Prediction of Eucalyptus grandis chemical compounds in a climate change context using hyperspectral imaging

The study of wood chemistry to explain the response of trees to climate variation is efficient for retrospective analysis of changes induced in wood during the process of adaptation to seasonal variations. Hyperspectral imaging (HSI) in near infrared could be useful for prediction of several wood chemical components. The objective is understand how water constraints influence wood formation. Wood disks of E. grandis clone from six treatments (100% and 65% of rainfall crossed with potassium and sodium fertilizations) were sampled. HSI were obtained on transversal section of the disks using a line scan hyperspectral camera from 1000-2500 nm with a pixel size of 625 x 625 µm. For calibration, were selected 60 wood solid samples from an Eucalyptus collection, which were measured the total extractive values. HSI or these samples were acquired from transversal section with the same camera. We regressed the mean spectra for each sample with extractives values by Partial Least Square Regression. Due to the model, the total extractives for each pixel to produce an image for the wooden disks were predicted. Based on them, the total extractive distribution according to growth conditions were compared. revealing that trees under stress conditions show a higher heterogeneous chemical profile from the pith to bark. Eucalyptus demonstrates sensitive precipitation variations. with rapid growth and considerable increase in DBH during rainy seasons and the reverse in drought. Consequently, is possible to discriminate different patterns of chemical compound distribution according to the growth conditions.