Abstract
Candeia [Eremanthus erythropappus (DC.) MacLeish], a Brazilian tree species, is being threatened by indiscriminate logging because the essential oil present in its wood has economic importance. The aim of this study was to develop a near infrared spectroscopic model for estimating the essential oil content in E. erythropappus wood to select trees with a high amount of essential oil before harvesting them. Essential oil from 103 wood powders was extracted via hydrodistillation. The values were calculated as the ratio between the mass of essential oil extracted and the oven dry mass of wood, and correlated to the NIR spectra recorded from the wood powders. Statistics associated with the predictive models have demonstrated that NIR has the potential to be a fast and feasible method to replace standard procedures for selecting trees with a high essential oil content. The NIR-based predictions in an independent validation set yielded a high correlation (r = 0.89) with the laboratory-determined values for essential oil content in E. erythropappus wood. This NIR model can be applied to guide wood managers for selecting high-oil-content trees before harvesting them and for developing sustainable strategies for industrial utilisation of Candeia populations.
© 2015 The Author(s)
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