## 3 Results and Discussion
### Interaction between Silage Parameters and Biogas Yield  
Factor and PCA analyses were performed in order to assess relationships between the variables. The PCA analysis also included the calculation of the correlation matrix (Table 10), expressing relations between the studied parameters in detail. It follows from the correlation matrix (Table 10) that the biogas yield (m\({}^{3}\)/kg\({}_{\text{VS}}\)) exhibited a strong linear positive dependence on the parameters of ash (R = 0.91) and proteins (R = 0.87) and a negative dependence on the parameters of the fiber and lignin contents in the silage: NDF (R = \(-\)0.91), ADF (R = \(-\)0.89), CF (R = \(-\)0.88), ADL (R = \(-\)0.83) and starch (R = \(-\)0.70). Thus, the yield of biogas increased with the increasing content of proteins while it decreased with the increasing contents of fiber and starch. According to [PERSON] et al. (2016), substrates rich in proteins are suitable for anaerobic digestion. [PERSON] (2017) claimed, however, that using these substrates increases the risk that the process of anaerobic digestion will be inhibited by ammonia. The mutual negative correlation between the biogas yield and the parameter of starch can be explained by the very low starch content in the FM silage (7.33%/kg\({}_{\text{STS}}\)), WSC silage (8.57%/kg\({}_{\text{STS}}\)) and in the mixed FM + WSC silage (6.85%/kg\({}_{\text{STS}}\)) compared with the maize silage (20.7%/kg\({}_{\text{STS}}\)) ([PERSON] et al., 2016; [PERSON] et al., 2016). In contrast, the relation between the biogas yield and contents of lipids in the silage (R = 0.29) exhibited a very weak, non-significant, negative dependence. In addition, the methane yield also exhibited a positive dependence on the content of proteins (R = 0.52); however, this was non-significant. In contrast, the methane yield was negatively correlated with the content of starch (R = \(-\)0.61), and a similar negative correlation with the starch content was exhibited by the content of methane (R = \(-\)0.59). These dependencies were, however, non-significant. Based on the PCA analysis, the interactions between the studied parameters and the biogas (methane) production are shown by means of biplots and scree graphs (Figures 8 and A3). During the graph analysis, two main factors were set up (PC 1 and PC 2) that explained more than 83% of the variability of measured values; this is why they were chosen to explain the variability detected in the measured values (Figure A3). The measured data indicate there were two main factors (Figure A4): probably the grown plant species, which showed also in the composition of silage, and the effect of agrotechnology. PC 1 was considered the main factor as it explained more than 57% of the variability of variables, while the PC 2 factor explained hardly 26%. The factor analysis (Table 11, Figures 8 and A4) showed that Factor 1 strongly negatively correlated with the yield of biogas, methane and with the content of methane in biogas and strongly positively correlated with the starch value. Factor 2 strongly positively correlated with the parameters of proteins and ash and negatively correlated with the NDF, ADF, CF and ADL parameters.