WOOD RESEARCH Volume 69, Number 3, 2024
SENDER ALTANGEREL, IKUMI NEZU, JYUNICHI OHSHIMA, SHINSO YOKOTA, and FUTOSHI ISHIGURI

CHANGES IN WOOD QUALITY OF BETULA ERMANII LOGS BY HEATING TREATMENT

Logs of Betula ermaniiCham. were heated at a temperature inside the logs of 80°C for different heating durations of 0, 20, 40, and 60 h using a laboratory oven. After heating treatment, several wood qualities were examined, including residual stresses, moisture content, wood color, and physical and mechanical properties. The effects of the heating treatment duration on wood quality were analyzed using linear mixed-effect modeling. The developed models revealed that heating treatment affected residual stresses and wood color but not mechanical properties. The obtained results also suggest that a heating treatment duration of 20 h is sufficient to reduce residual stresses in B. ermaniilogs without reducing the physical and mechanical properties of wood

WOOD RESEARCH Volume 67, Number 5, 2022
EUN-SUK JANG and CHUN-WON KANG

Short notes: Can the physical properties of wood samples be predicted from photographs displayed on a monitor?

This study focused on evaluating the physical properties of wood from photographs displayed on a monitor. Sample photos of 475 hardwoods and their physical information were collected from a wood database. R, G, and B values were extracted from the wood photos using color picker software. Statistical techniques such as Pearson’s correlation coefficient and multiple regression analysis were applied to investigate relationships between wood color and physical properties. From results of Pearson’s correlation coefficient, R, G, and B values were most affected by specific gravity. In a multiple regression analysis, tree size, specific gravity, and modulus of rupture (MOR) were significant in the positive (+) direction by color (R, G, and B). On the other hand, modulus of elasticity (MOE) was significant in the negative (-) direction at the 1% level by color. The specific gravity of wood had the most significant effect on R, G, and B values in multiple regression analysis. In conclusion, the color and specific gravity of wood were related closely. Additionally, it is possible to predict the physical properties of wood from the R, G, and B values of a wood sample photograph displayed on a monitor. These results could provide useful information for wood researchers as well as wood exporters and importers.