14Fourier Transform Infrared (FTIR) spectroscopic data was used to classify wood samples from nine 15 species within the Fagales and Malpighiales using a range of multivariate statistical methods.
16Taxonomic classification of the family Fagaceae and Betulaceae from Angiosperm Phylogenetic 17 System Classification (APG II System) was successfully performed using Supervised Pattern 18Recognition techniques. A methodology for wood sample discrimination was developed using both 19 sapwood and heartwood samples. Ten and eight biomarkers emerged from the dataset to 20 discriminate order and family, respectively. In the species studied FTIR in combination with 21Multivariate analysis highlighted significant chemical differences in hemicelluloses, cellulose and 22 guaiacyl (lignin) and shows promise as a suitable approach for wood sample classification. 23
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
In this contribution, we present findings on biosorption of Cu (II) ions using novel alkali-treated nopal fibres. The biosorption data at equilibrium were fitted to several isotherm models and the biosorbent was characterized by XRD and SEM–EDX. The biosorption mechanism was investigated using a holistic approach of pH shifts, apparent colour variations and changes in the concentration of Cu(II) and dissolved hard ions (calcium and magnesium) in the Cu(II) solution. The correlation between the colour, XRD analysis, pH shifts and hard cations released from the biosorbent into the solution suggested the existence of two crystal formations, malachite and moolooite, in what appears to be a microprecipitation mechanism via reactive crystallization. The role of magnesium during the transformation of malachite into moolooite during the copper binding mechanism is analysed. Magnesium cations were released into the solution during malachite growth but were taken up from the solution during the moolooite crystal growth phase. The shift of the molar ratio Mg/Ca was located between the two inflexion points of the crystal growth transition. This specific location at the sorption isotherm was correlated with the colour evolution by a linear discriminant model confirming its association with the polymorphs.
Graphic abstract
The authorship has changed: Wanawan Pragot regrettably published the work that she carried out during her Ph.D. at the University of Aberdeen under the supervision of Waheed Afzal where this work had been assisted by (then) post-doc Ara Carballo-Meilan and (then Ph.D. student) Lewis McDonald. Wanawan Pragot regrets her action and wants to correct it. She notes that Chaiwat Photong helped her in proofreading the manuscript before she submitted. We believe that the contribution of Chaiwat Photong does not merit being the first author. The revised order and new additions reflect the contributions.The Acknowledgment and Author contributions have also been revised as given here.
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