Applying productivity and phytonutrient profile criteria in modelling species selection of microgreens as Space crops for astronaut consumption

Introduction: Long-duration missions in outer Space will require technologies to regenerate environmental resources such as air and water and to produce food while recycling consumables and waste. Plants are considered the most promising biological regenerators to accomplish these functions, due to their complementary relationship with humans. Plant cultivation for Space starts with small plant growth units to produce fresh food to supplement stowed food for astronauts’ onboard spacecrafts and orbital platforms. The choice of crops must be based on limiting factors such as time, energy, and volume. Consequently, small, fast-growing crops are needed to grow in microgravity and to provide astronauts with fresh food rich in functional compounds. Microgreens are functional food crops recently valued for their color and flavor enhancing properties, their rich phytonutrient content and short production cycle. Candidate species of microgreens to be harvested and eaten fresh by crew members, belong to the families Brassicaceae, Asteraceae, Chenopodiaceae, Lamiaceae, Apiaceae, Amarillydaceae, Amaranthaceae, and Cucurbitaceae. Methods: In this study we developed and applied an algorithm to objectively compare numerous genotypes of microgreens intending to select those with the best productivity and phytonutrient profile for cultivation in Space. The selection process consisted of two subsequent phases. The first selection was based on literature data including 39 genotypes and 25 parameters related to growth, phytonutrients (e.g., tocopherol, phylloquinone, ascorbic acid, polyphenols, lutein, carotenoids, violaxanthin), and mineral elements. Parameters were implemented in a mathematical model with prioritization criteria to generate a ranking list of microgreens. The second phase was based on germination and cultivation tests specifically designed for this study and performed on the six top species resulting from the first ranking list. For the second selection, experimental data on phytonutrients were expressed as metabolite production per day per square meter. Results and discussion: In the final ranking list radish and savoy cabbage resulted with the highest scores based on their productivity and phytonutrient profile. Overall, the algorithm with prioritization criteria allowed us to objectively compare candidate species and obtain a ranking list based on the combination of numerous parameters measured in the different species. This method can be also adapted to new species, parameters, or re-prioritizing the parameters for specific selection purposes.