PI: Per Persson
CoPI: Björn Sundberg
Staff: András Gorzsás, postdoc
Understanding the chemical composition of wood is essential for many areas of the research. In addition to revealing chemical differences between cell types and tissues, it helps the identification of the functions and effects of genes and environmental factors, such as seasonal changes, stress, etc. There are several ways to obtain information about the chemistry of wood, ranging from extractives to spectroscopic methods, such as NMR and FTIR. The advantage with FTIR spectroscopy is that various sample forms can be used (freeze-dried and powderised samples as well as different sections); it is fast, inexpensive and non-destructive. Thus, it is particularly suited for in situ analysis. Although determining the differences in chemistry among various samples is very valuable in itself, to be able to localise these differences is even more desirable. In that case, the changes caused by the modification of a gene or by environmental/stress factors, as well as the results of natural biological variations between and within cell types and tissues can be localised and attributed to certain areas or cells within the plant. Problems with the resolution of traditional detectors and "classical" spectral evaluation methods (integration), however, limit the applicability of the technique. Thus, a high resolution focal plane array (FPA) detector and multivariate data analysis are required. In addition, observed changes in chemistry should be further investigated and confirmed with additional methods, such as NMR or MS, to obtain an all-round view.
To develop a new method utilizing high resolution FTIR microspectroscopy with an FPA detector and multivariate data analysis to enable the routine analysis of the chemical composition of a wide range of wood samples. In connection, a new piece of software should be developed, which uses multivariate data analysis to identify spectral differences and map these differences across a sample. As a result, changes in chemistry could be localized with high spatial resolution and assigned to specific areas or cell types of a wood section. Images correlating this chemical variation with visual photographs of the sample can thus be obtained. Whenever possible, spectral differences should also be traced back to chemical differences in an effort to identify the change in composition that results in them. Since FTIR alone may not always provide the necessary information to do this, data from other spectroscopic methods, such as NMR and MS, should also be used. A compilation of all data will be created (FuncFiber 100 database). The method developed should be general and applicable in all cases where chemical changes detectable by FT-IR occur, including natural differences (biology, environmental and stress factors), mutations, fungal or bacterial infections, etc. This would help to pinpoint the location (and determine the nature) of the altered composition.