DETERMINATION OF CARBON FRACTION AND NITROGEN CONCENTRATION IN TREE FOLIAGE BY NEAR-INFRARED REFLECTANCE - A COMPARISON OF STATISTICAL-METHODS

Further evaluation of near infrared reflectance spectroscopy as a meth od for the determination of nitrogen, lignin, and cellulose concentrat ions in dry, ground, temperate forest woody foliage is presented. A co mparison is made between two regression methods, stepwise multiple lin ear regression and partial least squares regression. The partial least squares method showed consistently lower standard error of calibratio n and higher R(2) values with first and second difference equations. T he first difference partial least squares regression equation resulted in standard errors of calibration of 0.106%, with an R(2) Of 0.97 for nitrogen, 1.613% with an R(2) of 0.88 for lignin, and 2.103% with an R(2) of 0.89 for cellulose. The four most highly correlated wavelength s in the near infrared region, and the chemical bonds represented, are shown for each constituent and both regression methods. Generalizabil ity of both methods for prediction of protein, lignin, and cellulose c oncentrations on independent data sets is discussed. Prediction accura cy for independent data sets and species from other sites was increase d using partial least squares regression, but was poor for sample sets containing tissue types or laboratory-measured concentration ranges b eyond those of the calibration set.