![Fig. 5 | Lettuce model comparison. a Experimental data (circles) and NP model fits (lines) for lettuce biomass predicted by the MEC model and grown in 3 different nitrogen conditions. b Fitting of m N by values of r, K, and α to experimental mass of N in plant. c Fitting of _ Y N by functions for η N and μ N to nitrogen productivity calculated from experimental data. d Sensitivity analysis result based on the ranges defined by the fitting procedure. The y − axis denotes the variable of interest wile the x − axis represents the corresponding variable's index value. e Fitted NP parameter values for MEC baseline and experimental N conditions. r: governing rate in [d −1 ]; K: limiting value of m N in [g N ]; α: dimensionless scaling factor; η N : nitrogen use efficiency in [g DW g À1 N ]; μ N relative nitrogen accumulation rate in [d −1 ].](https://www.researchgate.net/publication/384431031/figure/fig3/AS:11431281280780407@1727549612377/Lettuce-model-comparison-a-Experimental-data-circles-and-NP-model-fits-lines-for_Q320.jpg)
September 2024
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npj Microgravity
Food production and pharmaceutical synthesis are posited as essential biotechnologies for facilitating human exploration beyond Earth. These technologies not only offer critical green space and food agency to astronauts but also promise to minimize mass and volume requirements through scalable, modular agriculture within closed-loop systems, offering an advantage over traditional bring-along strategies. Despite these benefits, the prevalent model for evaluating such systems exhibits significant limitations. It lacks comprehensive inventory and mass balance analyses for crop cultivation and life support, and fails to consider the complexities introduced by cultivating multiple crop varieties, which is crucial for enhancing food diversity and nutritional value. Here we expand space agriculture modeling to account for nitrogen dependence across an array of crops and demonstrate our model with experimental fitting of parameters. By adding nitrogen limitations, an extended model can account for potential interruptions in feedstock supply. Furthermore, sensitivity analysis was used to distill key consequential parameters that may be the focus of future experimental efforts.
