This paper presents an optimized composition of crop growth areas for biological life support systems with respect to nutrition and equivalent system mass. For this purpose, crop growth area compositions from literature are compared with compositions derived from an optimization algorithm. The optimization algorithm uses literature data for crop growth rates and crop nutrient content to minimize the required crop growth area required to supply all nutrients for a human. The algorithm derives the required crop growth area per crew member under different dietary boundary conditions and the resulting nutrient supply is compared to reported diets from crops for spaceflight. The primary goal of this optimization is to find the minimal area required to supply all relevant macronutrients. The minimal area for the exact desired composition of macronutrients (carbohydrates, fats and proteins) was 106.86 m$^2$ using chard, lettuce, peanut, bell pepper, snap beans and spinach. If a deviation in the macronutrient composition is allowed the required area can be reduced to 39.88 m$^2$ of wheat and white potatoes. Since the variety of crops is a relevant factor for long term food supply, a limit of the maximum growth area per crop was introduced to derive a diet with more variety, which resulted in a minimal area of 57.04 m$^2$ using drybean, rice, snap beans, sweet potato, wheat and white potato. Based on this result, a further manual adjustment of the crop growth areas was performed to also introduce lettuce and tomato in the crops provided and adjust the remaining crop compositions to receive better macro- and micronutrient conformity while maintaining a crop growth area of 57 m$^2$. One major result of this analysis is that soybeans are not the most favorable crop with regard to protein and fat productivity and the focus of NASA crop selection for full nutrient supply on soybean results in exceedingly large required crop areas of 164.15 m$^2$. The resulting crop growth areas from both the optimization and literature are then analyzed as plant growth chambers (PGC) in the Life Support Trade-Off Tool (LiSTOT) of the institute of astronautic from the Technical University of Munich (TUM). LiSTOT calculates the impact of the PGC on an ISS based environmental control and life support system (ECLSS) using averaged steady state values for the plants from literature. Based on this result LiSTOT scales the physical chemical systems and calculates the resulting equivalent system mass (ESM) of the different cases. This approach allows the consideration of not only the PGC ESM, but also the impacts the PGC has on other ECLSS systems and their ESM. The ESM values for PGC were updated to assume LEDs instead of high pressure sodium lamps resulting in a new logistic mass of the PGC of 1.28~kg/(y m$^2$) and a lower specific system mass of 87.7~kg/m$^2$. The mass balance analysis of carbon within the overall ECLSS lead to a reduction of the plant growth area to 50.6 m$^2$ and the break-even time with the ISS ECLSS was calculated to 87.2 years. With more optimistic assumptions for the LED and using urine as nutrient supply this time can be reduced to 14.6 years. The analysis also showed that the derived crop composition is not only favorable regarding nutrient supply but also with regard to the ESM and break-even time compared to previously reported crop compositions. Only the PGC with only wheat and white potatoes has a lower ESM but also provides a less balanced nutrient supply. This PGC is downscaled to 37.55 m$^2$ to achieve carbon balance and a break-even time of 38.4 years or 10.3 years with the optimistic assumptions.
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This paper presents an optimized composition of crop growth areas for biological life support systems with respect to nutrition and equivalent system mass. For this purpose, crop growth area compositions from literature are compared with compositions derived from an optimization algorithm. The optimization algorithm uses literature data for crop growth rates and crop nutrient content to minimize the required crop growth area required to supply all nutrients for a human. The algorithm derives the...
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