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Research Article | Open Access |

Method for Productive Cattle Finding with Estrus Cycle Estimated with BCS and Parity Number and Hormone Treatments based on a Regressive Analysis

Author 1: Kohei Arai Author 2: Narumi Suzaki Author 3: Iqbal Ahmed Author 4: Osamu Fukuda Author 5: Hiroshi Okumura Author 6: Kenji Endo Author 7: Kenichi Yamashita
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 8, No. 9 · Published 2017

DOI: 10.14569/IJACSA.2017.080927

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Abstract

Estrus cycle estimation method through correlation analysis among influencing factors based on regressive analysis is carried out for Japanese Dairy Cattle Productivity Analysis. Through the experiments with 280 Japanese anestrus Holstein dairy cows, it is found that estrus cycle can be estimated with the measured with visual index of Body Condition Score (BCS), hormone treatments, and parity number, based on regressive equation. Also, it is found that the time from the delivery to the next estrus can be expressed with BCS, hormonal treatments, parity. Thus it is found that productivity of cattle can be identified.

Keywords

Body Condition Score (BCS) postpartum interval parity number estrous cycle cattle productivity

How to Cite this Article

Arai, K., Suzaki, N., Ahmed, I., Fukuda, O., Okumura, H., Endo, K., & Yamashita, K. (2017). Method for Productive Cattle Finding with Estrus Cycle Estimated with BCS and Parity Number and Hormone Treatments based on a Regressive Analysis. International Journal of Advanced Computer Science and Applications, 8(9). https://doi.org/10.14569/IJACSA.2017.080927

Arai, Kohei, et al.. "Method for Productive Cattle Finding with Estrus Cycle Estimated with BCS and Parity Number and Hormone Treatments based on a Regressive Analysis." International Journal of Advanced Computer Science and Applications, vol. 8, no. 9, 2017, https://doi.org/10.14569/IJACSA.2017.080927.

@article{Arai2017,
  title     = {Method for Productive Cattle Finding with Estrus Cycle Estimated with BCS and Parity Number and Hormone Treatments based on a Regressive Analysis},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {8},
  number    = {9},
  year      = {2017},
  publisher = {The Science and Information Organization},
  author    = {Kohei Arai and Narumi Suzaki and Iqbal Ahmed and Osamu Fukuda and Hiroshi Okumura and Kenji Endo and Kenichi Yamashita},
  doi       = {10.14569/IJACSA.2017.080927},
  url       = {https://doi.org/10.14569/IJACSA.2017.080927}
}

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Volume 17 No. 11, November 2026
Paper Submission Due October 25, 2026
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