Quantitative Analysis of Root System Architecture and Fresh Weight Biomass Traits Highlight Phenotypic Variation in Radish (Raphanus sativus L.) Germplasm

Background Radish ( Raphanus sativus L.) exhibits remarkable diversity in its root morphology and architecture, varying widely in length, thickness, shape, and branching patterns. These traits are crucial for nutrient and water uptake, adaptation to stress or different environments and cultivation practices, as well as marketability. Despite their breeding potential, comprehensive evaluation of root traits across diverse genotypes remains limited. This study assessed root morphological and architectural variability in 23 radish accessions, including wild relatives, landraces, and cultivars from nine different countries in order to inform selection and breeding strategies. Results Plants were grown under controlled greenhouse conditions, and root traits quantified using digital imaging and methods. Analysis of variance revealed significant variation (p < 0.01) for almost all traits, across genotype, except average length of link. Descriptive analysis indicated wide variability in most traits, including root length, forks, crossings, and tips. Turkish accessions had the highest average root length and branching traits, while Chinese and Korean accessions exhibited greater root diameter and biomass-related traits. Landraces developed the most extensive root systems, wild relatives showed high trait variability, and cultivars were more uniform in root volume and diameter. Correlation analysis revealed strong positive associations among root length, surface area, projected area, and branching traits, suggesting a coordinated module for soil exploration. Conversely, root fresh weight, root-shoot ratio, and link surface features were negatively correlated with architectural traits. Principal component analysis grouped traits into functional clusters, with the first five components explaining 93.485% of total variation. The first principal component (60.402%) was primarily driven by strong positive loadings from number of root tips, root length, number of crossings, forks, projected area, surface area, and average projected area of link. The cluster and biplot analysis differentiated accessions based on trait expression, and identified accessions PI140433 (G1), HA17 (G18), Kvarta (G19), and CHERISH-1 (G22) as major contributors to phenotypic diversity. Conclusion This study revealed the multidimensional variation in radish root traits and identified valuable accessions with distinct or integrated trait profiles. The study provides a strong foundation for trait-based selection and ideotype development in radish breeding programs targeting improved adaptability, resource-use efficiency, and market traits.