Android Based Mobile Application to Estimate Nitrogen Content in Rice Crop

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2016 by IJCTT Journal
Volume-38 Number-2
Year of Publication : 2016
Authors : Navdeep Kaur, Derminder Singh
  10.14445/22312803/IJCTT-V38P116

MLA

Navdeep Kaur, Derminder Singh "Android Based Mobile Application to Estimate Nitrogen Content in Rice Crop". International Journal of Computer Trends and Technology (IJCTT) V38(2):87-91, August 2016. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
The color of leaf corresponds to nitrogen deficiency status of that particular crop, farmers compares color of leaf with Leaf Color Chart (LCC) in order to estimate the need of nitrogen fertilizer of their crop. However the ability to compare leaf color with the LCC varies from person to person that affects the accuracy of final result. This paper proposes a mobile-device based application called "mlcc". Main idea is to simultaneously capture and process a 2-D color image of rice leaf, thus eliminating the expensive external components, reducing the human color perception and results in achieving high color accuracy. This android-based application can be correctly identified all the important 6 green color levels of rice leaf.

References
[1] Houshmandfar A and Kimaro A (2011) Calibrating the leaf color chart for rice nitrogen management in Northern Iran. African J Agric Res 6: 2627-33.
[2] Islam M S, Bhuiya M S U and Rahman H (2009) Evaluation of SPAD and LCC Based Nitrogen Management in rice. Bangladesh J Agril Res34(4): 661-72.
[3] Kaur G, Din S and Brar A S (2014) Design and Development of Software for the Implementation of Image Processing Approach for Leaf Area Measurement. Int J Comp Sci InfoTech 5(3): 4793-97.
[4] Kaur S and Singh D (2015) Geometric Feature Extraction of Selected Rice Grains using Image Processing Techniques. Int J Comp Appl124(8): 41-46.
[5] Pandurng J A and Lomte S S (2015) Digital Image Processing Applications in Agriculture: A Survey. Int J Adv Res Comp Sci Software Engg5(3): 622-24.
[6] Tewari V K, Arudra A K, Kumar S P, Pandey V and Chandel N S (2013) Estimation of plant nitrogen content using digital image processing pp.15.

Keywords
Image processing, Leaf color chart, Android studio, digital camera, rice field.