Genetic and phenotypic diversity in cannabis genotypes: insights from seed dimensions, mineral profiles, and Short Tandem Repeats (STR) markers

This study characterized cannabis varieties based on seed physical properties, mineral composition, and Short Tandem Repeats (STR) markers. Eleven cannabis varieties were analyzed, including landraces Ladysmith Ugwayi wesiZulu (‘L1’) and Iswazi (‘L2’), Durban Poison (‘H1’), Bergville Ugwayi wesiZulu (‘B1’), Natal (‘B2’) and Iswazi (‘B3’), and Msinga Ugwayi wesiZulu (‘M1’) and Iswazi (‘M2’), and the commercially available ‘Hemp’, ‘Cherry bubble gum’ (‘High-CBD’) and ‘White Rhino’ (‘High-THC’) varieties. Physical traits measured included seed length, width, thickness, geometric mean diameter, surface area, aspect ratio, and sphericity. Genetic analysis was conducted using sixty-eight STR markers, while mineral composition was assessed using Scanning Electron Microscopy (SEM) with an energy-dispersive X-ray (EDX) detector. Significant differences ( p < 0.001) were found in seed dimensions and surface area, while aspect ratio and sphericity showed no significant variation ( p > 0.05). Elemental composition varied significantly ( p < 0.05), particularly for carbon, oxygen, potassium, phosphorus, sulfur, iron, and silicon. Carbon was highest in ‘High-THC’ (75.10 %) and lowest in ‘H1’ (55.58 %), whereas oxygen showed an inverse trend. Variations in seed dimensions and mineral profiles highlight the diverse genetic and phenotypic landscape of the samples. Positive correlations ( p < 0.001) among varieties suggested similarities in physical traits, mineral composition, and STR markers. However, hierarchical clustering revealed distinct groupings, indicating complex diversity. Landraces could not be reliably classified as ‘High-CBD’, ‘High-THC’, or ‘Hemp’, reflecting STR marker neutrality. Integrating STRs with functional gene markers or metabolic profiling may improve chemotype discrimination and support development of cannabis-specific identification tools. These findings provide insights for breeding programs and optimization of desirable traits. • Correlation analysis revealed similarities among cannabis genotypes. • Agglomerative hierarchical clustering showed differences among genotypes. • Mineral composition clustering differed from physical traits-based grouping. • STR markers produced unique groupings distinct from those based on physical traits. • Differences in clustering highlight the complexity of cannabis genotype diversity.