A specific case in the classification of woods by FTIR and chemometric: discrimination of Fagales from Malpighiales

Fourier transform infrared (FTIR) spectroscopic data was used to classify wood samples from nine species within the Fagales and Malpighiales using a range of multivariate statistical methods. Taxonomic classification of the family Fagaceae and Betulaceae from Angiosperm Phylogenetic System Classification (APG II System) was successfully performed using supervised pattern recognition techniques. A methodology for wood sample discrimination was developed using both sapwood and heartwood samples. Ten and eight biomarkers emerged from the dataset to discriminate order and family, respectively. In the species studied FTIR in combination with multivariate analysis highlighted significant chemical differences in hemicelluloses, cellulose and guaiacyl (lignin) and shows promise as a suitable approach for wood sample classification

Application of chemometric analysis to infrared spectroscopy for the identification of wood origin

Chemical characteristics of wood are used in this study for plant taxonomy classification based on the current Angiosperm Phylogeny Group classification (APG III System) for the division, class and subclass of woody plants. Infrared spectra contain information about the molecular structure and intermolecular interactions among the components in wood but the understanding of this information requires multivariate techniques for the analysis of highly dense datasets. This article is written with the purposes of specifying the chemical differences among taxonomic groups, and predicting the taxa of unknown samples with a mathematical model. Principal component analysis, t-test, stepwise discriminant analysis and linear discriminant analysis, were some of the chosen multivariate techniques. A procedure to determine the division, class, subclass and order of unknown samples was built with promising implications for future applications of Fourier Transform Infrared spectroscopy in wood taxonomy classification

Isolating stem cells in the inter-follicular epidermis employing synchrotron radiation-based Fourier-transform infrared microspectroscopy and focal plane array imaging

Normal function and physiology of the epidermis is maintained by the regenerative capacity of this tissue via adult stem cells (SCs). However, definitive identifying markers for SCs remain elusive. Infrared (IR) spectroscopy exploits the ability of cellular biomolecules to absorb in the mid-IR region (\ensuremathλ = 2.5-25 \ensuremathμm), detecting vibrational transitions of chemical bonds. In this study, we exploited the cell's inherent biochemical composition to discriminate SCs of the inter-follicular skin epidermis based on IR-derived markers. Paraffin-embedded samples of human scalp skin (n = 4) were obtained, and 10-\ensuremathμm thick sections were mounted for IR spectroscopy. Samples were interrogated in transmission mode using synchrotron radiation-based Fourier-transform IR (FTIR) microspectroscopy (15 × 15 \ensuremathμm) and also imaged employing globar-source FTIR focal plane array (FPA) imaging (5.4 × 5.4 \ensuremathμm). Dependent on the location of derived spectra, wavenumber-absorbance/intensity relationships were examined using unsupervised principal component analysis. This approach showed clear separation and spectral differences dependent on cell type. Spectral biomarkers concurrently associated with segregation of SCs, transit-amplifying cells and terminally-differentiated cells of epidermis were primarily PO(2)(-) vibrational modes (1,225 and 1,080 cm(-1)), related to DNA conformational alterations. FPA imaging coupled with hierarchical cluster analysis also indicated the presence of specific basal layer cells potentially originating from the follicular bulge, suggested by co-clustering of spectra. This study highlights PO (2) (-) vibrational modes as potential putative SC markers