## 3 Results
### Principal Component Analysis

Table 4: Eigenvalues and variance explained by the first five principal components (PCs) of the analysis carried out on the whole dataset of soil indicators (20 variables). Figure 1: Score plots of the first two principal components extracted in the analysis carried out on the set of chemical (a) and physical (b) soil indicators. MT = minimum tillage; NT = no-tillage. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multicolumn{2}{c}{**Factor1**} & \multicolumn{2}{c}{**Factor2**} & \multicolumn{2}{c}{**Factor3**} & \multicolumn{2}{c}{**Factor4**} \\ \hline WEOC & 54 & * & \(-\)22 & & 44 & * & 5 & \\ WEN & \(-\)77 & * & 4 & & \(-\)11 & 6 & \\ C\_biomass & 32 & & 53 & * & 21 & 53 & * \\ TOC & **91** & * & \(-\)29 & & 12 & 2 & 2 \\ TEC & **93** & * & \(-\)27 & & 6 & 15 & \\ HA\_FA & \(-\)36 & * & \(-\)**59** & * & 7 & 40 & * \\ N & 36 & * & 7 & 34 & **60** & * \\ P\_Oisen & 33 & & \(-\)**63** & * & \(-\)21 & 26 & \\ pH & \(-\)70 & * & 52 & * & \(-\)14 & \(-\)3 & \\ EC & 50 & * & 43 & * & 13 & 42 & * \\ Ca\({}^{2}\) & 2 & & 2 & & **79** & * & \(-\)23 & \\ K\({}^{*}\) & 82 & * & \(-\)8 & & \(-\)36 & * & 26 & \\ Mg\({}^{2+}\) & \(-\)46 & * & \(-\)9 & & 57 & * & 18 & \\ Na\({}^{*}\) & \(-\)52 & * & 41 & * & 43 & * & 12 & \\ BD & 83 & * & 37 & * & 12 & & \(-\)12 & \\ P\_Mcc & \(-\)**84** & * & \(-\)34 & * & 16 & & 18 & \\ AC & \(-\)**91** & * & \(-\)26 & & 8 & & 21 & \\ RFC & **92** & * & 27 & & \(-\)6 & & \(-\)18 & \\ clay & \(-\)43 & * & 45 & * & \(-\)10 & 12 & \\ sand & 23 & & \(-\)21 & & 58 & * & \(-\)49 & * \\ \hline \hline \end{tabular}
* * indicates the significance of the variable loadings. The sign of variable loadings indicates the positive or negative correlation between the variables and the principal component. WEOC = water extractable organic carbon; WEN = water extractable nitrogen; C\_biomass = microbial biomass carbon; TOC = total organic carbon; TEC = alkali-extractable carbon; HA\_FA = humic and fulvic acid carbon; N = total nitrogen; P\_Oisen = Olsen available phosphorus; EC = electrical conductivity; Ca\({}^{2+}\), Mg\({}^{2+}\), Na\({}^{*}\), K\({}^{*}\) = exchangeable cations. BD = dry bulk density; P\_Mcc = macrocopy; AC = air capacity; RFC = relative field capacity.  
\end{table} 
Table 5: Variable loadings of the first four components in the analysis carried out on the whole dataset. Values are multiplied by 100 and rounded to the nearest integer. Variance explained: PC1 = 41.21%; PC2 = 12.61%; PC3 = 10.65%; PC4 = 8.07%. In detail, the first four PCs explained cumulatively about 72.54% of total variance (Table 4). In the first PC (41.21% of total variance) the highly weighted variables were TOC and TEC among chemical variables, whereas RFC and AC, followed by P\({}_{\text{MAC}}\), for the hydrological soil parameters (Table 5). Slightly under the threshold of 10% of the highest factor loading [50], there were exchangeable K\({}^{+}\) and bulk density and, at a lower extent, WEN. In the second PC (12.61%), available P and humic and fulvic acids showed the highest loadings, with microbial biomass carbon and pH slightly under the threshold. In the third (10.65%) and fourth (8.07%) components, exchangeable Ca\({}^{2+}\) and N were selected, respectively (Table 5). The inspection of these results showed that the first PC summarized main findings of the analysis of variance. The second component highlighted instead the role of available nutrients (P) and some carbon fractions (humic and fulvic acids C and microbial biomass C), adding, in this way, further elements to explain differences observed in the experimental conditions.