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Research Article | Open Access |

Optimum Band and Band Combination for Retrieving Total Nitrogen, Water, Fiber Content in Tealeaves Through Remote Sensing Based on Regressive Analysis

Author 1: Kohei Arai
International Journal of Advanced Research in Artificial Intelligence (IJARAI) · Vol. 3, No. 3 · Published 2014

DOI: 10.14569/IJARAI.2014.030304

Abstract

Optimum band and band combination for retrieving total nitrogen, water and fiber content in tealeaves with remote sensing data is investigated based on regressive analysis. Based on actual measured data of total nitrogen, fiber and water content in tealeaves as well as remotely sensed visible to near infrared reflectance data with 5nm of wavelength steps and ASTER/VNIR onboard Terra satellite, regressive analysis is conducted. As the results, it is found that 1045nm is the best wavelength for retrieving total nitrogen content while 945nm is the best wavelength for fiber content retrieval. Also it is found that 545nm is the best wavelength for water content. On the other hand, it is found that 350 and 750nm wavelength combination is the best for estimation of total nitrogen content while 535 and 720 wavelength combination is the best for fiber content estimation. It also found that 545 and 760nm wavelength combination is the best for water content retrieval.

Keywords

How to Cite this Article

Arai, K. (2014). Optimum Band and Band Combination for Retrieving Total Nitrogen, Water, Fiber Content in Tealeaves Through Remote Sensing Based on Regressive Analysis. International Journal of Advanced Research in Artificial Intelligence, 3(3). https://doi.org/10.14569/IJARAI.2014.030304

Arai, Kohei. "Optimum Band and Band Combination for Retrieving Total Nitrogen, Water, Fiber Content in Tealeaves Through Remote Sensing Based on Regressive Analysis." International Journal of Advanced Research in Artificial Intelligence, vol. 3, no. 3, 2014, https://doi.org/10.14569/IJARAI.2014.030304.

@article{Arai2014,
  title     = {Optimum Band and Band Combination for Retrieving Total Nitrogen, Water, Fiber Content in Tealeaves Through Remote Sensing Based on Regressive Analysis},
  journal   = {International Journal of Advanced Research in Artificial Intelligence},
  volume    = {3},
  number    = {3},
  year      = {2014},
  publisher = {The Science and Information Organization},
  author    = {Kohei Arai},
  doi       = {10.14569/IJARAI.2014.030304},
  url       = {https://doi.org/10.14569/IJARAI.2014.030304}
}

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