## 3 Results
### Statistical Analysis  
_Wind tunnel tests: Phase 1_. The results of the two-way ANOVA (Table 3) of the wind tunnel test data reveal that for both tested soil types, the biopolymer type (\(p<0.001\)) and concentration (\(p<0.001\)) have a significant effect on wind-induced soil loss. Some  
Figure 11: Penetration resistance of crusts from fine-grained silica sand samples performed after the fifth wind tunnel cycle on day 28. Biopolymers were applied at their respective plateau concentration determined in Phase 1. Each of the three prepared samples was penetrated at the top and bottom of the centre (n = 6). The numerical results are appended in Table 5.  
Figure 10: Penetration resistance of crusts from medium-grained sand samples, performed after the fifth wind tunnel cycle on day 28. Biopolymers were applied at their respective plateau concentration determined in Phase 1. Each of the three prepared samples was penetrated at the top and bottom of the centre (n = 6). The numerical results are appended in Table 5.  
biopolymer types achieve higher wind erosion resistance than others do, and the soil loss generally decreases as the concentration increases until it reaches a plateau concentration. _Penetrometer tests: Phase 1._ For both tested soil types, the results of the two-way ANOVA reveal that the biopolymer type (\(p<0.001\)) and concentration (\(p<0.001\)) have a significant effect on the samples' penetration resistance (Table 5). Some biopolymer types achieve higher penetration resistances than others do, and the penetration resistance generally increases with higher concentrations. _Penetrometer tests: Phase 2._ For the penetrometer tests performed in Phase 2, the two-way ANOVA shows that the biopolymer type has a significant effect on the penetration resistance of both the medium-grained sand (\(p<0.001\)) and the fine-grained silica sand (\(p<0.05\)) (Table 6). Additionally, the application rate significantly affects penetration resistance (\(p<0.001\)), with penetration resistance generally increasing at higher application rates. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Factor**} & \multicolumn{6}{c}{**Medium-Grained Sand**} & \multicolumn{6}{c}{**Fine-Grained Silica Sand**} \\ \cline{2-11}  & **SS** & **df** & **MS** & **F** & \(p\)** & **SS** & **df** & **MS** & **F** & \(p\)** \\ \hline Type & 106.33 & 4 & 26.58 & 10.7 & \textless{}0.001 & 196.99 & 4 & 49.25 & 2.6 & \textless{}0.050 \\ Application rate & 160.87 & 6 & 40.22 & 16.1 & \textless{}0.001 & 55.96 & 6 & 13.99 & 0.7 & 0.568 \\ Interaction & 124.30 & 24 & 7.77 & 3.1 & \textless{}0.050 & 217.03 & 24 & 13.56 & 0.7 & 0.761 \\ Error & 124.58 & 70 & 2.49 & & 941.9 & 70 & 18.84 & & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Results of two-way ANOVA (\(\alpha=0.05\)) of wind tunnel test data from Phase 2, investigating the effect of the application rate on the wind-induced soil loss. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Factor**} & \multicolumn{6}{c}{**Medium-Grained Sand**} & \multicolumn{6}{c}{**Fine-Grained Silica Sand**} \\ \cline{2-11}  & **SS** & **df** & **MS** & **F** & \(p\)** & **SS** & **df** & **MS** & **F** & \(p\)** \\ \hline Type & 136,232.79 & 4 & 34,058.20 & 32.7 & \textless{}0.001 & 21,479.42 & 4 & 5369.85 & 53.5 & \textless{}0.001 \\ Concentration & 380,509.42 & 6 & 63,418.24 & 60.9 & \textless{}0.001 & 40,628.28 & 6 & 6771.38 & 67.5 & \textless{}0.001 \\ Interaction & 355,037.08 & 24 & 14,793.21 & 14.2 & \textless{}0.001 & 86,459.69 & 24 & 3602.49 & 35.9 & \textless{}0.001 \\ Error & 72,859.77 & 70 & 1040.85 & & & 7025.46 & 70 & 100.36 & & \\ \hline \hline \end{tabular} Note. SS = sum of squares, df = degrees of freedom, MS = mean square, F = F-value, and \(p=p\)-value.  
\end{table} 
Table 3: Results of two-way ANOVA (\(\alpha=0.05\)) of wind tunnel test data from Phase 1, investigating the effect of the concentration on the wind-induced soil loss.