Nitrogen Content Estimation of Rice Crop Based on Near Infrared (NIR) Reflectance Using Artificial Neural Network (ANN)

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Abstract

Nitrogen content is an important indicator used for monitoring and management of plant due to its role in photosynthesis, productivity as well as its effect on carbon and oxygen cycle. The research aimed at estimation of nitrogen content of rice crop based on Near Infrared (NIR) reflectance using Artificial Neural Network (ANN). ANN is a non-linear modeling tools based on statistical data. Nitrogen content was measured by laboratory analysis, meanwhile, its spectral reflectance of NIR (700 – 1075 nm) in the field was measured by using hand held spectroradiometer. Data were divided into 33 data training and 15 data testing using 3-fold cross validation. We found that organic molecules (nitrogen, water, etc) have specific absorption pattern in the NIR region. The experimental result shows that the comparison between measured and model estimation of Nitrogen content have RMSE of about 0.32. We conclude that NIR reflectance values can be used to predict nitrogen content using ANN method.

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