Identification of behaviour patterns of viticultural regions according to their agroclimatic fingerprint and grape characteristics

Abstract

Background and Aims Each viticultural region has its own oenological tradition, heritage culture and history. Consequently, in wine production, the human factor may be significant in differentiating the final product of one viticultural region from another. Then, the question remains as to whether such differentiation is caused by winemakers or whether they simply amplify the differences present already in grapes and shaped by the agroclimatic fingerprint. The present research aims to provide a methodology, based on a multimetric approach to both grape characteristics and agroclimatic conditions of the vineyard, that is able to evaluate the appropriateness of the Protected Geographical Indications (PGIs) of a wine region. The Balearic Islands (Spain) were chosen for the study. Methods and Results Twenty-eight Merlot and 28 Cabernet Sauvignon vineyards were selected from the four vine-growing subregions of the Balearic Islands. Grapes and soils were sampled evenly over the whole surface of each vineyard. Climatic and landscape conditions were also recorded at each site. Principal component analysis (PCA) was applied to grape attributes, soil texture and fertility, climate features and landscape conditions of the vineyards. The PCA results revealed that 70% of the total variance of the dataset in Merlot and 68% in Cabernet Sauvignon could be explained by the first three components. For both cultivars, two of these three principal components are related to agroclimatic features and the third, to grape attributes. Independent of the cultivar, the PCA distribution of the samples resulted in four clusters, where the maximum temperature and silts content of the vineyard were the most important descriptors. Conclusion The proposed methodology contributes to an understanding of the behaviour patterns of the four PGIs present in the Balearic Islands because they matched the four clusters obtained by the PCA distribution of the sample dataset. It thus corroborates their historical existence and explains it, in a first approach, on a more geographical basis. Significance of the Study This work provides a methodology for evaluating the appropriateness of the PGIs recognition based on both the grape and the agroclimatic attributes of the region.