Mobile aRCee Checker an Application of Rice and Corn Checker for Nutrient Deficiency through Leaf Coloration

Abstract

Objectives: This paper aims to develop an Android Based Application for Diagnosing Rice and Corn Nutrient Deficiency through Leaf and Pattern Recognition. An application designed to quantify Nitrogen, Potassium and Phosphorus deficiency in Rice and Corn crops through the image processing of their leaves. The application also provides farmers the ability to track the test results from multiple farm land. Methods/Statistical analysis: The research methods used in this paper are designing and developing. It designs a mobile application that can diagnose rice and corn nutrient deficiency through leaf color and pattern recognition. Moreover, they also developed an application that could calculate the amount of fertilizer needed in rice and corn nutrient deficiency. Findings: The results show that the application improved the process of diagnosing rice and corn nutrient deficiency. Thus, the survey result have positive feedback from the respondents. With this, it can calculate the accurate nutrient deficiency of rice and corn. It gives results and suggestions immediately that is directed to rice and corn crops. It is also capable of tracking the tests in a visual graph. Application/Improvements: The study is developed in order to address the problems in diagnosing rice and corn nutrient deficiency namely the inaccurate reading, the sampled leaf must be in a controlled light module, time consuming, destructive since the