Leaf anatomical parameters such as leaf mass per area (LMA) and biochemical composition can be used as
indicators of leaf photosynthetic capacity. The aims of this study are to evaluate the potential of reflectance
spectroscopy of fresh leaves for assessing and predicting various parameters, anatomical (LMA and tissue
thickness) and biochemical (nitrogen concentration). This paper describes results obtained with fresh leaves of
holm oak (Quercus ilex), an evergreen oak that is widely distributed from mesic to xeric habitats in the
Mediterranean. Fresh leaves (560) were collected over 3 yr at six different sites, from the top to the bottom of the
canopy. The reflectance of each leaf was obtained within 1 h of sampling with an NIRSystems 6500
spectrophotometer over the range 400–2500 nm. LMA was determined for all samples; biochemical and
anatomical measurements were conducted over representative subsample populations of 92 and 87 leaves,
respectively. Stepwise regression calibrations and partial least squares (PLS) calibrations were developed and
compared with different spectral regions and mathematical treatments. Calibration equations had high coefficients
of determination (r2 ranging from 0.94 for nitrogen to 0.98 for LMA and tissue thickness). The PLS regressions
gave better results than stepwise regressions for all parameters studied. Compared with regressions calculated on
raw spectral data, calculations on second derivatives of spectra improved results in all cases. The use of scatter
corrections also improved results. These results show that visible and near-infra red reflectance can be used for
accurately predicting anatomical parameters and the nitrogen concentration of fresh holm oak leaves. The results
support the suggestion that high spectral resolution imaging spectrometry can be a useful tool for assessing
functional processes in forest ecosystems.