The MELiSSA project aims to develop a regenerative life support system for long term manned space missions. As part of this initiative, a higher plant compartment will be designed to produce food for the crew, regenerate the atmosphere and contribute to the recycling of some wastes. It is desirable to develop dynamic plant models of plant growth for the prediction of the life support contributions and the enhanced control of the plant growth chamber environment. The main objective will be to provide a certain desired flow of edible biomass; however other fluxes, including carbon dioxide, oxygen, water and nutrients, should also be predicted.

A mass balance approach has been taken to develop simple plant growth models based on the key reactions for biomass production (photosynthesis, photorespiration and dark respiration) and other important related phenomena (light interception, etc.). We focus on maintaining model simplicity while capturing the main dynamical features of growth, so as to improve the model's predictive ability and to allow for an efficient controller to be built. Mass balance equations on biomass, carbon dioxide, oxygen and water have been derived. Reaction kinetics were selected based on plant physiology, standard biochemical reaction knowledge, and a mathematical analysis of terms. The simplified representation of plant metabolism led to some errors in the prediction of important fluxes (most notably oxygen). However, this was corrected by separating the model into several phases of growth (developmental stages) with transition times between stages linked to measurable data. This allowed the changing metabolism to be represented without adding unnecessary complexity. The model was tested on beet and lettuce data. The results show a good prediction of biomass, carbon dioxide, oxygen and water. The next important step in model development should be to consider biomass partitioning, however data on biomass development with time is required before this goal can be realized.