Multivariate Analysis Approaches for Dimension and Shape Discrimination of Vitis vinifera Varieties.

Abstract

In this study, berry dimensions and shape traits, which are important for the design of the grape processing system and the classification of 10 different grape varieties grown in same ecological conditions ('Ata Sarısı', 'Barış', 'Dımışkı', 'Hatun Parmağı', 'Helvani', 'Horoz Karası', 'Hönüsü', 'İtalia', 'Mevlana Sarısı', and 'Red Globe') were determined; differences between the varieties were identified with the use of discriminant analysis. The largest grape varieties were identified as 'Ata Sarısı' and 'Red Globe'. The 'Red Globe' and 'Helvani' varieties had geometrically sphere-like shape. The 'Barış' variety had the lowest size averages. According to elliptic Fourier analysis, the primary source of shape variation was ellipse and sphere-looking varieties. However, shape variation was seen due to the existence of a small number of drop-like varieties. According to discriminant analysis, shape differences of the varieties were defined by two discriminant functions. Based on these discriminant functions, the greatest classification performance was achieved for 'Mevlana Sarısı' and 'Dımışkı'. In scatter plots, three shape definitions (sphere, ellipse, and drop) were made for grape varieties. Cluster analysis revealed 4 sub-groups. The first sub-group included the 'Mevlana Sarısı' variety; the second sub-group included the 'Hönüsü', 'Hatun Parmağı', 'Dımışkı', and 'Horoz Karası' varieties; the third sub-group included the 'Ata Sarısı' variety; the fourth sub-group included the 'Barış', 'Helvani', 'İtalia', and 'Red Globe' varieties. The variety in the first group had a geometrically ellipse-like shape, the largest length, and the smallest width. The size data were the smallest for the second sub-group. The third sub-group, with the ellipse-like shape, had the large size data. The grape varieties the closest to the sphere were classified in the fourth group, and these varieties had the large sizes.

Plant phenotyping relevance

ブドウ果実の寸法・形状という植物形質を対象に、楕円フーリエ解析、判別分析、クラスター分析を組み合わせた形状識別手法を中心的に適用しているため。

Code and data availability

The article describes image-based phenotyping of 10 Vitis vinifera varieties (dimensions, shape traits, elliptic Fourier analysis), but contains no data availability statement, no public phenotype dataset or image deposit, and no author analysis code or workflow with a public URL. The only URLs present are the CC BY 4.

No evidence-backed public reproduction asset is currently recorded.