Authors: Mario FranciscoFernández Javier TarríoSaavedra Salvador Naya Jorge LópezBeceiro Ramón Artiaga
Publish Date: 2016/11/02
Volume: 127, Issue: 1, Pages: 499-506
Abstract
The aim of this study is to statistically identify and distinguish wood samples corresponding to different areas of annual rings in trees of temperate regions using the corresponding thermogravimetric TG and their first TG derivative DTG curves and specifically to verify whether late and early wood chestnut samples are different with statistical significance taking into account their TG and DTG curves These significant differences are sought by applying statistical procedures based on functional data analysis FDA such as the functional ANOVA and the FDA classification methods Each TG curve is firstly smoothed using the local polynomial regression estimator and its first derivative is estimated Then functional ANOVA based on random projections RP is used to identify significant differences between TG or DTG curves of early and late wood samples In order to know the extent of the differences between early and late wood samples they are discriminated and the correct classification proportion obtained by employing a kernel nonparametric functional data analysis technique based on the Bayes rule as well as functional generalized linear models and functional generalized additive models allowing to classify materials using more than one type of thermal curves simultaneously The results are compared with those obtained using some classical multivariate supervised classification methods linear discriminant analysis naive Bayes NBC and quadratic classification QDA The partial least squares PLS dimension reduction procedure was previously applied to the TG curves in order to employ these multivariate methods The application of RP ANOVA shows significant differences between late and early wood regarding mass loss and mass loss rate under combustion The use of PLS multivariate methods or FDA classification approaches applied to the TG and DTG curves allows to distinguish very accurately between late and early wood The proposed method could be applied to other species to identify thermooxidative differences combined with other experimental methods to find their chemical and physical causes
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