Android-based rice leaf color analyzer for estimating the needed amount of nitrogen fertilizer

A mobile device is used to estimate the key color levels of the rice leaf.Environmental fluctuation is alleviated through our self-referencing approach.Additional key features include low cost and ease of implementation.Our field test shows high accuracy in identifying important leaf color levels.It is well accepted with thousands downloaded worldwide. As the color level of the rice leaf corresponds to the nitrogen status of rice in the field, farmers compare the rice leaf color to a leaf color chart (LCC) in order to estimate the amount of N fertilizer needed for the rice field. However, the ability of the farmers and degeneration of the LCC color affect the accuracy in reading the rice leaf color level. In this paper, we propose a mobile device-based rice leaf color analyzer called "BaiKhao" (means rice leaf in Thai). Our key idea is to simultaneously capture and process the two-dimensional (2-D) data of the color image from the rice leaf and its surrounding reference, thus eliminating expensive external components and alleviating the environmental fluctuation but yet achieving a high color-reading accuracy. Our field tests using an Android-based mobile phone show that all important leaf color levels of 1, 2, 3, and 4 can be correctly identified. Additional key features include low cost and ease of implementation with highly efficient distribution through the application store on the internet. There are currently 6096 downloads worldwide from September 2011 to March 2015.

[1]  J. R. Evans,et al.  Nitrogen and Photosynthesis in the Flag Leaf of Wheat (Triticum aestivum L.). , 1983, Plant physiology.

[2]  Jianliang Huang,et al.  Using Leaf Color Charts to Estimate Leaf Nitrogen Status of Rice , 2003 .

[3]  Li Shen,et al.  Point-of-care colorimetric detection with a smartphone. , 2012, Lab on a chip.

[4]  Alberto J. Palma,et al.  Using the mobile phone as Munsell soil-colour sensor: An experiment under controlled illumination conditions , 2013 .

[5]  Sarun Sumriddetchkajorn,et al.  Low-cost light-emitting-diode based leaf color meter for nitrogen status estimation in the rice field , 2010, SPIE/COS Photonics Asia.

[6]  R. Buresh,et al.  04 New Leaf Color Chart for Effective Nitrogen Management in Rice , 2005 .

[7]  Rafael Huertas,et al.  Colour variation in standard soil-colour charts , 2005 .

[8]  Surat Bualert,et al.  Variation of Net Radiation and Solar Spectrum in Thailand , 2013 .

[9]  Mahabub Hossain,et al.  Adoption of leaf color chart for nitrogen use efficiency in rice: Impact assessment of a farmer-participatory experiment in West Bengal, India , 2007 .

[10]  S. Sumriddetchkajorn,et al.  Mobile device-based digital microscopy for education, healthcare, and agriculture , 2012, 2012 9th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology.

[11]  Sarun Sumriddetchkajorn,et al.  BaiKhao (rice leaf) app: a mobile device-based application in analyzing the color level of the rice leaf for nitrogen estimation , 2012, Photonics Asia.

[12]  Alberto J. Palma,et al.  Mobile phone platform as portable chemical analyzer , 2011 .

[13]  Shoji Furuya,et al.  Growth Diagnosis of Rice Plants by Means of Leaf Color , 1987 .

[14]  Sarun Sumriddetchkajorn,et al.  Low-cost cell-phone-based digital lux meter , 2010, SPIE/COS Photonics Asia.

[15]  Javier Hernández-Andrés,et al.  Influence of Natural Daylight on Soil Color Description: Assessment Using a Color‐Appearance Model , 2011 .

[16]  Sarun Sumriddetchkajorn,et al.  Single-wavelength based rice leaf color analyzer for nitrogen status estimation , 2014 .

[17]  Sarun Sumriddetchkajorn,et al.  Cell phone-based two-dimensional spectral analysis for banana ripeness estimation , 2012 .

[18]  Manuel Melgosa,et al.  SPECTRORADIOMETRIC AND VISUAL COLOR MEASUREMENTS OF DISTURBED AND UNDISTURBED SOIL SAMPLES , 1995 .

[19]  L. Capitán-Vallvey,et al.  Use of the hue parameter of the hue, saturation, value color space as a quantitative analytical parameter for bitonal optical sensors. , 2010, Analytical chemistry.

[20]  Sarun Sumriddetchkajorn,et al.  Mobile-platform based colorimeter for monitoring chlorine concentration in water , 2014 .

[21]  Sarun Sumriddetchkajorn,et al.  Mobile device-based self-referencing colorimeter for monitoring chlorine concentration in water , 2013 .

[22]  Brian V. Funt,et al.  Irradiance-independent camera color calibration , 2014 .