Forests (Apr 2024)

Electrical Properties at Multi-Frequencies for Analysis of Physical and Anatomical Properties of Fast-Growing Standing Teak Trees at Various Ages

  • Dyah Ayu Agustiningrum,
  • Iskandar Zulkarnaen Siregar,
  • Ratih Damayanti,
  • Warsito Purwo Taruno,
  • Harisma Nugraha,
  • Rohmadi,
  • Lina Karlinasari

DOI
https://doi.org/10.3390/f15040669
Journal volume & issue
Vol. 15, no. 4
p. 669

Abstract

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Fast-growing teak trees are cultivated extensively in Indonesia to meet the growing demand for teak wood. However, it is necessary to assess the conditions of teak stands throughout their growth period. The nondestructive testing of wood utilizing dielectric spectroscopy approaches based on electrical properties is currently under development, particularly for evaluating tree stands. This study aimed to analyze the dielectric values of fast-growing teak tree stands within a frequency range of 250 kHz to 60 MHz and to understand the relationship between their physical and anatomical properties. A capacitance measurement system was employed to collect dielectric spectroscopy data directly from trees aged 4, 5, and 7 years. Simultaneously, physical and anatomical samples were obtained using a 0.5 cm diameter increment borer. The results revealed significant differences in the fiber length, lumen diameter, and wall thickness at each age. The optimal dielectric frequency for distinguishing wood properties in standing trees was identified to be within a range of 18 MHz to 23 MHz. In the linear model, a moderate relationship was observed with a correlation coefficient of (r)0.403, although the coefficient of determination (r2) was weak at 0.162 for green density. However, a robust relationship was observed in the linear model for specific gravity with r = 0.826 and r2 = 0.682. A weak but significant relationship was also identified with r = 0.2, a coefficient of determination of r2 = 0.04, and a significance level 2 but high significance indicate that the independent variables still noticeably contribute to explaining the dependent variable. Further analysis and data processing can be enhanced by identifying the crucial variables in the capacitance measurement system.

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