## 3 Results
### Principal Component Analysis  
In order to determine the relationship between storage protein fractions, their subfractions and the baking quality (Table 4), a correlation-based principal component analysis (PCA) was carried out. The first two principal components together explained 60.1% of the total variance (PC1: 36.9%, PC2: 23.23%) (Figure 5).  
The PCA allowed to visualize the separation of the different genotypes (Figure 5), and to identify the traits mainly correlated with the PCs (Figure 6). In the scores plot (Figure 5), PC1 separated the genotypes Alvand, Mihan, Discus and Rumor on the negative side from Hybery and Impression on the positive side. Impression is especially associated with high values of PC1. Within each genotype, the samples from well-watered Discus, Rumor and Mihan plants were bundled furthest to the left, those of moderately stressed plants in the middle, and those of severely stressed plants furthest to the right. For the genotypes Impression, Hybery and Alvand, well-watered and moderately stressed samples were not clearly separated, but severely stressed samples again clustered furthest to the right. PC2 tended to separate the German cultivars on the positive side and the Iranian cultivars on the negative side, with partial overlaps between the genotypes, suggesting that PC2 might be related somehow to the cultivar origin. Comparison of the scores plot and the correlation circle (Figure 6) indicates that PC1 is positively correlated with \(\omega\)-gliadin concentrations, high specific volume, high HMW concentrations and a high HMW/LMW ratio, and negatively correlated with LMW-B. It seems that PC2 is positively correlated with  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**Genotype** & \multicolumn{3}{c}{**Alvand**} & \multicolumn{3}{c}{**Mihan**} & \multicolumn{3}{c}{**Impression**} \\ \hline Treatments & WW & MD & SD & WW & MD & SD & WW & MD & SD \\ \hline Specific volume (mL/g) & 3.3 b & 3.4 b & 3.7 a & 2.9 b & 3.3 a & 3.4 a & 3.5 b & 3.6 b & 3.8 a \\ Freshness retention (N) & 13.1 & 16.7 & 15.6 & 14.8 & 12.7 & 12.4 & 17.1 & 15.3 & 15.4 \\ Hardness (N) & 4.6 & 5.1 & 4.6 & 5.1 & 4.4 & 4.0 & 5.0 & 4.9 & 4.6 \\ \hline
**Genotype** & \multicolumn{3}{c}{**Discus**} & \multicolumn{3}{c}{**Rumor**} & \multicolumn{3}{c}{**Hybery**} \\ \hline Treatments & WW & MD & SD & WW & MD & SD & WW & MD & SD \\ \hline Specific volume (mL/g) & 2.8 c & 3.0 b & 3.3 a & 2.8 b & 2.9 b & 3.0 a & 3.2 b & 3.2 b & 3.4 a \\ Freshness retention (N) & 17.0 & 16.2 & 13.8 & 18.6 A & 13.8 BB & 13.3 B & 15.4 & 14.4 & 14.0 \\ Hardness (N) & 6.0 \(a\) & 5.0 _ab_ & 4.2 \(b\) & 6.1 & 5.6 & 5.1 & 5.2 & 4.4 & 4.8 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Baking quality parameters depending on the treatments (well watered: WW, moderate drought stress: MD, severe drought stress: SD) of the Iranian (Alvand, Mihan) and German wheat genotypes (Impression, Discus, Rumor and Hybery). For each variety, different letters within the same genotype represent significant differences between treatments (small letters: specific volume of the bread; capital letters: freshness retention; italic letters: hardness); No letter means no significant differences in this group; \(p\) \(<\) 0.05; \(n\) = 4.  
\(\alpha/\beta\)-gliadin and negatively with LMW-C. Moreover, there is a highly significant positive correlation between \(\omega\)-gliadins and the specific bread volume.  
Figure 5: Biplot representation of the principal component analysis according to Pearson. Outlined data points are observations of the Iranian (Alvand, Mihan) and German wheat genotypes (Impression, Discus, Rumor and Hybery). Colours indicate the treatments well-watered: green, moderate drought: yellow, severe drought red; symbols indicate the six genotypes (circle: Alvand; diamond: Mihan; triangle: Discus; square: Rumor; star: Hybery; line: Impression).  
Figure 6: Correlation circle examined by Pearson correlation with \(p=0.05\).