Total views : 196
Mobile aRCee Checker an Application of Rice and Corn Checker for Nutrient Deficiency through Leaf Coloration
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 leaf samples are extracted and may take a week for the results and not suitable for determining nitrogen in small area.
Leaf Checker, Leaf Color Chart, Mobile Application, Pattern Recognition, Rice and Corn Deficiency, Soil Fertility.
- Padmavathi K, Thangadurai K. Implementation of RGB and grayscale images in plant leaves disease detection – comparative study. Indian Journal of Science and Technology.2016 Feb; 9(6):1–6.
- Garg P, Kumar D. Pattern recognition using normalized feature vectors analysis. Indian Journal of Science and Technology. 2016 Jul; 9(25):1–6.
- Vebhute V , Anup A . Application of image processing in agriculture: a survey. International Journal of Computers Application. 2012; 52(2):34–40.
- Arivazhagan S, Shebiah SN, Ananthi S, Varthini SV. Detection of unhealthy region of plant leaves and classification of plant leaf diseases using texture features. Agricultural Engineering International: CIGR Journal. 2013 Mar; 15(112):1–7.
- What is mobile image processing [Internet]. 2015 [cited 2015 Oct 26]. Available from: http://www.wisegeek.com/ what-is-mobile-image-processing.htm.
- John ES. Nutrient deficiencies and application injuries in field crops. Extension and Outreach Publications. Book 89; 2010.
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.