TY - JOUR
T1 - Nondestructive measurement of microfibril angle of wood by using near-infrared spectroscopy
AU - Kojima, Miho
AU - Kurata, Yohei
AU - Abe, Hisashi
N1 - Publisher Copyright:
© 2025 The Author(s).
PY - 2025
Y1 - 2025
N2 - Fast-growing tree species, such as Eucalyptus, are used extensively in plantations for timber, but their mechanical properties are not well understood, especially the microfibril angle (MFA), which affects wood stiffness. MFA measurement is complex and expensive, but near-infrared spectroscopy (NIRS) offers a non-destructive alternative. This study aims to evaluate the effectiveness of NIRS in predicting MFA across different regions and environments. The results showed that NIRS could predict MFA, but the accuracy varied. In Brazil, higher prediction accuracy was observed when data from multiple regions were combined. In Laos, the presence of juvenile wood significantly decreased prediction accuracy. Combining data from multiple sites improved prediction accuracy, but decreased accuracy when juvenile wood was included. The study concludes that effective MFA prediction models must consider regional and environmental differences. Creating region-specific models is necessary for reliable wood quality assessment using NIRS. This research underscores the potential of NIRS as a practical tool for wood quality evaluation, highlighting the importance of accounting for factors such as wood maturity and environmental conditions in developing robust predictive models.
AB - Fast-growing tree species, such as Eucalyptus, are used extensively in plantations for timber, but their mechanical properties are not well understood, especially the microfibril angle (MFA), which affects wood stiffness. MFA measurement is complex and expensive, but near-infrared spectroscopy (NIRS) offers a non-destructive alternative. This study aims to evaluate the effectiveness of NIRS in predicting MFA across different regions and environments. The results showed that NIRS could predict MFA, but the accuracy varied. In Brazil, higher prediction accuracy was observed when data from multiple regions were combined. In Laos, the presence of juvenile wood significantly decreased prediction accuracy. Combining data from multiple sites improved prediction accuracy, but decreased accuracy when juvenile wood was included. The study concludes that effective MFA prediction models must consider regional and environmental differences. Creating region-specific models is necessary for reliable wood quality assessment using NIRS. This research underscores the potential of NIRS as a practical tool for wood quality evaluation, highlighting the importance of accounting for factors such as wood maturity and environmental conditions in developing robust predictive models.
KW - eucalyptus
KW - microfibril angle
KW - near-infrared spectroscopy
KW - non-destructive measurement
KW - reflectance
KW - wood property
UR - https://www.scopus.com/pages/publications/85219144336
U2 - 10.1139/cjfr-2024-0270
DO - 10.1139/cjfr-2024-0270
M3 - Article
AN - SCOPUS:85219144336
SN - 0045-5067
VL - 55
JO - Canadian Journal of Forest Research
JF - Canadian Journal of Forest Research
ER -