In indoor and vertical farming systems, the design of the cultivation environment and the selection of operating set-points are crucial to ensure healthy plant development while limiting energy consumption. Plants, however, further increase system complexity, as they are not passive components: as they grow, their physiological activity and structural characteristics evolve, continuously modifying airflow resistance, heat exchange, and moisture release. Adapting environmental conditions over time, rather than relying on fixed control settings throughout the growth cycle, may therefore positively impact overall production performance. In this presentation, we propose a three-dimensional omputational fluid dynamics framework in which the crop is explicitly modeled as an evolving system component. At each growth-cycle step, airflow is simulated by solving the unsteady incompressible turbulent Navier–Stokes equations, accounting for crop-induced resistance through a porous-medium approach. The resulting airflow field is then used to compute the spatial distributions of temperature, water vapor, and carbon dioxide. Source and sink terms within the crop region are obtained from a transpiration model that is dynamically coupled to a crop growth model formulated as a system of ordinary differential equations. Experimental validation is performed using measurements collected in a real vertical farming cell. The proposed framework is then employed to investigate the design of time-dependent climate control strategies for a single-layer indoor farming configuration with top or side air supply through a perforated panel. A surrogate-based multi-objective optimization approach is adopted to explore operating and design conditions aimed at maximizing final biomass while minimizing energy demand, subject to microclimatic constraints within the canopy region. This analysis will provide insights into the potential benefits of accounting for dynamic plant–microclimate interactions and may support the development of energy-efficient, growth-stage-dependent climate management strategies for indoor farming systems.