Relationship analysis between tree recognition and pyrolysis products based on 103 species by Py-GC/MS

This study systematically investigated the pyrolysis behaviors and composition characteristics of pyrolysis products based on 103 species of wood (covering 39 families and 68 genera) by using Py-GC/MS. The correlation between compositional distribution patterns and plant taxonomy was further evaluated via principal component analysis (PCA) and hierarchical cluster analysis (HCA). The results demonstrated that the effect of pyrolysis temperature on product distribution was significantly greater than that of pyrolysis time. Different components exhibited characteristic reaction pathways and representative products as the temperature changed. A total of 172 pyrolysis products were detected in the pyrolysis products, among which 18 common products were present in over 95% of the wood samples. The study further revealed that pyrolysis behavior exhibited significant differences between gymnosperms and angiosperms, as well as at the family and genus levels. For example, gymnosperms were dominated by G-type lignin, while the Fagaceae family was characterized by the enriched anhydro sugars content. Multivariate statistical analysis (PCA and HCA) confirmed a strong correlation between the distribution of pyrolysis products and plant taxonomy. These findings were conducive to distinguishing different types of wood and provided fundamental data for identifying and differentiating tree species from the perspective of chemical fingerprints.