Extraction of REPs from leaves reflectance spectrum for estimation of chlorophyll content

Abstract

Abstract: The red edge parameters which include red edge amplitude, red edge position, red edge area and the reflectance of red edge position can be used as an indicator of stress and senescence of vegetation. Among these parameters, the red edge position (REP) is the best one to estimate tomato chlorophyll content according to statistical analysis. The REP is defined as the point of maximum slope at the 680 ~ 740nm region in a vegetation reflectance spectrum. In this research, the 6 algorithms could be used to extract the REP, and the quantitative relationships between REP on various algorithms and leaf chlorophyll status were analyzed, and then the prediction models of the chlorophyll content for each REP extraction algorithm were developed using Linear regression, Logarithmic regression, Power regression, Exponential regression and Quadratic polynomial regression. The result showed that the Logarithmic model of the Linear Extrapolation had the best accuracy and reliability. The calibration R-Square was 0.62 and the validation R-Square was 0.77 and the root mean squared error (RMSE) was 8.36.