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DOI: 10.14569/IJARAI.2015.041003
PDF

Estimation of Rice Crop Quality and Harvest Amount from Helicopter Mounted NIR Camera Data and Remote Sensing Satellite Data

Author 1: Kohei Arai
Author 2: Masanoori Sakashita
Author 3: Osamu Shigetomi
Author 4: Yuko Miura

International Journal of Advanced Research in Artificial Intelligence(IJARAI), Volume 4 Issue 10, 2015.

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Abstract: Estimation of rice crop quality and harvest amount in paddy fields with the different rice stump density derived from helicopter mounted NIR camera and remote sensing satellite data is made. Using the intensive study site of rice paddy fields with managing, estimation of protein content in rice crop and nitrogen content in rice leaves through regression analysis with Normalized Difference Vegetation Index: NDVI derived from camera mounted on a radio-control helicopter is made together with harvest amount of rice crops. Through experiments at rice paddy fields which is situated at Saga Prefectural Agriculture Research Institute SPRIA in Saga city, Japan, it is found that protein content in rice crops is highly correlated with NDVI which is acquired with visible and Near Infrared: NIR camera mounted on radio-control helicopter. It also is found that nitrogen content in rice leaves is correlated to NDVI as well. Protein content in rice crop is negatively proportional to rice taste. Therefore rice crop quality can be evaluated through NDVI observation of rice paddy field.

Keywords: Rice Crop; Rice Leaf; Nitrogen content; Protein content; NDVI

Kohei Arai, Masanoori Sakashita, Osamu Shigetomi and Yuko Miura, “Estimation of Rice Crop Quality and Harvest Amount from Helicopter Mounted NIR Camera Data and Remote Sensing Satellite Data” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 4(10), 2015. http://dx.doi.org/10.14569/IJARAI.2015.041003

@article{Arai2015,
title = {Estimation of Rice Crop Quality and Harvest Amount from Helicopter Mounted NIR Camera Data and Remote Sensing Satellite Data},
journal = {International Journal of Advanced Research in Artificial Intelligence},
doi = {10.14569/IJARAI.2015.041003},
url = {http://dx.doi.org/10.14569/IJARAI.2015.041003},
year = {2015},
publisher = {The Science and Information Organization},
volume = {4},
number = {10},
author = {Kohei Arai and Masanoori Sakashita and Osamu Shigetomi and Yuko Miura}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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