Rice Crop Quality Evaluation Method through Regressive Analysis between Nitrogen Content and Near Infrared Reflectance of Rice Leaves Measured from Near Field
Journal Title: International Journal of Advanced Research in Artificial Intelligence(IJARAI) - Year 2013, Vol 2, Issue 5
Abstract
Rice crop quality evaluation method through regressive analysis between nitrogen content in the rice leaves and near infrared reflectance measurement data from near field, from radio wave controlled helicopter is proposed. Rice quality dependency on nitrogen of chemical fertilizer and water supply condition is evaluated. Also homogeneity of the rice crop quality in the paddy fields is evaluated. Furthermore, influence due to shadow on near infrared reflectance of rice leaves measured from near field is taken into account in the rice crop quality evaluation processes
Authors and Affiliations
Kohei Arai
Keywords
Related Articles
- EP ID EP114886
- DOI -
- Views 102
- Downloads 0
Digital Library of Expert System Based at Indonesia Technology University
Digital library is a very interesting phenomenon in the world of libraries. In this era of globalization, the digital library is needed by students, faculty, and the community in the search for quick reference thro...
An Implementation of Outpatient Online Registration Information System of Mutiara Bunda Hospital
Outpatient care is one of the medical services in Mutiara Bunda hospital. The management of outpatient registration of Mutiara Bunda Hospital used conventional way. Within 1 hour serving, 5 patients were enrolled w...
Silent Speech Recognition with Arabic and English Words for Vocally Disabled Persons
This paper presents the results of our research in silent speech recognition (SSR) using Surface Electromyography (sEMG); which is the technology of recording the electric activation potentials of the human articul...
A Rank Aggregation Algorithm for Ensemble of Multiple Feature Selection Techniques in Credit Risk Evaluation
In credit risk evaluation the accuracy of a classifier is very significant for classifying the high-risk loan applicants correctly. Feature selection is one way of improving the accuracy of a classifier. It provide...
Comparison between Rayleigh and Mie Scattering Assumptions for Z-R Relation and Rainfall Rate Estimation with TRMM/PR Data
Comparison of the rain rate estimated with the assumptions of Rayleigh and Mie scattering is made. We analyzed the different relationships between the radar reflective factor and rain rate (so-called Z-R relationship) wi...