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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 |

Rice Crop Quality Evaluation Method through Regressive Analysis between Nitrogen Content and Near Infrared Reflectance of Rice Leaves Measured from Near Field

Author 1: Kohei Arai
International Journal of Advanced Research in Artificial Intelligence (IJARAI) · Vol. 2, No. 5 · Published 2013

DOI: https://doi.org/10.14569/IJARAI.2013.020501

Abstract

Rice crop quality evaluation method through regressive analysis between nitrogen content in the rice leaves and near infrared reflectance measurement data from near field, from radio wave controlled helicopter is proposed. Rice quality dependency on nitrogen of chemical fertilizer and water supply condition is evaluated. Also homogeneity of the rice crop quality in the paddy fields is evaluated. Furthermore, influence due to shadow on near infrared reflectance of rice leaves measured from near field is taken into account in the rice crop quality evaluation processes.

Keywords

How to Cite this Article

Arai, K. (2013). Rice Crop Quality Evaluation Method through Regressive Analysis between Nitrogen Content and Near Infrared Reflectance of Rice Leaves Measured from Near Field. International Journal of Advanced Research in Artificial Intelligence, 2(5). https://doi.org/10.14569/IJARAI.2013.020501

Arai, Kohei. "Rice Crop Quality Evaluation Method through Regressive Analysis between Nitrogen Content and Near Infrared Reflectance of Rice Leaves Measured from Near Field." International Journal of Advanced Research in Artificial Intelligence, vol. 2, no. 5, 2013, https://doi.org/10.14569/IJARAI.2013.020501.

@article{Arai2013,
  title     = {Rice Crop Quality Evaluation Method through Regressive Analysis between Nitrogen Content and Near Infrared Reflectance of Rice Leaves Measured from Near Field},
  journal   = {International Journal of Advanced Research in Artificial Intelligence},
  volume    = {2},
  number    = {5},
  year      = {2013},
  publisher = {The Science and Information Organization},
  author    = {Kohei Arai},
  doi       = {10.14569/IJARAI.2013.020501},
  url       = {https://doi.org/10.14569/IJARAI.2013.020501}
}

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