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The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

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Research Article | Open Access |

Artificial Intelligence based Fertilizer Control for Improvement of Rice Quality and Harvest Amount

Author 1: Kohei Arai Author 2: Osamu Shigetomi Author 3: Yuko Miura
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 9, No. 10 · Published 2018 · Cited by 5

DOI: https://doi.org/10.14569/IJACSA.2018.091008

Abstract

Artificial Intelligence: AI based fertilizer control for improvement of rice quality and harvest amount is proposed together with intelligent drone based rice field monitoring system. Through experiments at the rice paddy fields which is situated at Saga Prefectural Research Institute of Agriculture: SPRIA in Saga city, Japan, it is found that the proposed system allows control rice crop quality and harvest amount by changing fertilizer type and supply amount. It, also, is found the most appropriate fertilizer supply management method which maximizing rice crop quality and harvest amount. Furthermore, these rice crop quality and harvest mount can be predicted in the early stage of rice leaf grow. Therefore, rice crop quality and harvest amount becomes controllable.

Keywords

How to Cite this Article

Arai, K., Shigetomi, O., & Miura, Y. (2018). Artificial Intelligence based Fertilizer Control for Improvement of Rice Quality and Harvest Amount. International Journal of Advanced Computer Science and Applications, 9(10). https://doi.org/10.14569/IJACSA.2018.091008

Arai, Kohei, et al.. "Artificial Intelligence based Fertilizer Control for Improvement of Rice Quality and Harvest Amount." International Journal of Advanced Computer Science and Applications, vol. 9, no. 10, 2018, https://doi.org/10.14569/IJACSA.2018.091008.

@article{Arai2018,
  title     = {Artificial Intelligence based Fertilizer Control for Improvement of Rice Quality and Harvest Amount},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {9},
  number    = {10},
  year      = {2018},
  publisher = {The Science and Information Organization},
  author    = {Kohei Arai and Osamu Shigetomi and Yuko Miura},
  doi       = {10.14569/IJACSA.2018.091008},
  url       = {https://doi.org/10.14569/IJACSA.2018.091008}
}

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