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Millet in Bioregenerative Life Support Systems: Hypergravity Resilience and Predictive Yield Models.

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Millet shows promise for space farming, as hypergravity did not impact its yield. Predictive models were developed to automate crop cultivation and optimize food production for long-duration space missions.

Keywords:
Panicum miliaceum L.bioregenerative life support systemscentrifugationgerminationhypergravityseedling developmentyield componentsyield modeling

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Area of Science:

  • Astrobiology
  • Plant Science
  • Agricultural Engineering

Background:

  • Sustainable food production is crucial for long-distance space exploration.
  • Millet is being investigated as a potential crop for biological life support systems in space.

Purpose of the Study:

  • To evaluate millet's viability in biological life support systems.
  • To develop predictive models for millet yield components to automate cultivation.

Main Methods:

  • Assessing millet response to hypergravity (800–3000 g) during germination.
  • Cultivating millet in a closed system to measure yield and seed characteristics.
  • Describing 40 quantitative plant traits, including leaf, trichome, and grain features.
  • Developing predictive regression equations for biomass and yield components.

Main Results:

  • Hypergravity stress did not negatively affect millet seedlings or yield.
  • Millet yield in a closed system reached 0.31 kg/m², with a 1000-seed weight of 8.61 g.
  • Predictive models were created for biomass accumulation, seed weight, inflorescence number, and grain yield.
  • Detailed phenotyping of 40 quantitative traits was performed.

Conclusions:

  • Millet is a viable crop for space-based food production systems.
  • Predictive models enable automated control and yield optimization for space agriculture.
  • These models support the development of computer vision and phenotyping for space farming.
  • Biomass yield predictions aid in waste processing system assessments for planetary stations.