Measuring the drying checks requires a lot of time and effort, and the judgment of the drying checks differs depending on the person. Semi-automatic measurement methods based on image processing in previous studies required special treatment of specimens, and has not solved the problem of time-consuming. In this study, to develop a convenient measurement method to quantify drying checks in sawn timber, we created a Convolutional Neural Network (CNN) that can discriminate drying checks in cross-sectional images pixel by pixel. The CNN was trained on 850 cross-sectional images (cross-sectional dimension 105 × 105 mm) of sugi boxed-heart square timber acquired by a flatbed scanner, and a testing set of 150 images evaluated its performance. The results showed that the Root Mean Squared Error (RMSE) for total check area and total check length were 11.8 mm² and 28.4 mm, respectively. In especially, the area was found to be predictable with high accuracy. The low accuracy of length prediction compared to area was attributed to the loss of small checks information when the images were compressed and input into the CNN. It was necessary to change the method of inputting images to the CNN to improve the prediction accuracy.

In Japan, there have been few studies on the promotion of wood usage using social scientific methods. In this study, we investigated the association of consumers' attributes and values with their preferences for wood and the intention to use wood products, focusing on naturalistic/urbanistic values, which are considered useful in the field of architectural environment studies. The t-tests, analyses of variance, and multiple regression analyses were conducted using the participants' attributes, childhood and current residential area, as well as naturalistic/urbanistic values as independent and explanatory variables. In addition, we employed their preferences for wood and the intention to use wood products (building materials, furniture, tableware and accessories) as dependent and objective variables. The results suggested that, (1) people with more naturalistic values have a higher preference for wood and a higher intention to use wood products, (2) age and gender are partially related to the preference for wood and the intention to use wood products, and (3) people whose childhood residence was in an urban suburb area showed a lower intention to use building materials, furniture, and tableware. These findings should be useful for more effective promotion of the usage of wood.

The bending performance of wood can be assessed through mechanical testing, and parameters such as Young's modulus and strength are generally obtained. Although these parameters are fundamental knowledge for researchers and engineers, it may be difficult to understand for individuals lacking expertise in mechanics. Recently, interest has been growing among non-specialists in understanding the mechanical performance of wood harvested from the forests they manage. Looking around the cases in other industrial fields, there are many indicators which is represented with one value by reducing various monitoring result, and they support the individuals to safety and healthy life. Consequently, this study aimed to create a novel parameter facilitating a more intuitive understanding of bending performance. The newly proposed parameter was derived from the first principal component score obtained through a principal component analysis using Young's modulus and bending strength. The parameter enabled easy comparison of mechanical performance between tested data and literature value.

The Japan Wood Research Society compiled two glossaries of terms used in wood science, especially in the research fields of wood anatomy and wood quality. The two glossaries, “Glossary in Wood Anatomy” and “Glossary in Wood Quality”, are revised versions of formerly compiled glossaries, which were published in 1975 and 1972, respectively. This paper describes the details of the revision in the process and the difference from the former versions. We hope the two glossaries will be used by many colleagues in broader context and can contribute further development of wood science.