33 B. Neyses and O. Hagman: Identifying suitable wood species for wooden products with multivariate data analysis holztechnologie 56 (2015) 2 © IHD, Dresden Introduction Despite or maybe even due to its long history as a construction material wood is still very popular. Perhaps it will become even more popular in the future. Among others, one of the main reasons for this is the possibility to use the material in a sustainable way, unlike metal or various types of plastics. However, in many cases wood is harvested and used irres- ponsibly. Relentless deforestation without subsequent refo- restation is the standard in numerous countries around the world (Laurance, 1999). This is partially caused by the high demand for certain species with a limited availability. An example is the guitar industry. Species like mahogany, rose- wood or ebony were and are still used for guitar bodies, necks and fretboards, even though they are vulnerable or critically endangered. Even if endangered species are not used, the wood choice is often not justiiable from an objective point of view. In many cases only a few species are considered for application. Alder for example, is a very popular wood species for electric guitar bodies. If people are asked why, some say because Leo Fender – who was the founder of the Fender Musical Instruments Cooperation – used it already decades ago. As a consequence, it must be good. Allegedly, In many cases only few wood species are used or even considered for any given wooden product, even though there are hundreds of wood species available. The objective of this project was the development of a time efficient and structured method to identify the most suitable wood species for wooden products, based on a set of required material properties. This goal was achieved by applying multivariate data analysis. The method was based on a dataset consisting of commercial- ly available wood species represented by many different properties. The scores and loadings of the multivariate data analysis method Principal Component Analysis (PCA) were used to identify the wood species with the most fitting property combinations for the product in question. Applying the method to an example case resulted in several plausible alternatives to the commonly used wood species. It is possible to apply the method to any wooden product by determining the set of required properties. Keywords: Wood properties, product development, wood choice Identifying suitable wood species for wooden pro- ducts with multivariate data analysis Benedikt Neyses, Olle Hagman he started using alder just because it was cheap and available (Fender, 2014). Similar behaviour most likely prevails regar- ding many other wooden products. This is contrasted by the fact that hundreds of wood species from all around the world are commercially available, many of them not endangered in any way (Kribs, 1968). The question is: How to provide people with a tool to identify the most suitable wood species for any wooden product in a quantiiable and comprehensive way that is also easy and fast to apply. The objective of this research project was the development of a wood identiication tool which is able to achieve this. The tool was based on the application of principal components analysis (PCA), a multivariate data analysis (MVDA) method. In general, PCA is utilized to extract and visualize useful in- formation from large datasets, in particular those with many observations and variables (Eriksson et al., 2006). Giving people the means to make a profound material choices in an easy and quick way has the potential to enhance the qua- lity and variety of wooden products while supporting respon- sible utilization of timber at the same time. Review: