84 Matsumoto et al.: Evaluation of Compressive Strength of Decayed Wood in Magnolia obovata In the present study, a significant correlation between CS and holocellulose contents in wood decayed by the brown rot fungus was obtained. In general, the strength of decayed wood decreases because brown rot fungi decompose carbohydrates in the wood cell wall (Kollmann and Côté 1984; Schwarze et al. 2000; Schmidt 2006). Thus, in the present study, the reduc- tion of CS in wood decayed by the brown rot fungus seemed to be caused by the decomposition of cellulose and hemicel- luloses in the wood cell wall. There were significant positive correlations among CS, holocellulose, and α-cellulose in white rotted wood. As explained before, white rot fungi decompose cellulose, hemicellulose, and lignin at the same rate (Koll- mann and Côté 1984; Schwarze et al. 2000; Schmidt 2006). Therefore, in the present study, the CS of white rotted wood was greatly affected by carbohydrate contents. Compared to the brown rot and white rot fungi, in soft rotted wood, large amounts of the main wood chemical components in the cell wall remained. Thus, no significant correlations between CS and chemical components were obtained for soft rotted wood. Table 1. Correlation coefficients among compressive strength, weight loss, and chemical components of decayed wood in Magnolia obovata. Factor 1 Factor 2 CS Weight loss Klason lignin Holocellulose α-cellulose z Significance at 5% level. y Significance at 1% level. CS = Compressive strength measured by Fractometer; brown-rot decay by F. palustris; white-rot decay by T. versicolor; soft-rot decay by C. globosum; ns = no significance; n = number of samples. CONCLUSION Figure 4. Time-course changes in chemical components of wood core samples of Magnolia obovata. Relationships Among Compressive Strength, Weight Loss, and Chemical Components of Decayed Wood Table 1 shows correlation coefficients among the CS, weight loss, and chemical components of decayed wood. In general, when the wood was decayed by fungi, the wood strength decreased as the weight loss ratio increased. Thus, a negative relationship was recognized between weight loss ratio and strength in decayed wood (Mizumoto 1966; Doi and Nishimoto 1986; Curling et al. 2002). In the present study, high correlation coefficients between weight loss ratio and CS were found in brown rot (r = -0.909) and white rot (r = -0.918). These results correspond to those of previous studies (Mizumoto 1966; Doi and Nishimoto 1986; Curling et al. 2002). Nearly the same values were observed for weight loss ratio and CS in wood decayed by the soft rot fungus. ©2010 International Society of Arboriculture Sever decay of tree stems can occur unexpectedly by wind and other environmental factors. For preventing unexpected tree fell- ing, urban tree managers should know the degree of decay of trees. In addition, accuracy of decay diagnosis of trees should be improved. In the present study, we clarified the relationships among CS, weight loss ratio, and chemical components in de- cayed Magnolia wood by three different types of fungi in labora- tory condition. The data obtained would help further more ac- curate diagnosis of decay in standing trees. In addition, decrease of CS was recognized at relatively low values of weight loss ra- tio, indicating that Fractometer can detect the decrease of CS at relatively early stage of decay. Increase of weight loss ratio and decrease of CS might be caused by cell wall degradation by fun- gus. Further research is needed in order to clarify the relationship between the cell wall degradation observed by microscopy and the degree of wood decay. Although, we used only one species, relationships among CS, weight loss ratio, and chemical com- ponents might differ among the species. Thus, further research is needed for other species. By combining the results of future studies with those of the present study, a more accurate diagnosis of decay in a standing tree for many species would be obtained. Brown-rot (n = 5) -0.909z 0.696ns 0.903z 0.864ns White-rot (n = 5) -0.918y 0.768ns 0.916z 0.890z Soft-rot (n = 5) -0.562ns 0.488ns 0.508ns 0.672ns
March 2010
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