Digital image-based morphometrics and mixed effects inference resolve environment sensitive and stable traits in onion (allium cepa L.).

Abstract

Despite their relevance to postharvest engineering and cultivar improvement, the genotype- and environment-dependent variation of the physical and geometrical traits of onion bulb remains poorly characterized in the Republic of Korea. The study evaluated these traits in six commercial onion cultivars grown across two distinct production regions (Muan and Changnyeong), using a randomized complete block design with three replications. A standardized phenotyping workflow combined with image acquisition and imageJ-based trait extraction was employed to measure linear dimensions, including polar and equatorial diameters, neck and bulb thickness. Linear mixed models were used to partition genotype (G), location (L), and G x L interaction effects. Most traits exhibited significant G, L, and G×L effects, indicating strong environmental sensitivity alongside genetic control Combined heritability estimates were high for bulb thickness (0.83), bulb weight (0.66), and diameter- and area-related traits (0.54–0.68), while broad-sense heritability across locations was consistently high (0.71–0.99), particularly for single bulb weight and size traits. Spring Breeze, Katamaru, and Healthy Q consistently produced larger bulbs, while Cheonjujeok and Eomji Nara exhibited smaller bulb dimensions. Trait responses varied markedly between environments, with changes ranging from reduction of approximately 80% to increases exceeding 160%, highlighting pronounced genotype × environment interactions. Hierarchical cluster heatmap analysis revealed strong associations among bulb size–related traits and distinct genotype groupings, with clear location-dependent differences in trait expression between Muan and Changnyeong. These findings demonstrate the utility of image-based phenotyping for robust environment-aware assessment of onion bulb geometry and provides a quantitative basis for region-specific cultivar selection, postharvest system design, and future multi-site breeding evaluations.

Plant phenotyping relevance

画像取得とImageJによる形質抽出を組み合わせた標準化フェノタイピングワークフローが、タマネギ球の形態形質測定の中心的手法として明示されているため。

Code and data availability

The article describes image-based phenotyping of onion bulbs and R/SIMCA-P analyses, but contains no public phenotype dataset, image repository, author code deposit, or trained model. The only supplementary item is a docx without stated data/code contents, and no authors' public URL for assets is provided.

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