Simple linear regression and reflectance sensitivity analysis used to determine the optimum wavelengths for the nondestructive assessment of chlorophyll in fresh leaves using spectral reflectance

ABSTRACT. The accuracy of nondestructive optical methods for chlorophyll (Chl) assessment based on leaf spectral characteristics depends on the wavelengths used for Chl assessment. Using spectroscopy, the optimum wavelengths (OW) for Chl assessment were determined by using 1-year-old almond (Prunus dulcis), poplar (Populus trichocarpa · P. deltoides), and apple (Malus ·domestica) trees grown at different rates of nitrogen fertilization to produce leaves with different Chl concentrations. Spectral reflectance of leaf discs was measured using a spectroradiometer (300 to 1100 nm at 1-nm intervals), and total Chl concentration in leaf discs was extracted and determined in 80 % acetone. The OW for nondestructive Chl assessment by reflectance spectroscopy was estimated using 1) the coefficient of determination (r2) from simple linear regression; 2) reflectance sensitivity analysis (a measure for changes of spectral reflectance on unit change in leaf Chl concentration); and 3) the first spectral derivative method. Our results indicated that the first derivative method can be used only to identify OW in the red edge region of the spectrum, whereas r2 and reflectance sensitivity analysis can be used to identify the OW in both the red edge and green regions. Our results indicate that using simple linear r2 in combination with reflectance sensitivity and/or the first derivative analyses is a reliable method for determining OW in plant leaves tested. Two optimum wavebands with larger r2, smaller root mean square error, and higher reflectance sensitivity were found in red edge (700 to 730 nm) and green (550 to 580 nm) regions, respectively, which can be used as common OW for Chl reflectance assessment in poplar, apple, an