Species-Specific Prediction Model of Wood Moisture Content Based on Electromagnetic Wave Propagation Time

Abstract

Laboratory and field experiments were performed to examine the feasibility of using Time Domain Reflectometry (TDR) to monitor moisture content (MC) of wood and standing trees. The TDR was used to detect the electromagnetic wave propagation time of four tree species (Betula platyphylla, Tilia tuan, Picea asperata, and Fraxinus mandshurica) at different MCs. During the TDR test, effects of probe insertion depths on MC predictive accuracy were considered. The best results were obtained at an insertion depth of 8 cm. At the selective 8 cm insertion depth, a species-specific MC prediction model (0.94 ≤ R² ≤ 0.98), a generalized model for the four species (R² = 0.65), and a hybrid model for the species with similar densities (0.80 ≤ R² ≤ 0.96) were constructed, respectively. Overall, the species-specific MC prediction model showed good predictive ability for both tree and wood disc samples, including that TDR can be used to detect wood and standing tree MC. If possible, the hybrid model can be used for species with similar density.