The Suitability of a Foliometric Method for Leaf Vein Analysis in Grapevine Variety Identification, Using the Example of St. Georgener-Rebe (Mater Veltlinis), Gewürztraminer, and Grüner Veltliner

In addition to purely qualitative trait descriptions, biometric studies have become established within ampelography for the identification and characterisation of grapevine varieties. This publication examines the suitability of a software-assisted foliometric method, based on the self-similarity of vine leaves and employing 24 vein branching nodes, for grapevine variety identification. Various classification methods were used, including PCA, discriminant analysis, and two different neural networks. The findings show that in Vitis vinifera, leaf venation alone provides enough distinguishing features to enable an almost perfect classification of the varieties analysed here—Grüner Veltliner and its parent varieties, Traminer and St. Georgener-Rebe (Mater Veltlinis). However, due to significant individual variability, single leaves are not sufficient. By generating composite leaf data through averaging a small number of leaves, accurate classification becomes feasible. The choice of features also allows for a reasonably precise description of differences in leaf venation, which were analysed in terms of their variability across different years of data collection, within a growing season, and along the primary shoot (from proximal to distal), with particular attention to varietal differences. Leaves of the shoot middle proved more suitable for identification, while the time of year when sampling occurs is of less importance, although differences between spring and summer leaves were observed. Furthermore, the method was employed to provide a comparative description of the leaf venation patterns of the three grapevine varieties. For most traits, Grüner Veltliner exhibited intermediate characteristics between its parent varieties.