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🎓 Undergraduate Track: Advanced Astrobotany Research

Welcome to the Undergraduate Track of the AstroBotany Investigation Resource (AIR). This track is designed for upper-level undergraduate students, advanced research teams, and educators wishing to integrate cutting-edge space biology, hardware engineering, data science, and computational modeling into their curricula.

🎯 Program Objectives & Core Competencies

By participating in this track, students will develop competencies in the following core areas:

  1. Experimental Design & Execution:
  2. Formulating hypotheses regarding plant behavior in simulated microgravity.
  3. Preparing sterile culture systems (agar plates, tissue culture) for continuous phenotyping.

  4. Utilizing professional simulated-microgravity hardware (clinostats and Random Positioning Machines).

  5. Advanced Phenotypic Analysis & Data Science:

  6. Building and calibrating specialized scientific photography platforms.

  7. Processing image datasets using Python-based pipelines, Fiji/ImageJ, and PlantCV to extract quantitative parameters such as Green Area Index (GAI) and Root System Architecture (RSA).

  8. Computational Biology & Systems Modeling:

  9. Simulating auxin-transport dynamics at a multicellular scale to predict gravitropic curvature.

  10. Quantitative modeling of root hydraulic conductance, hydropatterning, and metabolic pathways.

  11. Omics & Bioinformatics:

  12. Mining NASA Open Science Data Repository (OSDR) / GeneLab to analyze real spaceflight RNA-seq datasets.
  13. Correlating gene expression networks with observed macroscopic phenotypic changes in space environments.

🛠️ Required Equipment & Materials

To fully implement the 12-week schedule, the following resources are recommended:

  • Hardware & Growth Platforms:
  • Simulated microgravity platform (e.g., CoSE SciSpinner Max RPM or custom 2D clinostats).
  • Sterile laminar flow hood or clean-air work bench.
  • Plant growth LED chambers with programmable spectrum and photoperiod control.
  • Consumables:
  • Microgreen seeds (e.g., Mustard, Mizuna, Chia, Radish).
  • High-purity agar-agar or plant-based gellan gum.
  • Murashige & Skoog (MS) basalt salt mixture and plant hormones (e.g., Auxin: 2,4-D or IAA).
  • Petri dishes (100mm x 15mm) and parafilm.
  • Software & Computing:
  • Personal computers or cloud environments (e.g., Google Colab) with Python 3, Fiji/ImageJ, and R.
  • Internet access for database mining (GeneLab, Epicollect5).

🗺️ How to Use This Track

This track is organized into a cohesive 12-week schedule mapped to practical laboratory activities and weekly deliverables.