Title of article
Prediction of SPAD chlorophyll meter readings using remote sensing technique
Author/Authors
Teoh, C. C. Malaysian Agricultural Research and Development Institute (MARDI), Headquarters - Mechanization and Automation Research Centre, Malaysia , Abu Hassan, D. Malaysian Agricultural Research and Development Institute (MARDI), Headquarters - Mechanization and Automation Research Centre, Malaysia , Radzali, M. Muhammad Malaysian Agricultural Research and Development Institute (MARDI), Headquarters - Strategic Resources Research Centre, Malaysia , Jafni, J. J. Malaysian Agricultural Research and Development Institute (MARDI), Headquarters - Mechanization and Automation Research Centre, Malaysia
From page
127
To page
136
Abstract
A method using unmanned airborne vehicle (UAV) and image processing technique to enable prediction of SPAD chlorophyll meter readings was developed. Relationships between SPAD readings and R, G, B, R/(R+G+B), G/(R+G+B), and B/(R+G+B) values were analysed. The R/(R+G+B) values indicate the highest correlation with SPAD readings with r^2 value of –0.9695 and a SPAD reading prediction model was developed from the relationship analysis. The prediction model is capable to predict SPAD reading with average accuracy value of 89%. A SPAD reading map was generated by converting the spectral reflectance values into SPAD readings using the prediction model. This SPAD reading map was classified into high, medium and low levels of SPAD values for easy identification of N stress levels in the paddy fields
Keywords
rice plant , SPAD reading prediction , unmanned airborne vehicle , remote sensing
Journal title
Journal of Tropical Agriculture and Food Science
Journal title
Journal of Tropical Agriculture and Food Science
Record number
2576963
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