A Multivariate Spatial Framework for Delineating Viticulture Management Zones: A Proof-of-Concept Study

Soil heterogeneity is a critical factor in vineyard performance, influencing both vine vegetative growth and yield. This study investigated the application of Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) to soil datasets derived from both the topsoil and the integrated soil layers. This analysis was conducted within a precision viticulture framework that also incorporates grape data. Initially, PCA was applied to a set of soil variables to identify those contributing most to spatial variability. Subsequently, HCA was conducted on a subset of the most informative variables to classify soil samples into meaningful clusters based on their PCA scores. The results demonstrate that analyzing both the top and integrated soil layers provides critical information for delineating functional management zones. To visualize this, interpolated maps were created using PCA component values and HCA cluster assignments as input, illustrating the geographical extent of these factors and clusters. The final thematic maps feature interpolated HCA clusters from the integrated soil layer as a background, with overlaid proportional symbols representing the values of key grape characteristics. These maps, which geographically depict soil heterogeneity and the spatial variability of both soil parameters and grape characteristics, can be used to delineate management zones. This research highlights the importance of adopting a multivariate spatial approach when analyzing available soil data, offering a methodological contribution to optimizing data-driven decision-making in precision viticulture. The framework proposed for zone delineation demonstrates that analysis of the integrated soil layer provides critical information for defining functional management zones.