Phenotypic diversity and preliminary phytochemical screening of Iranian Datura populations: a descriptive baseline study under controlled greenhouse conditions

Medicinal plants belonging to the genus Datura are prized for their production of bioactive tropane alkaloids and other therapeutic compounds. Systematic genetic improvement of these species is hindered by a lack of fundamental genetic information. This study evaluated morphological, physiological, and phytochemical diversity in 23 natural populations of Datura stramonium L. and D. innoxia collected from across Iran. Seeds were cultivated under controlled greenhouse conditions in a completely randomized design with three replications during 2022. Nested ANOVA partitioning species and population-level effects revealed that species identity was significant for 3 of 18 traits (LL, LW, and SWT), while population-level differences within species were highly significant for all traits, accounting for up to 99.99% of phenotypic variance. Analysis of variance revealed highly significant differences among populations across all traits assessed. These findings demonstrate that Iranian Datura populations harbor substantial genetic diversity at the population level, independent of species identity. Plant height was the most variable morphological trait (GCV = 42.80%), yet phytochemical and physiological traits displayed the highest population-level repeatability (R² = 0.96–0.99) and high potential population differentiation index (PDI = 67–116%) at the population level assuming a selection intensity of 10%, with antioxidant activity and chlorophyll b emerging as the most responsive traits (116% and 113%, respectively). These estimates, derived under controlled greenhouse conditions, reflect population-level differentiation and repeatability of population means; they serve as preliminary indicators for identifying promising populations for further evaluation. However, validation in multi-environment trials with appropriate genetic designs is required before these estimates can guide breeding decisions. Multivariate analyses, including hierarchical clustering, principal components analysis, and canonical correlation analysis, effectively distinguished populations and unveiled distinct trait associations. Canonical correlation analysis revealed a strong association between preliminary phytochemical/physiological and agronomic trait sets, with chlorophyll SPAD serving as the key linking trait, and clearly separated D. innoxia (superior seed traits) from D. stramonium (higher phenolic content). Heatmap correlation analysis grouped traits into three clusters: seed and reproductive traits (strongly inter-correlated), leaf morphology with phenolics (weakly associated), and pigments with antioxidant capacity (strongly correlated). Four populations S2P3 (Kerman, Kerman), S2P9 (Amiriyeh, Isfahan), S2P14 (Amol, Mazandaran), and S1P3 (Razavi Khorasan) exhibited superior performance across multiple traits, representing promising candidates for Datura improvement and warranting further investigation through targeted phytochemical profiling to quantify specific bioactive compounds. These findings establish a descriptive baseline that prioritizes the population for further investigation.