Li-Chia-ching/AlfalfaGeoSelect

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Authors: Jiaqing Li
Cited by: 0

Abstract

AlfalfaGeoSelect v3.0 First public release – publication-ready selection pipeline This is the first official public release of AlfalfaGeoSelect, a reproducible R-based workflow for selecting elite alfalfa (Medicago sativa) hybrid candidates using a weighted geometric index and professional-grade visualization. Although internally iterated prior to release, this version establishes v3.0 as the stable baseline for future development and citation. Key Features Weighted geometric selection index Integrates plant height and multifoliate score Explicit cutoff-based Top-N (Top 50 by default) selection Robust phenotypic data handling Automatic reshaping from field-layout wide tables Intelligent input detection (workspace objects or CSV files) Explicit handling of missing or dead plants Publication-ready visualization Contour-based selection surface Clearly annotated cutoff threshold Vector-based directional annotation (no special characters) High-resolution, journal-quality output Fully script-driven and reproducible Automatic dependency checking Timestamped output directories Deterministic ranking and selection logic Visualization Improvements Replaced symbolic annotations with true vector arrows using geom_segment Improved visual hierarchy for selected vs. non-selected plants Clean minimal theme suitable for manuscript figures Compatibility & Maintenance Resolved ggplot2 deprecation warning Updated element_rect(size = …) → element_rect(linewidth = …) Ensures compatibility with ggplot2 ≥ 3.4.0 No impact on results or appearance, but improves long-term stability Output Artifacts Each run generates a timestamped directory containing: Plot_Geometric_Selection_Pro.png High-resolution contour-based selection figure 01_Selection_List.csv Ranked list of selected elite plants Intended Audience Alfalfa and forage crop breeding programs Multi-trait phenotypic selection studies Reproducible research and methods papers Trait integration and selection index demonstrations Notes Internal code header reflects continued refinement (v3.2), while v3.0 is defined as the first public, citable release. Future releases will build upon this stable analytical and visual framework. Recommended citation: AlfalfaGeoSelect v3.0 – Weighted geometric selection and visualization pipeline for alfalfa hybrid screening.

Fields of Study & Subjects

Genetic and Environmental Crop Studies Data Visualization and Analytics Scientific Computing and Data Management

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
20 January 2026