A functional–structural plant model for dwarf tomato ideotype identification in vertical farming

Abstract

Dwarf tomatoes are well suited for vertical farming due to their compact architecture and determinate growth, but their current genotypes are not optimized for high-density indoor systems. We developed the first functional–structural plant (FSP) model tailored to dwarf tomatoes in vertical farming to simulate light interception, photosynthesis, and biomass allocation at the organ level. The model integrates both static and dynamic modes using multiscale tree graph (MTG) formalism to encode plant architecture and was implemented in GroIMP. The model was parameterized and validated using experimental data obtained at multiple planting densities under controlled environmental conditions. The model accurately predicted key plant traits such as fruit dry mass, total dry mass, and leaf area index. In follow-up scenario analyses, we explored model responses to temperature perturbations (± 2 ∘C) and photosynthetically active radiation changes (± 20 %) at selected planting densities, quantifying how these factors modulate the same traits. The model was executed both in dynamic and static mode to assess architectural ideotypes with focus on leaflet morphology, revealing that leaflet curvature and shape influence light distribution and carbon gain, with effects differing across densities and simulation modes. The model highlights the importance of dynamic feedbacks in high-density vertical farming and supports ideotype design through in silico evaluation of morphological traits. This work establishes a validated modelling framework for guiding breeding and cultivation strategies aimed at enhancing productivity and light use efficiency in vertical farming systems.