow and increase economic income of ranch.The change in activity is one of the most important external features of dairy cows' estrus.In this paper, the activity of cows was collected remotely using activity collectors, wireless transmission networks and cloud servers, and the data was framed, labeled and preprocessed. The logistic regression, MLPs and SVMs model were trained by differential activity data of current and historical dates within the same hour.The experimental results show that the detection model by cow activity has a higher accuracy in predicting the estrus of cows. The SVMs in the three models have the best prediction effect. The recall and accuracy rate reach 90.12% and 93.74%, respectively.In the actual ranch test, the estrus detection system using the SVM model has more than double the exposure rate than the manual disclosure.},
     year = {2018}
    }
    

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  • TY  - JOUR
    T1  - Research of Estrus Detection Models in Dairy Cows by Activity
    AU  - Daoerji Fan
    AU  - Huijuan Wu
    Y1  - 2018/06/22
    PY  - 2018
    N1  - https://doi.org/10.11648/j.sd.20180602.15
    DO  - 10.11648/j.sd.20180602.15
    T2  - Science Discovery
    JF  - Science Discovery
    JO  - Science Discovery
    SP  - 102
    EP  - 109
    PB  - Science Publishing Group
    SN  - 2331-0650
    UR  - https://doi.org/10.11648/j.sd.20180602.15
    AB  - The detection of estrus in large-scale ranch is an extremely labor-intensive task. Accurate and efficient detection can shorten the tires spacing of cow and increase economic income of ranch.The change in activity is one of the most important external features of dairy cows' estrus.In this paper, the activity of cows was collected remotely using activity collectors, wireless transmission networks and cloud servers, and the data was framed, labeled and preprocessed. The logistic regression, MLPs and SVMs model were trained by differential activity data of current and historical dates within the same hour.The experimental results show that the detection model by cow activity has a higher accuracy in predicting the estrus of cows. The SVMs in the three models have the best prediction effect. The recall and accuracy rate reach 90.12% and 93.74%, respectively.In the actual ranch test, the estrus detection system using the SVM model has more than double the exposure rate than the manual disclosure.
    VL  - 6
    IS  - 2
    ER  - 

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