Seleção de clones de Eucalyptus para a produção de carvão vegetal e bioenergia por meio de técnicas univariadas e multivariadas

Abstract

This work aimed at using univariate and multivariate statistical techniques for selection and evaluation of Eucalyptus clones for the production of charcoal and bioenergy. Three Eucalyptus urophylla clones and four Eucalyptus grandis clones were used. Five trees of each clone were sampled in base-top direction. Diameter at breast height was measured in all trees. Total lignin, total extractives, ashes, holocellulose, carbon, hydrogen, nitrogen and sulfur contents were quantified in the wood, also basic and energetic density and carbon stock by volume and higher heating value. Univariate variance analyses were used and the Scott-Knott algorithm was used for clone grouping. Multivariate variance analyses of principal components and canonical variables were also made aiming to group clones in similar groups. The multivariate techniques were more efficient in grouping and selection of Eucalyptus clones. It was observed that total lignin content was of great importance in grouping. Clone U103 was considered the most appropriate for charcoal production and clones U059 and U221 were recommended mostly for bioenergy production.