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.