LuxBio Microgreens: De-Risking Autonomous Crop Phenotyping for Lunar Surface Food Production

NASA's Moon Base requires in situ fresh food production to provide crew nutrition and countermeasures against the vitamin degradation observed in pre-packaged space diets, necessitating cultivar screening on the lunar surface per NASA's Crop Readiness Level (CRL) 3 requirements. This proposal reframes Ames' flight-heritage BioSensor payload, enhanced with FY25/26 LuxBio multi-modal sensing, from an ISS-relevant testbed into a distributed lunar-surface network for autonomous crop cultivar selection. We propose to determine whether crop germination stage and seed vigor, a predictor of resilience, can be deduced from multispectral data. Using microgreens, ideal models that rapidly produce health-critical compounds (e.g., carotenoids, vitamin C), we will grow 16 promising cultivars in BioSensor fluidic cards within the LuxBio optical stack, collecting time-series 12-band spectral data (400–850 nm) alongside daily ground-truth germination-stage assessments over 14-day periods. We will produce characteristic spectra for each germination stage (ungerminated, radicle emergence, cotyledon emergence) using class mean spectra and Jeffreys-Matusita separability, develop a PLSDA classifier validated via confusion matrix, and quantify seed vigor through 14-day germination percentage and cotyledon-emergence uniformity. Supporting Moon-to-Mars Architecture goals (AS-5; TX06.3.5), success would position Ames with uniquely capable, flight-heritage hardware for autonomous cultivar screening across all Moon Base development phases.

The project will generate a time-series dataset of multispectral optical measurements from microgreen cultivars, annotated with germination stages and end-of-run germination percentages. Unique spectral signatures for each germination stage will be identified, enabling the development of a classification model to assess seed vigor and crop resilience. The partial least squares discriminant analysis (PLSDA) model aims for high accuracy in classifying germination stages, supporting autonomous crop screening for lunar food production. All datasets and analysis will be published in open-source repositories, with anticipated peer-reviewed publications and conference presentations. Ultimately, the work will advance flight-heritage hardware for reliable, in situ food production on the lunar surface, positioning Ames for future Moon Base missions

This is a mature technology (TRL 7+) — the realistic path in is usually NASA's Technology Transfer Program: licensing an existing NASA patent, or a Space Act Agreement to use NASA facilities/expertise directly. NASA also runs a startup licensing program with no upfront fee for companies formed to commercialize a specific NASA technology.

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