Methodological approaches for estimating radiosensitivity in Quillaja saponaria: comparison of LD₅₀ models and a...

Quillaja saponaria is an endemic Chilean tree of ecological and economic importance currently threatened by climate change and increasing extraction pressure. Ionizing radiation represents a potential tool to support mutation breeding or radiostimulation strategies however, its effective application requires an accurate characterization of species specific radiosensitivity. This study aimed to characterize radiosensitivity in Q. saponaria by comparing conventional LD₅₀ based approaches with growth based and multivariate methods, and to define biologically meaningful LD₅₀ and GR₅₀ estimates.

Seeds of Q. saponaria were exposed to increasing doses of ionizing radiation. Radiosensitivity was assessed through germination assays, seedling emergence and survival, and morphometric measurements conducted 90 days after sowing. LD₅₀ estimates were obtained from emergence and survival data, whereas GR₅₀ values were derived from individual morphometric traits. In addition, a multivariate approach based on Principal Component Analysis was applied to integrate multiple growth related variables into a single radiosensitivity index.

Seed germination exhibited high resistance to ionizing radiation and did not show a dose dependent response, rendering it unsuitable for LD₅₀ estimation. Seedling emergence and final survival displayed dose dependent patterns, but temporal variability and functional limitations reduced their reliability as radiosensitivity indicators. Morphometric traits exhibited clear and gradual dose response relationships, allowing GR₅₀ estimation. However, GR₅₀ values varied widely among individual traits, ranging from 167 to 347 Gy, reflecting organ and process specific radiosensitivity. Integration of morphometric variables through Principal Component Analysis yielded a multivariate GR₅₀ value of 89 Gy, capturing the combined phenotypic impact of radiation on early seedling development.

Growth based multivariate integration provides a more robust and biologically meaningful framework for radiosensitivity assessment than conventional binary endpoints. The Principal Component Analysis offers an integrative radiosensitivity estimator, supporting its use as a reference threshold for future studies based on ionizing radiation in woody species.