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For long-term manned missions, higher plants cultivation is mandatory for food supply. MELiSSA project (Micro-Ecological Life Support System Alternative) that is developed by ESA includes a higher plants compartment. In order to satisfy the general specification of any MELiSSA compartment, plants’ behavior must be understood and predicted using a knowledge-based and multi-parameter model. This paper concerns the presentation of the building blocks of a structured model, including the main plant processes: plant growth and development, plant architecture and morphology, plant physiology and metabolism for the principal organs (roots, stems, leaves, storage organs e.g. fruits, seeds, tubers…), depending on physical rate limiting processes: light interception, gas transfer, water and nutrients uptake, sap diffusion. Each of these different submodels is described. Light interception depends on the incident light intensity, properties of leaves and the canopy architecture. It permits calculation of the available light energy in order to perform photosynthesis. Gas exchange depends on the atmosphere composition, the stomata processes, the diffusion and dissolution rates, the leaf cells concentration of each exchanged gas and rate of use or production. Sap diffusion depends on the stem morphology, and the metabolic and physical processes of sap movement. Root uptake depends on the nutrient solution concentration and the metabolic and physical processes of nutrients and water absorption. The plant metabolism is used to predict the final composition of the plant, the growth rate and the available energy for the non-photosynthetic organs. Mass and energy balances give the structure of the model of the environmental variables, e.g. atmosphere composition, incident light, temperature, humidity, nutrient solution composition. The morphology and architecture model gives the plant dimensions e.g. stem length, leaf area or root surface, and the development model predicts evolution with time and environment. The general model will permit to predict the CO 2 and nutrient solution consumption, and oxygen, clean water and food production from the plant depending on the plant compartment conditions, using mass balance analysis of the system.