ESTIMATION AND VISUALIZAION OF NITROGEN CONTENT IN CITRUS CANOPY USING HYPERSPECTRAL IMAGERY

This study investigated the capability of hyperspectral imagery for estimating and visualizing the nitrogen content in citrus canopy. Fresh citrus leaf samples including the new, medium aged and old leaves were collected from a citrus orchard during the plant's vigorous vegetative growing season. Hyperspectral imageries were obtained for leaf samples in laboratory as well as for the whole canopy in the field with ImSpector V10E (Spectral Imaging Ltd., Oulu, Finland). The average spectral data for each leaf sample were extracted with ENVI software. The nitrogen content in each leaf sample was measured by the Dumas combustion method with the rapid N cube (Elementar Analytical, Germany). Simple correlation analysis and the two band vegetation index (TBVI) were used to develop the spectra data based nitrogen content prediction models. Results indicated that the model with the two band vegetation index (TBVI) based on the wavelengths 811 nm and 856 nm achieved the optimal estimation of nitrogen content in citrus leaves (R-2=0.6692). The canopy image for the identified TBVI was calculated, and the nitrogen content of the canopy was visualized by incorporating the model into the TBVI image. The results suggest the potential of hyperspectral imagery for the detection and diagnosis of nitrogen status in citrus canopy. This would provide valuable information for the implementation of individual tree-based fertilization schemes in precision orchard management practices.