High-throughput phenomic survey of seed morphological diversity in common and tartary buckwheat germplasm.

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Learn more: PMC Disclaimer | PMC Copyright Notice Sci Rep . 2026 Apr 11;16:16866. doi: 10.1038/s41598-026-47625-0 High-throughput phenomic survey of seed morphological diversity in common and tartary buckwheat germplasm Ji Eun Park 1, # , Bo Hwan Kim 2, # , Gyung Deok Han 3 , Wook Kim 2 , Piya Kittipadakul 4 , Supachai Vuttipongchaikij 5 , Faheem Shehzad Baloch 6 , Hyun Jo 7 , Jinhyun Ahn 8, ✉ , Yong Suk Chung 9, ✉ Author information Article notes Copyright and License information 1 National Agrobiodiversity Center, RDA, Jeonju, 54875 Republic of Korea 2 Institute of Life Science and Natural Resources, Korea University, Seoul, 02841 Republic of Korea 3 Biology and Agriculture Lab, Department of Practical Arts Education, Cheongju National University of Education, Cheongju, 28690 Republic of Korea 4 Department of Agronomy, Faculty of Agriculture, Kasetsart University, 50 Ngam Wong Wan Road, Chatuchak, Bangkok, 10900 Thailand 5 Department of Genetics, Faculty of Science, Kasetsart University, 50 Ngam Wong Wan Road, Chatuchak, Bangkok, 10900 Thailand 6 Department of Biotechnology, Faculty of Science, Mersin University, Mersin, Turkey 7 Department of Applied Biosciences, Kyungpook National University, Daegu, 41566 Republic of Korea 8 Department of Management Information Systems, Jeju National University, Jeju, 63243 Republic of Korea 9 Department of Plant Resources and Environment, Jeju National University, Jeju, 63243 Republic of Korea ✉ Corresponding author. # Contributed equally. Received 2025 Oct 22; Accepted 2026 Apr 1; Collection date 2026. © The Author(s) 2026 Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ . PMC Copyright notice PMCID: PMC13230958  PMID: 41963509 Abstract Buckwheat ( Fagopyrum spp.) germplasm represents an underutilized source of morphological diversity for crop improvement. This study presents a high-throughput phenomic survey quantifying five seed morphological traits (area, length, width, circularity, roundness) across 563 RDA genebank accessions (519 common buckwheat ( F. esculentum ), 44 Tartary buckwheat ( F. tataricum ) using standardized imaging. Common buckwheat exhibits larger seeds (area: 21.12 ± 4.04 mm²) with lower coefficients of variation (CVs: 17.9%), while Tartary buckwheat shows smaller seeds (14.80 ± 3.23 mm²) with higher CVs (20.1%) and greater shape dispersion (PC2 variance: 3.73 vs. 1.06). Principal component analysis confirms species-level morphological separation and documents exploitable polymorphism, including notched/slender/round/rice morphotypes in F. tataricum . These standardized phenotypic baselines support genebank curation, accession ranking by seed size/shape extremes, and prioritization for multi-environment trials and genetic studies. Supplementary Information The online version contains supplementary material available at 10.1038/s41598-026-47625-0. Keywords: Seed morphology, Image-based phenotyping, Population phenotypic variation, Common buckwheat, Tartary buckwheat Subject terms: Ecology, Ecology, Genetics, Plant sciences Introduction Seed morphology, including traits such as seed shape and size, is a critical agronomic factor that strongly influences crop performance and breeding outcomes 8 , 12 . Optimal seed size promotes faster germination, greater seedling vigor, and synchronized crop establishment, thereby enhancing overall field productivity. Seed shape affects sowing efficiency, mechanical resistance during handling and processing, and uniformity in crop stands 6 , 21 , 24 . Conversely, variations in seed size within a seed lot can cause uneven plant development and ultimately reduce yields. Seed grading by size is therefore widely applied as a practical strategy to improve crop uniformity and yield potential. The importance of seed size and shape has been well documented across diverse crops, emphasizing their role in maximizing resource use and achieving stable, high yields essential for food security and sustainable agriculture 2 , 9 , 19 . In common buckwheat ( Fagopyrum esculentum ), seed traits play a decisive role in consumer preference, post-harvest processing quality, and breeding objectives. The genetic inheritance of these traits, including maternal inheritance of seed coat color and complex inheritance patterns governing seed size, provides valuable insights for breeding strategies aimed at improving yield, stress resistance, and adaptability to environmental conditions 11 , 18 . Seed shape also influences seed packing density, sowing efficiency, resistance to mechanical damage, germination rate, and seedling vigor—factors that directly impact crop establishment and productivity 1 , 3 , 7 , 17 . In Tartary buckwheat (F. tataricum ), seed size and shape show considerable variation with complex inheritance patterns, including maternal effects and cases where progeny seeds exceed parental sizes 14 . Larger seeds are generally associated with increased yield potential and improved processing efficiency, such as better threshing and milling outcomes, while uniform seed shape enhances product quality and market acceptance 6 . Furthermore, seed morphology correlates closely with the accumulation of storage reserves such as starch and proteins, which determine nutritional value 5 , 15 . The broad variation in seed morphology reflects the underlying genetic diversity of Tartary buckwheat, which is crucial for adaptation to diverse environments and for maintaining population resilience 4 . Collectively, these findings underscore the central importance of seed morphological variation—particularly seed size and shape—in optimizing agronomic performance, guiding breeding programs, and enhancing both the nutritional and economic value of common and Tartary buckwheat. Accurate evaluation of seed morphology is therefore a cornerstone of crop improvement 23 . Traditional manual measurements of seed traits are labor-intensive, time-consuming, and prone to human error, limiting their utility in large-scale breeding programs. Image analysis provides a non-destructive, high-throughput alternative that enables precise and objective quantification of seed dimensions and shape descriptors such as length, width, area, perimeter, and aspect ratio 13 , 25 . By facilitating rapid and consistent data collection across thousands of seeds, image-based phenotyping accelerates the identification of superior genotypes, the discovery of genetic markers, and the development of cultivars with improved seed quality and yield 10 , 16 . We conducted a high-throughput phenomic survey of seed morphological variation across 519 common buckwheat ( F. esculentum ) and 44 Tartary buckwheat ( F. tataricum ) accessions from the RDA Genebank. Using standardized imaging, we quantified area, length, width, circularity, and roundness across approximately 100 seeds per accession to establish phenotypic baselines supporting (1) genebank curation and descriptor standardization, (2) initial parent selection by trait extremes, and (3) prioritization for multi-environment trials and genetic studies. We hypothesized that species differences in reproductive biology (outcrossing vs. selfing), breeding history, and germplasm composition would be reflected in contrasting patterns of within- and among-accession variation, while recognizing that our single-environment design primarily documents phenotypic polymorphism rather than causal mechanisms. Materials and methods Plant materials Seeds of 563 buckwheat ( Fagopyrum spp.) germplasm accessions were obtained from the Rural Development Administration (RDA) Genebank (Jeonju, Korea), where they are maintained through standardized regeneration cycles under controlled conditions to minimize maternal environment effects on seed morphology (Supplementary Tables S1 and S2). For this study, all accessions were phenotyped from seed lots regenerated under the standard RDA multiplication protocol; however, regeneration may occur in different years across accessions, so residual year-to-year environmental variation during seed fill cannot be fully excluded as a contributor to among-accession differences. This included 519 accessions of common buckwheat ( F. esculentum ) and 44 accessions of Tartary buckwheat ( F. tataricum ). Information on historical collection origins (IT Number, accession name, accession type, and country of origin) is provided in Supplementary Tables S1 and S2. While Tartary buckwheat accessions represent broader geographic provenance, all analyzed seeds derive from these uniform genebank multiplications. Information on the agronomic origin of each accession, including IT Number, accession name, accession type, and origin, is provided in Supplementary Tables 1 and 2. All accessions were collected from the Genebank of the Rural Development Administration (RDA), Republic of Korea. Imaging system and analysis Image system setup A complementary metal–oxide–semiconductor (CMOS) color image sensor camera (Nikon D7500, Nikon Imaging Japan Inc., Tokyo, Japan) with a resolution of 23.5 × 15.7 mm was used for image acquisition. The camera was equipped with a lens (AF-S DX NIKKOR 16–80 mm f/2.8–4E ED VR, Nikon Imaging Japan Inc., Tokyo, Japan). A studio box (M80 Studio, China) measuring 800 × 800 × 800 mm was constructed to provide a consistent imaging environment with minimal external light interference. To reduce shadow effects and ensure uniform illumination, a backlit LED panel (670 × 470 × 20 mm, ArtLight, Unclepen Co., Bucheon, Republic of Korea) was installed beneath the sample platform. Two LED light boards (600 × 10 mm, 5500 K ± 200) and two LED lighting stands (N-T96 LED, Prodean Co., Seoul, Republic of Korea, 5600 K) were positioned at fixed angles within the studio box to eliminate surface shadows from the seeds. Image acquisition Buckwheat seeds were manually arranged on a blue polypropylene (PP) sheet (255 × 310 mm; color clear PP “L” holder, Hyunpoong Inc., Pocheon, Republic of Korea). The blue PP background served as a chroma key to facilitate clear segmentation of the seeds from the background during image analysis. Vertical red, green, and blue (RGB) images were captured from a fixed height of 25 cm above the seeds. On average, each image included approximately 100 seeds per germplasm accession. To ensure accurate measurement of seed size, a 16 mm scale tag was included in each image. Additionally, to correct potential color distortion caused by lighting variability, a standardized color patch was placed on the PP sheet and used as a reference during image processing. Image analysis Buckwheat seed images were processed using a custom software developed by the Rural Development Administration of the Republic of Korea, based on the ImageJ platform (ImageJ, National Institutes of Health, USA, rsd.info.nih.gov/ij) 22 . This software enabled image editing, calibration, measurement, and analysis. Macros were implemented to automate tasks during image processing using ImageJ. During the image editing process, the pixel size was calibrated using a reference scale tag of 16 mm. The scale was set to convert pixel dimensions into millimeters to allow for accurate measurement. For background separation, images were split into red, green, and blue (RGB) channels using ImageJ. This color channel separation simplified the color profile of the seeds, making it easier to distinguish them from the background. After separating the RGB channels, binary images were generated using appropriate pixel threshold values to isolate the seeds from the background. To prevent the detection of noise particles, a size filter was applied: particles with a pixel area less than 1/100th of the average seed size were excluded from further analysis. Each seed was identified as a separate, non-overlapping object within the binary image. An example of the collected seed image and a schematic of the image analysis system are provided in Fig. 1 . Fig. 1. Open in a new tab Image acquisition and analysis workflow for buckwheat seed trait extraction. Images were acquired in a controlled studio-box setup with a scale tag and color patch, and seeds were segmented and measured in ImageJ (RGB channel separation, thresholding, and contour detection). Statistical analysis Statistical analyses were performed using R version 4.3.2 within RStudio version 2025.05.1 (Build 513, “Mariposa Orchid”) 20 . Before group comparisons, outliers were removed based on the interquartile range (IQR) method for each trait: values outside the range of Q1 − 1.5 × IQR and Q3 + 1.5 × IQR were excluded. After data cleaning, independent two-sample t-tests were conducted for each seed morphological trait (Area, Width, Length, Circularity, and Roundness) to assess differences between common buckwheat and Tartary buckwheat. Group means, standard deviations, t-statistics, and p-values were calculated and summarized. The coefficient of variation (CV) was calculated by dividing the standard deviation (SD) by the mean, and then multiplying by 100 to express it as a percentage. This value indicates the relative variability of the data compared to the mean. Principal component analysis (PCA) and visualization were also conducted using R within RStudio. Before PCA, outliers were also identified and removed using the interquartile range (IQR) method. The ggplot2 package was employed to generate PCA plots based on the first two principal components (PC1 and PC2), including group-specific coloring and normal distribution ellipses using the stat_ellipse() function with the confidence level set to 0.95 (level = 0.95). The factoextra package was used to visualize variable loading vectors, representing the direction and magnitude of each trait’s contribution to the principal components, with a color gradient indicating variable contribution. Group-wise variances of the principal component scores were calculated and summarized using the dplyr package. Results Significant differences were observed in all seed traits including area, width, length, circularity, and roundness in common buck wheat ( F. esculentum ) and Tartary buckwheat ( F. tataricum ) (Table 1 ). Common buckwheat seeds showed significantly larger values than Tartary buckwheat seeds in area, width, length, and roundness except for circularity. In the case of circularity, although the mean difference was small and Tartary buckwheat ( F. tataricum ) showed a slightly higher value, the difference was not statistically significant. Table 1. Comparison of seed morphological traits between common and Tartary buckwheat. Variable Common buckwheat (Mean ± SD (min, max)) Tartary buckwheat (Mean ± SD (min-max)) T value p - value Area † 21.12 ± 4.04 (8.71–46.43) 14.80 ± 3.23 (6.36–28.93) 119.0 *** †† Width 5.76 ± 1.17 (2.54–10.04) 4.77 ± 1.07 (2.42–8.54) 57.7 *** Length 5.56 ± 1.20 (2.58–10.96) 4.78 ± 1.07 (2.50–8.83) 51.9 *** Circ 0.738 ± 0.043 (0.458–0.886) 0.739 ± 0.053 (0.452–0.854) – 1.09 0.276 Round 0.664 ± 0.097 (0.409–0.998) 0.643 ± 0.127 (0.352–0.997) 10.4 *** Open in a new tab † Values are expressed as mean ± standard deviation (SD). Statistical significance was assessed using independent two-sample t -tests for each trait. Area; Projected area of the seed, mm 2 . Width, Length; Maximum horizontal and vertical dimensions of the seed, mm. Circularity; Circularity = 4 π (Area)/(Perimeter 2 ). Roundness; 4 × [Area] / (π × [Major axis] 2 ) †† *** indicate significance at p < 0.001. The CV values indicate the relative dispersion of each trait within species (Table 2 ). Across all measured traits, common buckwheat ( F. esculentum ) exhibited lower CV compared to Tartary buckwheat ( F. tataricum ), suggesting that its seed morphology is more phenotypically uniform. Table 2. The coefficient of variation (CV) of seed morphological traits between common and Tartary buckwheat (unit: %). Buckwheat n Area Width Length Circularity Roundness Common buckwheat 519 17.89 20.33 20.99 5.32 12.78 Tartary buckwheat 44 20.12 22.00 22.29 5.61 16.36 Open in a new tab Principal component analysis (PCA), as shown in Fig. 2 , clearly illustrates the morphological differences and variation patterns between common and Tartary buckwheat. Symbol shapes indicate species group (circles: common buckwheat; triangles: Tartary buckwheat), and color represents accession type (landrace, breeding line, improved cultivar, and wild species), with accessions of unknown type shown in gray. For common buckwheat, the accession types were: landrace ( n = 389), unknown ( n = 123), breeding line ( n = 4), and improved cultivar ( n = 3). For Tartary buckwheat, the accession types were: unknown ( n = 25), wild species ( n = 10), breeding line ( n = 5), and landrace ( n = 4), as summarized in Supplementary Tables S1 and S2. In the PCA scatter plot, common buckwheat accessions are clustered within a narrower region, whereas Tartary buckwheat accessions are spread across a broader range, indicating greater diversity in seed morphology. This distinction is further emphasized by the ellipses: the ellipse representing Tartary buckwheat covers a larger area, while that of common buckwheat is more compact and concentrated. Breeding lines of common buckwheat developed across different regions were more widely dispersed, while Tartary buckwheat breeding lines tended to cluster within a relatively restricted region of the PC1–PC2 space. The five Tartary buckwheat breeding-line accessions (IT 310557, IT 310558, IT 310559, IT 310560, and IT 310561), all originating from the same region (Table S2), were positioned close to one another. Fig. 2. Open in a new tab Principal component analysis (PCA) score plot of seed morphological traits in common buckwheat and Tartary buckwheat. Each point represents an individual seed projected into the PC1–PC2 space. Point colors indicate accession type, and gray points represent accessions with unknown type. Ellipses indicate the 95% normal data concentration ellipses (assuming a bivariate normal distribution) for each group. Furthermore, Fig. 2 ; Table 3 reveal that, when considering all buckwheat accessions together, seed size traits such as length, width, and area, and shape traits such as circularity and roundness, are separated along distinct principal components, suggesting that size and shape capture independent axes of morphological variation. This distinction is also reflected between species, as Tartary buckwheat exhibits broader variation along the shape-related axis, indicating greater diversity in seed shape. Table 3. Loadings of the seed morphological traits on the five principal components (PC1–PC5) obtained from PCA. PC1 PC2 PC3 PC4 PC5 Area 0.5789 0.1597 0.1907 0.0192 0.7763 Width 0.5521 – 0.0081 0.1093 – 0.7123 – 0.4193 Length 0.5546 0.0609 0.0241 0.6973 – 0.4493 Circularity – 0.2268 0.642 0.7189 0.0094 – 0.1397 Roundness 0.032 0.7474 – 0.659 – 0.0768 – 0.0138 Open in a new tab Each loading value represents the correlation between the original variable and the respective principal component. Variables with higher absolute loading values have a greater influence on the respective component. Tables 3 and 4 summarize group-wise variances and trait contributions to each principal component (PC). Tartary buckwheat ( F. tataricum ) exhibits higher variance along both PC1 and PC2, indicating broader morphological diversity. PC1 primarily reflects size-related traits (seed area, width, length), whereas PC2 corresponds to shape-related traits such as circularity, roundness. Table 4. The variance of principal component scores (PC1–PC5) obtained from PCA of seed morphological traits in common and Tartary buckwheat. Group PC1 PC2 PC3 PC4 PC5 Common buckwheat 1.85 1.06 0.535 0.267 0.00291 Tartary buckwheat 3.81 3.73 1.50 0.226 0.00606 Ratio (%) 56.22 26.08 12.30 5.32 0.07 Open in a new tab Our high throughput imaging pipeline quantifies seed morphological variation across 563 RDA buckwheat accessions, establishing a standardized phenotypic baseline for genebank curation and initial parent selection. These data identify high/low extremes in seed size/shape and document polymorphism structure (including F. tataricum morphotypes) to prioritize accessions for subsequent yield trials, stability analyses, and genetic studies. While GxE effects and year to year variation (~ 10% for quantitative seed traits) require multi environment validation for breeding decisions, this work provides essential groundwork documenting exploitable morphological diversity in Korean buckwheat germplasm. Discussion An interesting contrast emerges when comparing observed phenotypic patterns between species. Common buckwheat (F. esculentum) exhibits larger seeds with lower among-accession coefficients of variation (CVs: 17.9% area; Table 2 ) and tighter clustering in the PCA space (PC2 variance: 1.06; Table 4 ), whereas Tartary buckwheat (F. tataricum) shows smaller seeds with higher among-accession CVs (20.1% area) and broader dispersion (PC2 variance: 3.73). At the same time, mean within-accession CVs for area are lower in Tartary buckwheat (7.2%) than in common buckwheat (14.1%; Supplementary Table S3), consistent with expectations for a predominantly selfing vs. outcrossing species, but confounded by differences in sample size (44 vs. 519 accessions), breeding history, and germplasm composition. ​Several factors may explain these patterns. First, the number of accessions analyzed differed markedly (519 common vs. 44 Tartary), potentially introducing sampling effects. Second, long-term cultivation and selective breeding of common buckwheat in the Republic of Korea may have reduced among-accession variability, whereas commercial Tartary buckwheat cultivars are more recent and the RDA collection includes a higher proportion of wild and unknown-type accessions (Fig. 2 ; Supplementary Tables S1 and S2). Third, seed morphology may be influenced by environmental and agronomic conditions in addition to genetics. Although genebank standardization minimizes environmental effects, seed traits may retain maternal environment signatures from regeneration cycles, and Tartary buckwheat’s broader original origins and smaller sample size could amplify such effects, contributing to higher among-accession CVs independent of genetics. Multi-environment replication and genetic data would be needed to disentangle these factors from mating-system effects. F. tataricum exhibits remarkable seed polymorphism with at least four distinct morphotypes (notched, slender, round, and rice-shaped), which our image-based phenotyping can formally characterize using shape descriptors. Tartary buckwheat seeds showed higher circularity (0.739 ± 0.053) but lower roundness (0.643 ± 0.127) than common buckwheat (Table 1 ), consistent with more compact yet jagged morphotypes. Principal component 2, dominated by shape traits (circularity, roundness loadings > 0.64; Table 3 ), captures 26% of total variation and shows markedly higher Tartary dispersion (PC2 variance: 3.73 vs. 1.06 in common buckwheat; Table 4 ). These quantitative shape metrics provide formal descriptors for morphotype classification, enabling downstream genetic association studies to link specific morphotypes to underlying loci controlling seed form diversity. The imaging pipeline captures five seed traits (area, length, width, circularity, roundness) relevant to handling and processing efficiency. Applied to 563 RDA buckwheat accessions, it reveals clear species level morphological differences (common buckwheat larger seeds: Table 1 ) and unexpectedly higher among accession dispersion in Tartary buckwheat (higher CVs: Table 2 ; broader PCA ellipses: Fig. 2 ). These phenotypic baselines support germplasm prioritization for seed size/shape despite GxE limitations. Tartary buckwheat shows lower within-accession variation in seed area (mean within-accession CVs: 7.2% vs. 14.1% in common buckwheat; Supplementary Table S3) and relatively tight within-accession clustering in the PCA space (Fig. 2 ), but higher among-accession dispersion at the species level (higher species-level CVs; Table 2 ). Common buckwheat displays higher within-accession variation but lower overall among-accession dispersion in the RDA germplasm. This partitioning is consistent with theoretical expectations that selfing can reduce variation within accessions while allowing divergence among accessions, but our data cannot isolate mating system from other factors such as sample size, breeding history, and origin structure. Multiyear, multi-environment genetic studies will be required to test these hypotheses explicitly. These findings highlight the importance of characterizing trait distribution within germplasm pools before breeding. Morphological diversity in Tartary buckwheat indicates its potential as a source of diverse breeding material for novel cultivars. Breeders should evaluate both variation magnitude and environmental sensitivity to design efficient, stable, and trait-specific strategies, particularly for underutilized or recently domesticated crops. These phenotypic patterns challenge the expectation that selfing species exhibit uniformly lower trait variability. Despite predominant self pollination, Tartary buckwheat shows higher among accession dispersion (Tables 2 and 4 ; Fig. 2 ), while outcrossing common buckwheat appears more uniform. This reversal likely reflects breeding history (longer selection on common buckwheat in Korea), sample size (519 vs. 44 accessions), and germplasm composition (higher wild/unknown proportion in Tartary material) rather than mating system alone. These results emphasize that domestication context and management practices can override theoretical mating system effects in germplasm collections. The among accession dispersion in Tartary buckwheat (Tables 2 and 4 ) may reflect semi independent lineage histories, where selfing lineages diverged via drift and local adaptation across diverse original origins (Supplementary Table S2). Common buckwheat exhibits parallel isolation driven divergence among Korean regional populations, despite higher gene flow from outcrossing. These phenotypic patterns are consistent with but not attributable to mating system theory alone, given unmeasured genetic structure, sample size differences, and genotype by environment effects. Future multi environment trials and population genetic analyses, for example using markers to test lineage divergence via drift or adaptation, will be needed to partition these factors. In the meantime, breeders should consider the reproductive biology of both species alongside these phenotypic baselines when designing strategies for germplasm utilization. Conclusion High throughput image based phenotyping quantitatively reveals that common buckwheat (F. esculentum) produces larger, more uniform seeds, while Tartary buckwheat (F. tataricum) exhibits smaller seeds with greater morphological variability across 563 RDA genebank accessions (Table 1 2; Fig. 2 ). This standardized phenotypic dataset, comprising seed area, width, length, circularity, and roundness measurements from thousands of individual seeds, documents exploitable morphological diversity within both species and establishes essential baseline data for buckwheat breeding programs. These high resolution trait profiles may be able to support strategic parent selection, facilitate identification of diverse germplasm for hybrid development, and inform processing optimization by documenting size/shape differences that affect milling efficiency, germination uniformity, and market quality specifications, even though the underlying genetic and evolutionary mechanisms are not resolved in this study. Supplementary Information Below is the link to the electronic supplementary material. Supplementary Material 1 (69.6KB, docx) Author contributions Ji Eun Park; data curation, formal analysis, investigation, writing—original draft, writing—review and editing. Bo Hwan Kim; data curation, methodology, visualization, writing—original draft, writing—review and editing. Gyung Deok Han; conceptualization, data curation, formal analysis, methodology, writing—original draft. Wook Kim; supervision, validation. Piya Kittipadakul; data curation, investigation. Supachai Vuttipongchaikij; data curation, investigation. Faheem Shehzad Baloch; data curation, investigation. Hyun Jo; writing—review and editing. Jinhyun Ahn; methodology, supervision, validation, writing—review and editing. Yong Suk Chung; conceptualization, methodology, project administration, supervision, validation, writing—original draft, writing—review and editing. Funding It was supported by a grant from the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (RS-2024-00348897) and by Korea Institute of Marine Science & Technology Promotion (KIMST) funded by the Ministry of Oceans and Fisheries, Korea (RS-2025-02303933). Data availability The datasets used and analyzed during the current study are available from the corresponding author upon reasonable request. Declarations Competing interests The authors declare no competing interests. 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