## 3 Results
### Assessment of Relations through a Clustering Approach  
As reported previously, the maturation parameters of each site were grouped into two clusters: cluster 1 (years where the maturation parameter is higher than the median) and cluster 2 (years where the maturation parameter is lower than the median). The composition of the different clusters is indicated in Figure 4. The corresponding cluster-means (centroids) and the statistical significance of the respective differences are shown in Figure 5. The differences between averages of cluster 1 and 2 were significant (\(p\leq 0.05\)) for all studied berry parameters and regions, except for TA in Alentejo and TPI in Alentejo and Douro-D (Touriga Nacional) (\(p>0.05\)), thus showing that the clusters comprise vintages with notably different grape berry attributes. Figure 4: _Cont._Figure 4: Identification of the years keyed to the different clusters for each quality parameter and vineyard site (Douro-C, Douro-D, Dão and Alentejo). Figure 5 also hints at differences in berry composition between cooler and warmer regions. Generally, in warmer regions and with lower annual precipitation (Alentejo and Douro-D, Table 2), berry weight and TA were lower than in cooler regions and with higher annual precipitation (Dao and Douro-C). Conversely, the berry pH was higher in warmer regions. Potential alcohol level at maturity did not show a clear trend across regions. Even so, the highest potential alcohol level in ARA berries was observed in the warmer region (Alentejo) and was significantly different from the lowest level observed in the cooler region (Dao). The TPI was very similar in all regions for both clusters, although a slight decrease (from the warmer to the colder region) was observed for ARA. Anthocyanins at maturity did not show a clear trend across regions. The grape berry compositions for Alentejo, Dao and Douro-C were noticeably affected by climatic conditions and will then be analysed in greater detail. For Douro-D, however, no such clear associations were found, and the respective results are not shown for the sake of succinctness. The difference between monthly averages of TG, TX and TN for June, July and August between maturation clusters was calculated for each site and variety (Tables 4 and 5). This analysis allowed the identification of temperature differences that may explain the average difference in grape quality attributes between clusters. The temperature differences were associated with an increase in the grape quality parameter (cluster 1 - cluster 2). The results confirmed that higher temperature tends to lead to a reduction in berry weight, TA, anthocyanins and TPI (Tables 4 and 5). Conversely, lower temperature often induced a reduction in pH and potential alcohol. In general, significant temperature differences between clusters were lower for ARA. At large, higher temperature differences between clusters were found in July TX and for TON. In all studied regions, larger temperature differences between clusters were observed for TON in Alentejo and all parameters but TA. Temperature differences for TA clusters were higher for Dao. In Douro-C, the larger differences were found between potential alcohol clusters.