A virtual fruit model to simulate water deficit effects on water and solutes accumulation in the fruit and the consequences on fruit quality

Fruit size and solute composition are quality traits and are mainly determined by soluble sugars, acids, and mineral in concentrations that depend on water and solute translocation and metabolism. Water and sugar translocation depend on transport mechanisms that take place in the vascular system connecting the plant and the fruit. These transports are driven by the fruit water potential, which is determined by the concentrations of solutes in the fruit cell vacuoles. Nevertheless, this concentration determines the fruit osmotic potential itself. Therefore, there is strong feedback between the solutes and water translocation, metabolism, and fruit growth. Water deficit leads to changes in the water status of plants and therefore affects fruit growth. Understanding links between fruit growth processes and the plant growing conditions can be important to improve agricultural techniques and fruit quality. In this work, we show how we can describe such a complex system through a virtual fruit model, i.e., a process-based model composed of sub-modules that describe fruit growth and sugar and acid metabolism by using biophysical relationships. The model simulations well predicted the observed fruit size, and solutes concentrations of three cohorts of two commercial cultivars of tomato. We simulated the model on two scenarios of water deficit and we explored how the biophysical processes involved lead to changes in fruit growth with a focus on the role of sugar and acid accumulation and metabolism. The simulation results suggested that water deficit conditions could increase solutes concentrations and that dilution and osmotic potential changes are important variables to evaluate water deficit effects on fruit solutes content. The presented virtual fruit model is a promising tool to untangle the complex processes that involve fruit growth and to simulate environmental conditions for predicting response in fruit growth processes and their effect on fruit quality.