Assessment of the Chain Dependence Relationships between Geology, Soil Properties and Grape Composition using a Metric Generalization of PLS Regression.

An investigation was carried out to assess the suitability of an approach based on a metric generalization of the Partial Least Square Regression to identify and discriminate chain dependence relationships between geology, soil properties and grape composition. The study area was Telesina Valley (Campania Region, southern Italy), a foremost vineyard district with the Falanghina grape cultivar. Five geopedological units, with different assemblages of geological substrates and pedotypes, were surveyed. Soil surface horizons were sampled from 85 sites, representing the widest variability of geological and pedological features. Our results allowed, for each geopedological unit, to categorise the specific variables influencing grape quality, and to quantify their individual contribution. In particular, geopedological units with volcanic (Andisols) and more or less developed (Inceptisols) soils on recent (Olocenic) colluvial debris, as well as with Andisols and organic matter-rich soils (Mollisols) on older Pleisto-Olocenic pyroclastites, express the best performance of the main components of wine taste and flavour, as tartaric acid, malic acid and titratable acidity of grape. Specifically, these last were significantly dependent on soil features as fine texture, neutral-alkaline pH, and appreciable content of soil organic matter and high CEC.