## 3 Results and Discussion
### Statistical Evaluation of the Obtained Results  
Statistical evaluation of the moisture comparison of samples taken from four types of sawing, briquette, container and grinding technologies was performed by a one-way analysis of variance and looked for a significant difference in the humidity of the samples (Table 4, Figure 4).  
Figure 3: Continuous Cumulative Curve of spruce dust samples.  
\begin{table}
\begin{tabular}{l c c c c} \hline \hline \multirow{2}{*}{**Parameters**} & \multicolumn{4}{c}{**SpuceDust**} \\ \cline{2-5}  & **WD\_Saw** & **WD\_Briq** & **WD\_ExtrD** & **WD\_Grin** \\ \hline Determination of wood & 6.056 \(\pm\) 0.139 & 7.248 \(\pm\) 0.480 & 9.054 \(\pm\) 0.177 & 8.42 \(\pm\) 0.403 \\ dust moisture (\%) & & & & \\ Sieve analysis—average & 250 & 106 & 75 & 63 \\ value (\(\upmu\)m) & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 3: Presentation of material parameters of spruce dust samples.  
At the level of significance \(\alpha=5\%\), we reject the 0 hypothesis about the equality of average humidity with different technologies. The moisture of the sawdust differs in a statistically significant way, and from the box graph in Figure 4 it is clear that the highest moisture was observed in the container, with the lowest observed in sawing.  
One-factor analysis of variance was supplemented by [PERSON]'s test, i.e., a simultaneous pairwise comparison, the results of which are presented in Table 5.  
Based on the results, we can state (Table 5) that there is a statistically significant difference in the moisture of the samples between all pairs of technologies.  
Statistical evaluation of sieve analysis is difficult. Input values are different and variable values cannot be compared. It is possible to perform a mutual comparison of the percentage number of particle sizes from individual technological operations (Figure 5).  
The clarity of the particle number shows the largest proportion of the saw sample. Said sample was not initiated in the hot-plate (Table 4). Sieve analysis represents the basic characteristics of wood dust, from which other parameters of the generated dust are derived, as evidenced by our result. The experimental results indicate a variability in the number of individual fractions depending on the wood dust formed. The statement is in accordance with other results, which we realized during the research on the wood dust of beech samples [61; 62; 63; 64; 65; 66]. [PERSON] et al. [67] have made statements regarding the course of the machining of spruce and following the making of dust fractions as ambiguous.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & **SC** & **SV** & **PC** & **S\(\bar{\text{C}}\)** & **SV** & **PC** & **F** & \(p\) \\ \hline \multirow{3}{*}{Moisture * (\%)} & effect & effect & effect & error & error & error & \\  & 26.29 & 3 & 8.76 & 2.23 & 16.00 & 0.14 & 63.02 & 0.000 \\ \hline \hline \end{tabular}  
* Marked effects are significant at \(p\) < 0.05000.  
\end{table}
Table 4: Analysis of variance of four wood dust samples with variable, moisture (%).  
Figure 4: Graphical comparison of moisture level and variability of four different samples. Legend: “x” axis—dust samples.