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analysis. The total data set included six humidity levels × two of the model was evaluated using the coefficient of determination

temperatures × five replicates = 60 specimens. (R2 and adjusted R2) where applicable. All analyses were
Previously mentioned test parameters such as RH, moisture performed using IBM SPSS Statistics 28.0.
content and test temperature are interrelated variables within
the wood material. Study Results
In this study, relative humidity was used as the primary The groups of lamella samples were divided according to the
conditioning parameter, while moisture content was treated relative air humidity (RH) at which testing was conducted.
as the resulting material state at equilibrium. Because of this, The moisture contents of the lamella samples are recorded.
these factors were not considered fully independent, but rather The lowest moisture content, 4.8 percent, was measured
as coupled variables influencing dielectric behaviour under in samples tested at a RH of 10 percent, while the highest

defined environmental conditions. moisture content was measured in samples tested at a RH
The collected data were analysed using SPSS Statistics of 100 percent.
and Excel. Statistical analysis was performed using multiple The moisture content of the lamella samples increases
linear regression analysis to evaluate the effects of sample with rising RH. The lamella samples on which the dielectric
temperature, moisture content and measurement frequency on properties were measured after steaming had a moisture
the dielectric constant and dielectric loss tangent. content of 10.7 percent.
Statistical significance was set at p < 0.05. The appropriateness The densities of the lamellas by group are also recorded.