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Scientific and Technical Bulletin of the Institute of Oilseed Crops NAAS (ISSN: 2078-7316) / 2025 / 39 / P. 16-30

Determination of seed shape characteristics using automated computer image analysis
Busarov P. Yu., Vedmedeva K. V.

Sunflower (Helianthus annuus L.) is one of the world’s leading oilseed crops and the main source of edible oil in Ukraine. In addition to oil production, sunflower seeds are widely used as raw material in the confectionery industry. Breeding of confectionery types focuses on developing large-seeded varieties with a high kernel yield and improved physical and mechanical characteristics. The morphology of the seed — including its shape, thickness, and proportions — significantly affects processing quality and industrial use. Despite numerous studies, the shape of the seed remains a less explored trait compared to color or mass, and most existing methods rely on subjective visual evaluation. The aim of this study was to perform a quantitative assessment of sunflower seed morphology using automated computer image analysis and to compare the obtained parameters with the established UPOV and UPOV–OECD classification systems. The analysis was conducted on digital images of seeds from various sunflower lines, including oilseed, intermediate, and confectionery types. Image-processing software was used to determine seed area, proportions, angular characteristics, and thickness, enabling an objective shape classification. The results showed that seed area ranged from 13 mm² in line 160B to 90 mm² in line L3333, reflecting the differences between oilseed and confectionery types. The proposed θa angle parameter proved effective for shape characterization: elongated (L3333, θa = 52±3.1), narrow-elliptic (Orn1, θa = 64±3.3), broad-elliptic (KG110, θa = 67±2.1), and round (KG101, θa = 72±2.8). The obtained data support the development of an improved, quantitative approach for sunflower seed shape evaluation based on objective digital parameters. The proposed methodology can be applied in breeding and technological studies for morphological standardization and for refining classification criteria within UPOV and OECD systems.

Citation: Busarov, P. Y., & Vedmedeva, K. V. (2025). Determination of seed shape characteristics using automated computer image analysis. Scientific and Technical Bulletin of the Institute of Oilseed Crops NAAS, 39, 16-30.

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