Development of nitrogen fertilization dose prediction on rice field based on leaf color chart

Nitrogen (N) is one of the main nutrients for plant growth, as a major component of chlorophyll and proteins closely related to leaf color, growth, and crop yield. The efficiency of nitrogen fertilization is needed to increase rice productivity. Adequacy of N nutrient can be observed in the leaf’s color. The use of Leaf Color Chart (LCC) is one way to analyze the need for nitrogen fertilizer in the rice field. This research proposed the development tool to determine the greenish scale of rice leaves automatically and to give advice on the appropriate and optimal dose of nitrogen fertilizer to the rice field. In this study, Arduino Uno is functioned as a Processing Unit and integrated with TCS3200 color sensor as an input component to detect the greenish level of rice leaf color. By using this tool, the prediction of the needs of nitrogen in the rice field can be determined more effectively, not depending on one’s perception of the leaf’s color scale or different light intensity. The measurements show that the system has an average scale misidentification of 2%, therefore this system can be used as an alternative to determining the dose of nitrogen fertilizer according to the conditions of the plants and the desired harvest target can be achieved optimally.