Abstract

An artificial neural network was used to control for leaf water absorption during the estimation of lignin-cellulose and nitrogen concentration from the reflectance spectra of fresh slash pine needles. The inputs to the neural network comprised of spectral indices based upon wavelengths at the centre or wings of known absorption features of the biochemical compounds of interest. The results indicate that the neural network provides more accurate estimates of water concentration than when using spectral indices alone. More importantly, lignincellulose concentrations were estimated with an accuracy of around 3 per cent relative to mean value. However, an accuracy of only 24 per cent relative to mean value was achieved for estimates of nitrogen concentration.