PSRICalc — Plant Stress Response Index Calculator
Direct PSRI Calculation from Germination Data
Author: Richard A. Feiss
Version: 1.0.0
License: MIT
Institution: Minnesota Center for Prion Research and Outreach (MNPRO), University of Minnesota
Overview
PSRICalc provides clean, direct calculation of Plant Stress Response Index (PSRI) values from time-series germination data with optional radicle vigor integration. Built on the methodological foundation of the Osmotic Stress Response Index (OSRI) framework developed by Walne et al. (2020), PSRICalc offers a simplified, transparent approach suitable for agricultural research and statistical analysis.
Unlike complex optimization-based approaches, PSRICalc focuses on direct calculation using established germination parameters: Maximum Stress-adjusted Germination (MSG), Maximum Rate of Germination (MRG), and Mean Time to Germination (MTG).
Why PSRICalc Exists
The need emerged for a standalone, reproducible method to calculate PSRI values without the complexity of full optimization workflows. Researchers needed:
- Transparent methodology: Clear, auditable calculations
- Statistical compatibility: Individual replicate values for proper ANOVA
- Publication readiness: Defendable, straightforward approach
- Accessibility: No complex optimization dependencies
PSRICalc addresses these needs by extracting the core PSRI calculation logic into a focused, user-friendly R package.
Key Features
- Direct calculation: No iterative optimization required
- Radicle integration: Optional vigor assessment from radicle measurements
- Quality control: Built-in mass balance validation
- Statistical ready: Produces individual replicate values for analysis
- Well documented: Complete function documentation with examples
- CRAN compliant: Professional R package standards
Scientific Attribution
PSRICalc builds directly on the Osmotic Stress Response Index (OSRI) methodology established by:
Walne, C.H., Gaudin, A., Henry, W.B., and Reddy, K.R. (2020). In vitro seed germination response of corn hybrids to osmotic stress conditions. Agrosystems, Geosciences & Environment, 3(1), e20087. https://doi.org/10.1002/agg2.20087
Installation
# From CRAN (when available)
install.packages("PSRICalc")
# From source
devtools::install_github("username/PSRICalc")Basic Usage
library(PSRICalc)
# Calculate PSRI from germination data
result <- calculate_psri(
germination_counts = c(5, 8, 10),
time_points = c(3, 5, 7),
total_seeds = 15,
species = "corn"
)
print(result$PSRI)Human–AI Development Transparency
Development followed a collaborative human-machine process with full human oversight. All scientific methodology, mathematical formulations, and validation were designed and conceived by the author.
AI systems (Anthropic Claude) provided substantial assistance with:
- R package structure and CRAN compliance
- Function implementation and code debugging
- Documentation formatting and roxygen2 syntax
- Code organization and best practices
- Professional presentation standards
AI systems did not contribute to:
- Scientific methodology design
- Mathematical formulations
- Biological interpretation
- Research conclusions
Citation
If you use PSRICalc in your research, please cite:
Feiss, R.A. (2025). PSRICalc: Plant Stress Response Index Calculator.
R package version 1.0.0.License
MIT License - see LICENSE file for details.
Related Work
PSRICalc is part of a broader research ecosystem including the GALAHAD and SQUIRE optimization frameworks, but operates independently with no external dependencies beyond base R.