Significant Influence of EC₅₀ Estimation by Model Choice and EC₅₀ Type.

Area of Science:

• Plant pathology
• Biostatistics
• Mycology

Background:

• Effective concentration (EC50) is crucial for dose-response analysis.
• The R package "drc" offers advanced modeling for EC50 estimation.
• Hormetic effects and EC50 type (absolute/relative) are often overlooked in phytopathology.

Purpose of the Study:

• To demonstrate the impact of model choice and EC50 type on EC50 estimation.
• To highlight the importance of statistical rigor in phytopathological dose-response studies.
• To provide guidelines for accurate EC50 estimation in plant science.

Main Methods:

• Utilized the R package "drc" for dose-response modeling.
• Analyzed data from *Pythium oopapillum* and *Fusarium virguliforme*.
• Compared absolute vs. relative EC50 estimates and various log-logistic models.

Main Results:

• Model choice and EC50 type significantly affected EC50 values for *P. oopapillum*.
• Hormetic effects altered *F. virguliforme* EC50 distributions, yielding higher estimates.
• Differences between absolute and relative EC50 were significant for some *P. oopapillum* isolates.

Conclusions:

• Careful model selection and clear reporting of EC50 measures are essential in phytopathology.
• The R package "drc" provides flexibility but requires informed application.
• Guidelines are provided to improve the accuracy and interpretability of EC50 estimations.